diff --git a/.gitignore b/.gitignore index d233484e1e..e519f83cb6 100644 --- a/.gitignore +++ b/.gitignore @@ -10,4 +10,7 @@ __pycache__/ **/tmp/ dc_generated/ # Ignore the data folder under the un_census/enhanced_tmcf/ directory. -*/*/*/data/* \ No newline at end of file +*/*/*/data/* +lib/ +bin/ +pyvenv.cfg \ No newline at end of file diff --git a/.gitmodules b/.gitmodules new file mode 100644 index 0000000000..e688780163 --- /dev/null +++ b/.gitmodules @@ -0,0 +1,3 @@ +[submodule "scripts/un/sdg/sdg-dataset"] + path = scripts/un/sdg/sdg-dataset + url = https://code.officialstatistics.org/undata2/data-commons/sdg-dataset.git diff --git a/LICENSE-CC4 b/LICENSE-CC4 new file mode 100644 index 0000000000..c8c8904059 --- /dev/null +++ b/LICENSE-CC4 @@ -0,0 +1,7 @@ +Copyright 2023 Google LLC + +The non-source code materials in this project are licensed under: +Creative Commons - Attribution CC-BY 4.0 + +For the full license text, please visit: +https://creativecommons.org/licenses/by/4.0/legalcode diff --git a/README.md b/README.md index 5785834e69..8025776022 100644 --- a/README.md +++ b/README.md @@ -249,7 +249,6 @@ To disable yapf for some lines, For general questions or issues about importing data into Data Commons, please open an issue on our [issues](https://github.com/datacommonsorg/data/issues) -page. For all other questions, please send an email to -`support@datacommons.org`. +page. For all other questions, please [share feedback on this form](https://docs.google.com/forms/d/e/1FAIpQLScJTtNlIItT-uSPXI98WT6yNlavF-kf5JS0jMrCvJ9TPLmelg/viewform). **Note** - This is not an officially supported Google product. diff --git a/docs/README.md b/docs/README.md index c9616d2738..bef69acb3d 100644 --- a/docs/README.md +++ b/docs/README.md @@ -1,63 +1,42 @@ # Adding a Dataset to Data Commons -This document summarizes the steps involved in adding a dataset to Data Commons -(DC). As a prerequisite, please ensure that the DC core team -(support@datacommons.org) has approved the addition of the dataset. +This document summarizes the steps involved in adding a dataset to Data Commons (DC). -## Background +## Prerequisites -The following documents provide a background on the data model, format and workflow: +* Ensure that the Data Commons team has approved the addition of the dataset. Please [suggest a dataset here](https://docs.google.com/forms/d/e/1FAIpQLSf_kZ13bmzXvgEbim0OXeAVsTQYsIhN8_o9ekdbjKoeFjfvRA/viewform). +* Review the following documents to get a background on the data model, format and workflow: + * [Summary of data model](https://schema.org/docs/datamodel.html) (DC inherits schema from schema.org) + * [How statistics is represented in DC](representing_statistics.md) + * [MCF Format](mcf_format.md) + * [Life of a dataset](life_of_a_dataset.md) -1. [Summary of data model](https://schema.org/docs/datamodel.html) (DC inherits schema from schema.org) -1. [How statistics is represented in DC](representing_statistics.md) -1. [MCF Format](mcf_format.md) -1. [Life of a dataset](life_of_a_dataset.md) +## Design location and schema mapping -## Designing location and schema mapping +Data Commons is a single graph that reconciles references to the same entities and concepts across datasets. This linking happens at the time of importing datasets. To get started: -Data Commons is a single graph that reconciles references to the same entities -and concepts across datasets. This linking happens at the time of importing -datasets. +* Identify how the locations/places/entities and variables/properties in the dataset will get mapped. +* For locations/places, use the following (in preferred order): global identifiers (like FIPS), geo info (lat/lng, geo boundary), qualified names. +* For variables, find already existing schema in Data Commons (from existing statistical variables [here](https://datacommons.org/tools/statvar)), or add new StatisticalVariable nodes along with core schema (new Class, Property, Enumeration nodes) as necessary. -As part of the first step, we identify how the locations/places/entities and -variables/properties in the dataset will get mapped. +This process typically happens in collaboration with the DC core team, and we recommend that you put together a short import document ([Template](https://docs.google.com/document/d/1RUOD3VLZFBmyjZzBnwQBKB9TxNE7NhD4g9WX6gUZCQU/), [Example1](https://docs.google.com/document/d/e/2PACX-1vScfoVm36L7x1p4Bqh82JmDmsumhqiPz_w6zX7wzy0nX8kDLxMJw44hOBgB6CDd2o0kYKekdgNWIR1f/pub), [Example2](https://docs.google.com/document/d/e/2PACX-1vS9R0eZO-AhQ19jQcLyOyYODn3dF8wGjytro0nFTjp4MsoFvsAgD7mayppcseLvNSCO6Ac4-8b2SXe4/pub)) -* For locations/places, we can use the following (in preferred order): global -identifiers (like FIPS), geo info (lat/lng, geo boundary), qualified names. -The approach we use depends on how the locations appear in the dataset. - -* For variables, we either need to find already existing schema in Data Commons -(from existing statistical variables -[here](https://datacommons.org/tools/statvar)), or add new StatisticalVariable -nodes along with core schema (new `Class`, `Property`, `Enumeration` nodes) as -necessary. - -This process typically happens in collaboration with the DC core team, and we -recommend that you put together a short import document. - -Links: -* Suggested [import document template](https://docs.google.com/document/d/1RUOD3VLZFBmyjZzBnwQBKB9TxNE7NhD4g9WX6gUZCQU/) -* [Example1](https://docs.google.com/document/d/e/2PACX-1vScfoVm36L7x1p4Bqh82JmDmsumhqiPz_w6zX7wzy0nX8kDLxMJw44hOBgB6CDd2o0kYKekdgNWIR1f/pub) -* [Example2](https://docs.google.com/document/d/e/2PACX-1vS9R0eZO-AhQ19jQcLyOyYODn3dF8wGjytro0nFTjp4MsoFvsAgD7mayppcseLvNSCO6Ac4-8b2SXe4/pub) - -## Schema-less imports - -For datasets with complex schema or ones that we want to import quickly, we can start with a schema-less import, and iteratively add schema. The “schema-less” part of this framework means that the SV is not yet fully defined. This lets us get the dataset into Data Commons without blocking on schema definition. - -Links: -* [Schema-less Import Guide](https://docs.datacommons.org/import_dataset/schema_less_guide.html) -* [Import document template](https://docs.google.com/document/d/1GC7DTpxXo_3zreDRt7wFuURBfA1T275p-qx1N-VIdGM/) -* [Example](https://docs.google.com/document/d/e/2PACX-1vS6ItxH7T_XvYuz4-xeO9LKoYlrXr-YkrwiclRWcdtYm11J8OQHUwDw4E66uaTQA7yTdwLXfrNBdKgz/pub) +### Schema-less imports +For datasets with complex schema or ones that we want to import quickly, we can start with a schema-less import, and iteratively add schema. The “schema-less” part of this framework means that the statistical variables are not yet fully defined. This lets us get the dataset into Data Commons without blocking on schema definition. To learn more, please review the following links: + * [Schema-less Import Guide](https://docs.datacommons.org/import_dataset/schema_less_guide.html) + * [Schema-less import document template](https://docs.google.com/document/d/1GC7DTpxXo_3zreDRt7wFuURBfA1T275p-qx1N-VIdGM/) + * [Example](https://docs.google.com/document/d/e/2PACX-1vS6ItxH7T_XvYuz4-xeO9LKoYlrXr-YkrwiclRWcdtYm11J8OQHUwDw4E66uaTQA7yTdwLXfrNBdKgz/pub) ## Preparing artifacts -Once the entity and schema mapping have been finalized, you prepare the artifacts. This includes: +Once the entity and schema mapping have been finalized, you can now prepare the artifacts. This includes: + * StatisticalVariable MCF nodes (if any) checked into [schema repo](https://github.com/datacommonsorg/schema/tree/main/stat_vars) + * Template MCF and corresponding cleaned tabular files (typically CSV). + * Data cleaning code (along with README) checked into [data repo](https://github.com/datacommonsorg/data) + * Validation results for the artifacts (from running [`dc-import`](https://github.com/datacommonsorg/import#using-import-tool) tool) + +Note: you may also use the [DC Import Wizard](https://datacommons.org/import) to help generate artifacts for common dataset structures -1. StatisticalVariable MCF nodes (if any) checked into [schema repo](https://github.com/datacommonsorg/schema/tree/main/stat_vars). These nodes may be written by hand when there are only a handful in number. Otherwise, these nodes can be generated via scripts. -2. Template MCF and corresponding cleaned tabular files (typically CSV). Like StatisticalVariable MCF nodes, the Template MCF nodes can also be hand-written or script-generated depending on number of nodes. -3. Data cleaning code (along with README) checked into [data repo](https://github.com/datacommonsorg/data) -4. Validation results for the artifacts (from running [`dc-import`](https://github.com/datacommonsorg/import#using-import-tool) tool) +## Review by DC team -When all the artifacts are ready, please get it reviewed by the DC core team -via github Pull Requests. More details on this step are in the [Life of a -Dataset](life_of_a_dataset.md) document. +When all the artifacts are ready, please get it reviewed by the DC core team via github Pull Requests made to the [data repo](https://github.com/datacommonsorg/data). diff --git a/import-automation/import-progress-dashboard-frontend/client/package-lock.json b/import-automation/import-progress-dashboard-frontend/client/package-lock.json index c27041f942..5b3e443ee2 100644 --- a/import-automation/import-progress-dashboard-frontend/client/package-lock.json +++ b/import-automation/import-progress-dashboard-frontend/client/package-lock.json @@ -4,475 +4,448 @@ "lockfileVersion": 1, "requires": true, "dependencies": { - "@babel/code-frame": { - "version": "7.10.4", - "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.10.4.tgz", - "integrity": "sha512-vG6SvB6oYEhvgisZNFRmRCUkLz11c7rp+tbNTynGqc6mS1d5ATd/sGyV6W0KZZnXRKMTzZDRgQT3Ou9jhpAfUg==", + "@aashutoshrathi/word-wrap": { + 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a/requirements.txt b/requirements.txt index cd05657803..663ced4214 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,33 +1,37 @@ # Requirements for all Python code in this repo, except for import-automation -absl-py==0.9.0 +absl-py arcgis2geojson chembl-webresource-client>=0.10.2 dataclasses==0.6 datacommons==1.4.3 deepdiff==6.3.0 +earthengine-api flask_restful==0.3.9 frozendict==1.2 func-timeout==4.3.5 geojson==2.5.0 geopandas==0.8.1 +geopy +google-cloud-bigquery google-cloud-storage>=2.7.0 google-cloud-logging==3.4.0 google-cloud-scheduler==2.10.0 gspread lxml==4.9.1 matplotlib==3.3.0 -netCDF4==1.5.7 -numpy==1.18.5 +netCDF4 +numpy openpyxl==3.0.7 pandas==1.3.5 pylint pytest +rasterio rdp==0.8 requests==2.27.1 retry==0.9.2 s2sphere==0.2.5 -shapely==1.8 +shapely==1.8.5 tabula-py urllib3==1.26.8 xarray==0.19.0 diff --git a/run_tests.sh b/run_tests.sh index 307c46e0d4..becb877838 100755 --- a/run_tests.sh +++ b/run_tests.sh @@ -45,7 +45,7 @@ function run_py_lint_test { setup_python echo "#### Testing Python lint" if ! yapf -r --diff -p --style=google $PYTHON_FOLDERS; then - echo "ERROR: Fix lint errors by running ./run_test.sh -f" >&2 + echo "ERROR: Fix lint errors by running ./run_tests.sh -f" >&2 exit 1 fi } @@ -66,7 +66,7 @@ function help { echo "Usage: $0 -rplaf" echo "-r Install Python requirements" echo "-l Test lint on Python code" - echo "-p Run Python tests in specified folder, e.g. ./run_test.sh -p util" + echo "-p Run Python tests in specified folder, e.g. ./run_tests.sh -p util" echo "-a Run all tests" echo "-f Fix lint" exit 1 diff --git a/scripts/earthengine/README.md b/scripts/earthengine/README.md index db05c23d98..81b0edf136 100644 --- a/scripts/earthengine/README.md +++ b/scripts/earthengine/README.md @@ -139,6 +139,19 @@ python3 process_events.py \ # - flood_svobs.{csv}: Observations for each event ``` +## Events pipeline +The script `events_pipeline.py` can run all the above steps, including +downloading data from URLs or extracting geoTiff from EarthEngine and +generate events from the data. + +It uses a config with settings for each stage and can resume processing +from a previous instance, incrementally processing new data. +``` +# Process data from source to generate events +python3 events_pipeline.py \ + --config=events_pipeline_config.py +``` + ## Testing To test the scripts in this folder, run the commands: diff --git a/scripts/earthengine/common_flags.py b/scripts/earthengine/common_flags.py new file mode 100644 index 0000000000..d5cf2bf388 --- /dev/null +++ b/scripts/earthengine/common_flags.py @@ -0,0 +1,20 @@ +# Copyright 2022 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the 'License'); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an 'AS IS' BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Common flags used across scripts.""" + +from absl import flags + +flags.DEFINE_string('input_csv', '', 'CSV file to process') +flags.DEFINE_string('config', '', 'Config dictionary with parameter settings.') +flags.DEFINE_bool('debug', False, 'Enable debug messages.') diff --git a/scripts/earthengine/earthengine_image.py b/scripts/earthengine/earthengine_image.py index 0bef5a4774..a0d7a1185c 100644 --- a/scripts/earthengine/earthengine_image.py +++ b/scripts/earthengine/earthengine_image.py @@ -56,8 +56,19 @@ from datetime import timedelta from dateutil.relativedelta import relativedelta -flags.DEFINE_string('config', '', - 'File with configuration parameters as a dictionary.') +_SCRIPTS_DIR = os.path.dirname(__file__) +sys.path.append(_SCRIPTS_DIR) +sys.path.append(os.path.dirname(_SCRIPTS_DIR)) +sys.path.append(os.path.dirname(os.path.dirname(_SCRIPTS_DIR))) +sys.path.append( + os.path.join(os.path.dirname(os.path.dirname(_SCRIPTS_DIR)), 'util')) + +import common_flags +import file_util +import utils + +from counters import Counters + flags.DEFINE_string('ee_dataset', '', 'Load earth engine data set define in config datasets.') flags.DEFINE_string('gcs_output', '', 'Prefix for output file names on GCS.') @@ -108,7 +119,6 @@ 'Number of images to generate, each advanced by --time_period.') flags.DEFINE_bool('ee_export_image', True, 'If true, submit a task to export image.') -flags.DEFINE_bool('debug', False, 'Enable debug messages.') _FLAGS = flags.FLAGS _FLAGS(sys.argv) # Allow invocation without app.run() @@ -199,6 +209,9 @@ 'debug': _FLAGS.debug, } +# Interval in secs to cehck for EE task status +_EE_TASK_WAIT_INTERVAL = 10 + def _update_dict(src_dict: dict, dst_dict: dict) -> dict: '''Merge the src and dst dict, merging dictionary values instead of overwriting.''' @@ -238,37 +251,6 @@ def _load_config(config: str, default_config: dict = EE_DEFAULT_CONFIG) -> dict: return config_dict -def _parse_time_period(time_period: str) -> (int, str): - '''Parse time period into a tuple of (number, unit), for eg: P1M: (1, month).''' - re_pat = r'P?(?P[+-]?[0-9]+)(?P[A-Z])' - m = re.search(re_pat, time_period.upper()) - if m: - m_dict = m.groupdict() - delta = int(m_dict.get('delta', '0')) - unit = m_dict.get('unit', 'M') - period_dict = {'D': 'days', 'M': 'months', 'Y': 'years'} - period = period_dict.get(unit, 'day') - return (delta, period) - return (0, 'days') - - -def _advance_date(date_str: str, - time_period: str, - date_format: str = '%Y-%m-%d') -> str: - '''Returns the date string advanced by the time period.''' - next_date = '' - if not date_str: - return next_date - dt = datetime.strptime(date_str, date_format) - (delta, unit) = _parse_time_period(time_period) - if not delta or not unit: - logging.error( - f'Unable to parse time period: {time_period} for date: {date_str}') - return next_date - next_dt = dt + relativedelta(**{unit: delta}) - return next_dt.strftime(date_format) - - def _get_bbox_coordinates(bounds: str) -> ee.Geometry.BBox: '''Returns a bounding box coordinates dictionary for the bounds. bounds is a comma separated list of points of the form [lat,lng...].''' @@ -331,7 +313,7 @@ def ee_filter_date(col: ee.ImageCollection, end_dt = ee.Date(end_date) elif time_period: # Extract the delta and units from the period such as 'P1M'. - end_date = _advance_date(start_date, time_period) + end_date = utils.date_advance_by_period(start_date, time_period) end_dt = ee.Date(end_date) if end_dt is None: end_dt = ee.Date(date.today().strftime('%Y-%m-%d')) @@ -579,45 +561,29 @@ def export_ee_image_to_gcs(ee_image: ee.Image, config: dict = {}) -> str: if config.get('ee_bounds'): bbox_coords = _get_bbox_coordinates(config['ee_bounds']) region_bbox = ee.Geometry.BBox(**bbox_coords) - file_prefix = config.get('gcs_output') - if not file_prefix: - # Create name from config parameters. - img_config = [ - ('ee_image', - config.get( - 'ee_dataset', - config.get('ee_image', - config.get('ee_image_collection', 'ee_image')))) - ] - img_config.append(('band', config.get('band', ''))) - reducers = config.get('ee_reducer') - if reducers: - img_config.append(('r', str(reducers))) - img_config.append(('mask', config.get('ee_mask', ''))) - img_config.append(('s', str(config.get('scale', '')))) - img_config.append(('from', config.get('start_date', ''))) - img_config.append(('to', config.get('end_date', ''))) - if bbox_coords: - img_config.append( - ('bbox', '_'.join([f'{p:.2f}' for p in bbox_coords.values()]))) - file_prefix = '-'.join( - '_'.join((p, v)) for p, v in img_config if v and isinstance(v, str)) - file_prefix = re.sub(r'[^A-Za-z0-9_-]', '_', file_prefix) - scale = config.get('scale', 1000) + # Create output filename prefix from config parameters. + # Large images may be sharded across multiple tif files. gcs_bucket = config.get('gcs_bucket', '') - gcs_folder = config.get('gcs_folder', '') - if gcs_folder and gcs_folder[-1] != '/': - gcs_folder = gcs_folder + '/' + file_prefix = get_gcs_file_prefix_from_config(config, bbox_coords) + if config.get('skip_existing_output', True): + gcs_path = f'gs://{gcs_bucket}/{file_prefix}*.tif' + existing_images = file_util.file_get_matching(gcs_path) + if existing_images: + logging.info( + f'Skipping ee image generation for existing files: {existing_images}' + ) + return None + scale = config.get('scale', 1000) logging.info( - f'Exporting image: {ee_image.id()} to GCS bucket:{gcs_bucket}, {gcs_folder}{file_prefix}' + f'Exporting image: {ee_image.id()} to GCS bucket:{gcs_bucket}, {file_prefix}*.tif' ) task = ee.batch.Export.image.toCloudStorage( - description=file_prefix[:90], + description=file_prefix.split('/')[-1][:90], image=ee_image, region=region_bbox, scale=scale, bucket=gcs_bucket, - fileNamePrefix=f'{gcs_folder}{file_prefix}', + fileNamePrefix=f'{file_prefix}', maxPixels=10000000000000, fileFormat='GeoTIFF') task.start() @@ -634,11 +600,19 @@ def ee_process(config) -> list: For supported params, refer to _DEFAULT_CONFIG. if ee_image_count > 1, then multiple images are exported with the start_time, end_time advanced by time_period. + Returns: + List of competed task status with gfs_file set to the image generated + if config['ee_wait_task'] is True, else a list of tasks launched. ''' ee_tasks = [] ee.Initialize() config['ee_image_count'] = config.get('ee_image_count', 1) - while config['ee_image_count'] > 0: + time_period = config.get('time_period', 'P1M') + cur_date = utils.date_format_by_time_period(utils.date_today(), time_period) + counters = Counters() + # Get images by count or until yesterday + while (config['ee_image_count'] and + (config.get('start_date', '') < cur_date)): logging.info(f'Getting image for config: {config}') img = ee_generate_image(config) if isinstance(img, ee.ImageCollection): @@ -648,30 +622,108 @@ def ee_process(config) -> list: logging.info(f'Generated image {img.get("id")}') if config.get('ee_export_image', True): task = export_ee_image_to_gcs(img, config) - ee_tasks.append(task) + if task is not None: + ee_tasks.append(task) + counters.add_counter('total', 1) else: logging.error(f'Failed to generate image for config: {config}') # Advance time to next period. - time_period = config.get('time_period', 'P1M') for ts in ['start_date', 'end_date']: - dt = _advance_date(config.get(ts, ''), time_period) + dt = utils.date_advance_by_period(config.get(ts, ''), time_period) if dt: config[ts] = dt config['ee_image_count'] = config['ee_image_count'] - 1 logging.info(f'Advanced dates by {time_period}: {config}') + logging.info(f'Created ee tasks: {ee_tasks}') + completed_tasks = [] + if not config.get('ee_wait_task', True): + return ee_tasks + # Wait for tasks to complete - if config.get('ee_wait_task', True): - pending_tasks = set(ee_tasks) - while len(pending_tasks) > 0: - task = pending_tasks.pop() - if task.active(): - pending_tasks.add(task) - logging.info(f'Waiting for task: {task}') - time.sleep(10) - else: - task_status = ee.data.getTaskStatus(task.id) - logging.info(f'EE task completed: {task_status}') + pending_tasks = set(ee_tasks) + while len(pending_tasks) > 0: + task = pending_tasks.pop() + if task.active(): + pending_tasks.add(task) + logging.info(f'Waiting for task: {task}') + time.sleep(_EE_TASK_WAIT_INTERVAL) + else: + task_status = ee.data.getTaskStatus(task.id) + logging.info(f'EE task completed: {task_status}') + for status in task_status: + # Get the destination file for each completed task. + image_file = status.get('description', '') + gcs_path = status.get('destination_uris', [])[0] + if gcs_path and image_file: + gcs_path = re.sub('https.*storage/browser/', 'gs://', + gcs_path) + status['output_file'] = f'{gcs_path}{image_file}.tif' + completed_tasks.append(status) + counters.add_counter('processed', 1) + return completed_tasks + + +def get_gcs_file_prefix_from_config(config: dict, + bbox_coords: ee.Geometry.BBox) -> str: + '''Returns the file name prefix from the config settings. + The filename is of the form: + {gcs_folder}/ee_image--band_-r_-mask_ + -s_-from_-to_YYYY-MM-DD + The GCS bucket is added by the caller to get the full path. + ''' + # Return the file prefix set in the config. + file_prefix = config.get('gcs_output') + if file_prefix: + return file_prefix + # Collect all config tuples (parameter, value) to be addd to the filename + img_config = [('ee_image', + config.get( + 'ee_dataset', + config.get('ee_image', + config.get('ee_image_collection', + 'ee_image'))))] + img_config.append(('band', config.get('band', ''))) + reducers = config.get('ee_reducer') + if reducers: + img_config.append(('r', str(reducers))) + img_config.append(('mask', config.get('ee_mask', ''))) + img_config.append(('s', str(config.get('scale', '')))) + img_config.append(('from', config.get('start_date', ''))) + img_config.append(('to', config.get('end_date', ''))) + if bbox_coords is not None: + # Add bounding box if specified + img_config.append( + ('bbox', '_'.join([f'{p:.2f}' for p in bbox_coords.values()]))) + + # Merge all parameters with non-empty values. + file_prefix = '-'.join( + '_'.join((p, v)) for p, v in img_config if v and isinstance(v, str)) + + # Remove any special characters + file_prefix = re.sub(r'[^A-Za-z0-9_-]', '_', file_prefix) + gcs_folder = config.get('gcs_folder', '') + if gcs_folder and gcs_folder[-1] != '/': + gcs_folder = gcs_folder + '/' + return f'{gcs_folder}{file_prefix}' + + +def get_date_from_filename(filename: str, time_period: str = '') -> str: + '''Returns the date from the filename. + GeoTifs generated by EE may not have the date as a band. + Args: + filename: string of the form '*_from__*.tif', + the filename for generated geoTifs from get_file_prefix_from_config(). + time_period: string of the form P, for eg: P1D. + ''' + # Get the date from the filename + matches = re.search(r'from_(?P[0-9]{4}[0-9-]{2}[0-9-]{0,2})', + filename) + if matches: + # format the date string into YYYY-MM or YYYY by the time period. + return utils.date_format_by_time_period( + matches.groupdict().get('date', ''), time_period) + return '' def main(_): diff --git a/scripts/earthengine/event_config.py b/scripts/earthengine/event_config.py index 3e4c8af386..22783fe59c 100644 --- a/scripts/earthengine/event_config.py +++ b/scripts/earthengine/event_config.py @@ -1,26 +1,82 @@ -# Config settings for event aggregations. +# Config settings for generating events with process_events.py { - # Input settings. - # Columms of input_csv that are added as event properties - 'data_columns': ['area'], + # EventType used for StatVars and tMCFs + 'event_type': 'FloodEvent', + + ### Input settings. + + # Delimiter in the input CSV + 'input_delimiter': ',', + + # Map to rename input columns to output columns with entries as: + # '': '' + # Rest of the configs below refer to the renamed columns. + # Only output columns starting with lower case are added to tmcf. 'input_rename_columns': { 'date': 'observationDate', }, - # Input column for date. - 'date_column': 'observationDate', - # Columns of input_csv that contains the s2 cell id. + + # Columms of input_csv (after renaming) that are added as event properties + 'input_columns': ['area'], + + # Input CSV column (after renaming) that contain the place, such as, s2 cell id. 'place_column': 's2CellId', - # Processing settings - # Maximum distance within which 2 events are merged. - 'max_overlap_distance_km': 0, - # Maximum number of cells of same level in between 2 events to be merged. - 'max_overlap_place_hop': 2, + # Input CSV column (after renaming) for date. + 'date_column': 'observationDate', + + ### Processing settings + + # Maximum distance between places that are merged into the same event. + 'max_overlap_distance_km': 10, + # S2 level to which data is aggregated. - 's2_level': 10, # Events are at resolution of level-10 S2 cells. - 'aggregate': 'sum', # default aggregation for all properties - # Per property settings + # In case input place is an S2 cell of higher level, it is aggregated into + # a parent S2 cell of this level. + 's2_level': 10, # Events at level-10 S2 cells, roughly 10x10km. + + # Event property settings. + # Default aggregation for all event properties + 'aggregate': 'sum', + # Per property filter params for input data. + 'input_filter_config': { + # '' : { + # 'min': , + # 'max': , + # 'regex': '', + # }, + # For example: 'area': { 'min': 1 }, + }, + # Per property filter params for output events + # Applied when output_events is True + # Event is dropped if any property fails the filter. + 'output_events_filter_config': { + # '' : { + # 'min': , + # 'max': , + # 'regex': '', + # }, + # For example: to generate events with area of atleast 10sqkm, + # 'area' { 'min': 10 } + }, + # Per property aggregation settings for an event across places and dates. + # For different per-date and per-place aggregations, use the settings + # 'property_config_per_date' and 'property_config_across_dates'. 'property_config': { + 'aggregate': 'max', + 'area': { + 'aggregate': 'sum', + 'unit': 'SquareKilometer', + }, + 'affectedPlace': { + 'aggregate': 'list', + }, + }, + # Per property aggregation settings for a date across multiple places. + # Falls back to 'property_config' if not set. + 'property_config_per_date': { + # Default aggregation for all properties: pick max value across places. + 'aggregate': 'max', 'area': { 'aggregate': 'sum', 'unit': 'SquareKilometer', @@ -29,12 +85,81 @@ 'aggregate': 'list', }, }, - # Treat events at the same location more than 45 days apart as separate events. - 'max_event_interval_days': 45, + # Per property aggregation settings across multiple dates. + # Falls back to 'property_config' if not set. + 'property_config_across_dates': { + # Default aggregation for all properties: pick max value across dates. + 'aggregate': 'max', + 'area': { + 'aggregate': 'max', + 'unit': 'SquareKilometer', + }, + 'affectedPlace': { + 'aggregate': 'list', + }, + }, + # Threshold for dates and places added to an event + # Treat incidents at the same location more than 90 days apart as separate events. + 'max_event_interval_days': 90, + # Treat incidents after 90 days from start as a seperate event. + 'max_event_duration_days': 90, + # Treat incidents at more than 10000 places into seperate events. + 'max_event_places': 10000, - # Output settings. - 'event_type': 'FloodEvent', - 'output_svobs': True, - 'output_active_svobs': True, + # Generate property aggregations by containedInPlaces such as + # country, continent + 'aggregate_by_contained_in_place': True, + # Disable parent place lookups for place dcids added to the event. + # When disabled, parent places could be looked up using the + # place_property_cache. + 'lookup_contained_for_place': False, + # Cache file with properties for places. + # It is a pickle file with a dictionary of the form: + # { + # '' : { + # '': '' + # ... + # }, + # ... + # } + # For example: + # { + # 'containedInPlace' : { + # 'geoId/06': ['Earth', 'northamerica', 'country/USA', 'usc/PacificDivision' ] + # } + # 'latitude': { + # 'geoId/06': 37.148 + # }, + # 'longitude': { + # 'geoId/06': -119.540 + # } + # } + 'place_property_cache_file': '', + + ### Output settings. + + # CSV delimiter for outputs + 'output_delimiter': ',', + + # Settings for event boundary polygons. + # Add event boundary polygon covering all event affectedPlaces + # as value for the property: geoJsonCoordinatesDP1 + # To skip generating event polygons, set it to None. 'output_affected_place_polygon': 'geoJsonCoordinatesDP1', + # Simplify the output polygons to 0.1 degrees. + # To disable simplification, set it to None. + 'polygon_simplification_factor': 0.1, + + # Output svobs CSV per place + 'output_place_svobs': True, + + # List of properties for SVObs + 'output_place_svobs_properties': ['area', 'count'], + # Date formats to whcih SVObs are aggregated + 'output_place_svobs_format': ['YYYY-MM-DD', 'YYYY-MM'], + + # Enable/Disable events SVObs with eventId as observationAbout + # Disable until it is used in the UI + 'output_svobs': False, + 'output_active_svobs': False, } diff --git a/scripts/earthengine/events_pipeline.py b/scripts/earthengine/events_pipeline.py new file mode 100644 index 0000000000..b3ddaa20f2 --- /dev/null +++ b/scripts/earthengine/events_pipeline.py @@ -0,0 +1,235 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the 'License'); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an 'AS IS' BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Script to generate events from source data. +The pipeline to generate events can have the following supported stages: + 1. earthengine: Extract an image from Google EarthEngine as a geoTif + on Google Cloud Storage (GCS) + 2. download: Download data from source, incrementally with + any source specific processing and rate limits + 3. bq_export: Export a BigQuery table using an SQL query into a CSV + on Google Cloud Storage (GCS) + 3. raster_csv: Process source data downloaded from one of the above steps + into CSV with S2 cells. + 4. events: Generate events and related stats from the csv data. + +The stages are run sequentially in the order listed in the config, +with each stage run with the configs for that stage. +The output files generated by one stage is passed on to the next as inputs. +In case of an error in a stage, the stage runner is expected to terminate +the script. + +The whole pipeline can be restarted to regenerate the data either on failure or +to refresh with new data from source. +Some stages, such as 'download' can resume from past runs and incrementally +process new data. Some stages, like 'events', process all files in an +input folder when re-run. + +To use it, create a config file with a python dictionary with all the settings +for the stages to be run in sequence. + +The config value can have references to other settings with python format +syntax, '{}'. The values are resolved when that setting is used. + + { + 'defaults': { + # Default settings for all stages. + 'gcs_bucket': 'my-bucket', + 'gcs_folder': 'my-import-name', + }, + # Stage sepcific settings + 'stages': [ + { + 'stage': 'download', + 'output_dir': 'gs://{gcs_bucket}/{gcs_folder}/{stage}/{year}', + 'url': 'http://my-data-source/', + }, + { + 'stage': 'raster_csv', + 'input_files': 'gs://{gcs_bucket}/{gcs_folder}/download/{year}/*.csv', + 'output_dir': 'gs://{gcs_bucket}/{gcs_folder}/{stage}/{year}', + ... + }, + { + 'stage': 'events', + 'input_files': 'gs://{gcs_bucket}/{gcs_folder}/raster_csv/{year}/*.csv', + 'output_dir': 'gs://{gcs_bucket}/{gcs_folder}/{stage}/{year}', + ... + }, + ], + } + + See events_pipeline_config.py for list of settings for each stage. + test_data/sample_fires_event_pipeline_config.py has an example for FireEvent. + +Run all stages in the pipeline as: + python3 events_pipeline.py --pipeline_config= + +To run a sequence of specific stages, use: + python3 events_pipeline.py --pipeline_config= \ + --run_stages=[,] + The config for the stage is assumed to have the input files. +""" + +import os +import re +import sys +import time + +from absl import app +from absl import flags +from absl import logging + +flags.DEFINE_string('pipeline_config', '', + 'Config for the pipeline as a py dictionary of json') +flags.DEFINE_string( + 'pipeline_state', '', + 'File with state for the pipeline processing as a python dictionary.' + 'Used to resume processing for new incremental data.') +flags.DEFINE_list('run_stages', [], + 'List of stages to run. If empty, all stages are run.') + +_FLAGS = flags.FLAGS + +_SCRIPTS_DIR = os.path.dirname(__file__) +sys.path.append(_SCRIPTS_DIR) +sys.path.append(os.path.dirname(_SCRIPTS_DIR)) +sys.path.append(os.path.dirname(os.path.dirname(_SCRIPTS_DIR))) +sys.path.append( + os.path.join(os.path.dirname(os.path.dirname(_SCRIPTS_DIR)), 'util')) + +import common_flags +import file_util +import pipeline_stage_bigquery +import pipeline_stage_download +import pipeline_stage_earthengine +import pipeline_stage_events +import pipeline_stage_raster_csv +import pipeline_stage_runner +import process_events +import raster_to_csv +import utils + +from counters import Counters +from config_map import ConfigMap +from pipeline_stage_runner import StageRunner + +# Processing state persisted to a file +# Includes dynamic parameter values for each stage of processing. +_PROCESS_STATE = { + # Last date for which input was processed in YYYY-MM-DD format + 'last_input_date': '', +} + + +class EventPipeline(StageRunner): + '''Class to generate events from source data. + Runs a series of pipelines as per the config. + ''' + + def __init__(self, config: ConfigMap, counters: Counters = None): + self._config = config + if not config: + self._config = ConfigMap() + self._pipeline_state = {} + self.load_pipeline_state() + config_dicts = [self._config.get('defaults', {})] + config_dicts.append(self._config.get_configs()) + self.set_up('event_pipeline', config_dicts, self._pipeline_state, + counters) + self.setup_stages() + + def __del__(self): + # Save the pipeline state into the file. + if self._pipeline_state: + pipeline_state_file = self.get_config('pipeline_state_file', '') + if pipeline_state_file: + return file_util.file_write_py_dict(self._pipeline_state, + pipeline_state_file) + + def load_pipeline_state(self) -> dict: + pipeline_state_file = self._config.get('pipeline_state_file', '') + if pipeline_state_file: + self._pipeline_state = file_util.file_load_py_dict( + pipeline_state_file) + logging.info( + f'Loaded pipeline state: {self._pipeline_state} from {pipeline_state_file}' + ) + return self._pipeline_state + + def set_pipeline_state(self, key: str, value: str): + '''Sets the value of the pipeline state.''' + self._pipeline_state[key] = value + + def setup_stages(self): + '''Create the runners for each stage of the pipeline.''' + self.stage_runners = [] + stage_names = [] + default_config = self._config.get('defaults', {}) + if not default_config: + default_config = dict(self._config.get_configs()) + if 'stages' in default_config: + default_config.remove('stages') + for stage_config in self._config.get('stages', []): + stage = stage_config.get('stage', '') + runner = pipeline_stage_runner.get_stage_runner(stage) + configs = [default_config, stage_config] + self.stage_runners.append( + runner(configs, self._pipeline_state, self.counters)) + stage_names.append(stage) + logging.info( + f'Created pipeline with {len(self.stage_runners)} stages: {stage_names}' + ) + + def run_stage(self, stage_name: str, input_files: list = []) -> list: + '''Run a single stage and return the output files generated.''' + for stage_runner in self.stage_runners: + if stage_name == stage_runner.get_name(): + return stage_runner.run_stage(input_files) + return [] + + def run(self, run_stages: list = []) -> list: + '''Run all the stages in the pipeline.''' + stage_count = 0 + output_files = [] + for stage_runner in self.stage_runners: + stage_count += 1 + stage_name = stage_runner.get_name() + if not run_stages or stage_name in run_stages: + self.counters.set_prefix(f'S{stage_count}:{stage_name}:') + output_files = stage_runner.run_stage(output_files) + else: + output_files = [] + + if output_files: + # Update the process state + self.set_pipeline_state('last_input_date', utils.date_yesterday()) + return output_files + + +pipeline_stage_runner.register_stage_runner('event_pipeline', EventPipeline) + + +def main(_): + config_dict = file_util.file_load_py_dict(_FLAGS.pipeline_config) + if _FLAGS.pipeline_state: + config_dict['pipeline_state_file'] = _FLAGS.pipeline_state + config = ConfigMap(config_dict=config_dict) + if _FLAGS.debug or config.get('debug', False): + config.set_config('debug', True) + pipeline = EventPipeline(config=config) + pipeline.run(run_stages=_FLAGS.run_stages) + + +if __name__ == '__main__': + app.run(main) diff --git a/scripts/earthengine/events_pipeline_config.py b/scripts/earthengine/events_pipeline_config.py new file mode 100644 index 0000000000..57104478a9 --- /dev/null +++ b/scripts/earthengine/events_pipeline_config.py @@ -0,0 +1,399 @@ +# Default configuration settings for events_pipeline.py. +# Includes static settings for each stage of processing. +{ + # Defaults applied to configs of all stages + 'defaults': { + # Change to import specific name + 'import_name': 'SampleImport', + + # Date from which to process files. + 'start_date': '', + 'time_period': 'P1M', + + # GCS folder settings for output files + # outputs will be in: gs:////* + 'gcs_project': '', + 'gcs_bucket': 'datcom-prod-imports', + 'gcs_folder': '{import_name}', + }, + + # Sequence of stages with configs. + 'stages': [ + # stage config for EarthEngineRunner + # Settings to fetch geotiff from earth engine + # See earthentine_image.py:EE_DEFAULT_CONFIG for config parameters + { + 'stage': 'earthengine', + + # Date from which to process files. + # Images are generated from start_date until now + # with one image for each time period, say month. + 'start_date': '', + 'time_period': 'P1M', + + # Image settings + # Use the pre-configured data set in + # earthengine_image.py:_DEFAULT_DATASETS + # For example, use the image collection: 'DynamicWorld' + 'ee_dataset': 'dynamic-world', + # Band in the image collection to extract as output. + # Should be one of the bands in the image collection chosen above. + 'band': 'water', + + # reducer to aggregate band value for each point across images + # in the image collection into a single value in the output image. + 'ee_reducer': 'max', + + # Filter by band value to generate output with points having + # interesting values. + 'band_min': 0.7, + # Apply a mask to include values for places where mask is set to 1 + 'ee_mask': 'land', + + # Output settings + # Output pixel resolution in meters. + # Generates a value in the output for a region of 1000x1000m. + 'scale': 1000, + # Export geoTif to 'gs://{gcs_bucket}/gcs_folder}/ee_image*.tif' + 'gcs_folder': '{import_name}/{stage}/{year}', + + # Wait for EE tasks to complete + 'ee_wait_task': True, + + # Generate new images only since last run. + # Skip image generation for existing outputs generated previously. + 'skip_existing_output': True, + }, + + # stage config for DownloadRunner + # Settings to download source data from a list of URLs. + { + 'stage': + 'download', + + # List of URLs to download + 'url': [], + + # URL parameters for GET or POST requests + 'url_params': {}, + 'http_method': + 'GET', + + # Regular expression pattern to check in the URL response. + # Requests with responses not matching the regex are considered + # unsuccessful and will be retried. + # For example, look for a date column in the response CSV. + 'successful_response_regex': + ',[0-9]{4}-[0-9]{2}-[0-9]{2},', + + # Dates to download files + # URL is downloaded for dates from start_date to now + # with a request made for each time_period. + 'start_date': + '', + 'time_period': + 'P1D', + + # Retry settings. + # Timeout in seconds for HTTP requests. + 'timeout': + 60, + # Number of times to retry the HTTP request + 'retry_count': + 10, + # Interval in seconds between retries for HTTP requests + 'retry_interval': + 60, + + # Output file name for file downloaded from the URL. + # In case multiple requests are made for different dates, + # add the date to the file name. + 'output_file': + 'gs://{gcs_bucket}/{gcs_folder}/{stage_name}/{year}/{import_name}-{stage_name}-{start_date}-{time_period}.csv', + + # Skip download if the output file exists. + 'skip_existing_output': + True, + }, + + # stage config for RasterCSVRunner + # Settings to convert source input data to csv + # See raster_to_csv.py:_DEFAULT_CONFIG for config settings + { + 'stage': 'raster_csv', + + # Input: process output from previous stage + 'input_files': '', + 'gs://{gcs_bucket}/{gcs_folder}/download/{year}/*.csv,gs://{gcs_bucket}/{gcs_folder}/earthengine/{year}/*.tif' + + # Processing parameters + # Rename columns from input to output. + # rename columns : + # to the expected columns for processing: date, latitude, longitude + 'rename_columns': { + # Rename columns in CSV + 'acq_date': 'date', + 'lat': 'latitude', + 'lng': 'longitude', + + # Rename bands in geoTif + 'band:0': 'water', + }, + # Add an S2 cell of the given level for each input point. + # For GeoTif inputs, use the lat/lng of each data value, + # for CSV inputs, use the columns 'latitude' and 'longitude'. + # Generate data points for leve 10 S2 cells (10x10km) + 's2_level': 10, + + # Default aggregation for data values mapped to the same s2_cell+date + # that can be one of: min, max, mean, sum. + # For columns specific aggregation methods, + # use the config:'input_data_filter'. + 'aggregate': 'sum', + # Default area for input CSVs. + # For raster inputs, the cell area is computed from the input. + # Use one the area or width/height options. + # Default input point area in sqkm if constant for the whole data set. + 'default_cell_area': 0, + # Default point/cell width/height in degrees + # Use ~1sqkm at equator, lower near poles. + 'default_cell_width': 0.009, + 'default_cell_height': 0.009, + + # filter settings per column for data + # input (pre-aggregation) and output (post-aggregation) of the form: + # { + # '' : { + # 'min': , # Minimum value for + # 'max': , # Maximum value for + # 'aggregate': 'sum', # one of 'min','max','sum','mean' + # }, + # ... + # } + 'input_data_filter': { + # Add up area for points added to an s2cell. + 'area': { + 'aggregate': 'sum', + }, + # Pick rows with confidence column set to 'n' or 'h'. + # 'confidence': { + # 'regex': r'[nh]', # pick normal or high + # } + # 'water': { # band:0 + # 'min': 1.0 + # }, + }, + 'output_data_filter': { + # 'area': { + # 'min': 1.0, # Minimum area in sqkm after aggregation + # }, + }, + + # Output settings + # Generate an output file in the folder for each input file + 'output_dir': 'gs://{gcs_bucket}/{gcs_folder}/{stage_name}/{year}', + # Skip re-processing of existing output files. + 'skip_existing_output': True, + }, + + # stage config for EventsRunner + # Settings to process data into events + # See event_config.py for config settings. + { + 'stage': + 'events', + + # EventType used for StatVars and tMCFs + 'event_type': + 'FloodEvent', + + # Input: use CSV generated from raster_csv + # re-generating events for the current year. + 'input_files': + 'gs://{gcs_bucket}/{gcs_folder}/raster_csv/{year}/*.csv', + + # Output file name prefix for events, svobs CSV and tMCF + 'output_dir': + 'gs://{gcs_bucket}/{gcs_folder}/{stage}/{year}/{import_name}_', + + ### Input settings. + + # Map to rename input columns to output columns with entries as: + # '': '' + # Rest of the configs below refer to the renamed columns. + # Only output columns starting with lower case are added to tmcf. + 'input_rename_columns': { + 'date': 'observationDate', + }, + + # Columms of input_csv (after renaming) that are added as event properties + 'input_columns': ['area'], + + # Input CSV column (after renaming) that contain the place, + # such as, s2 cell id generated by raster_csv + 'place_column': + 's2CellId', + + # Input CSV column (after renaming) for date. + 'date_column': + 'observationDate', + + ### Processing settings + + # Maximum distance between places that are merged into the same event. + 'max_overlap_distance_km': + 10, + + # S2 level to which data is aggregated. + # In case input place is an S2 cell of higher level, it is aggregated into + # a parent S2 cell of this level. + 's2_level': + 10, # Events at level-10 S2 cells, roughly 10x10km. + + # Event property settings. + # Default aggregation for all event properties + 'aggregate': + 'sum', + # Per property filter params for input data. + 'input_filter_config': { + # '' : { + # 'min': , + # 'max': , + # 'regex': '', + # }, + # For example: 'area': { 'min': 1 }, + }, + # Per property filter params for output events + # Applied when output_events is True + # Event is dropped if any property fails the filter. + 'output_events_filter_config': { + # '' : { + # 'min': , + # 'max': , + # 'regex': '', + # }, + # For example: to generate events with area of atleast 10sqkm, + # 'area' { 'min': 10 } + }, + # Per property aggregation settings for an event across places and dates. + # For different per-date and per-place aggregations, use the settings + # 'property_config_per_date' and 'property_config_across_dates'. + 'property_config': { + 'aggregate': 'max', + 'area': { + 'aggregate': 'sum', + 'unit': 'SquareKilometer', + }, + 'affectedPlace': { + 'aggregate': 'list', + }, + }, + # Per property aggregation settings for a date across multiple places. + # Falls back to 'property_config' if not set. + 'property_config_per_date': { + # Default aggregation for all properties: pick max value across places. + 'aggregate': 'max', + 'area': { + 'aggregate': 'sum', + 'unit': 'SquareKilometer', + }, + 'affectedPlace': { + 'aggregate': 'list', + }, + }, + # Per property aggregation settings across multiple dates. + # Falls back to 'property_config' if not set. + 'property_config_across_dates': { + # Default aggregation for all properties: pick max value across dates. + 'aggregate': 'max', + 'area': { + 'aggregate': 'max', + 'unit': 'SquareKilometer', + }, + 'affectedPlace': { + 'aggregate': 'list', + }, + }, + # Threshold for dates and places added to an event + # Treat incidents at the same location more than 90 days apart as separate events. + 'max_event_interval_days': + 90, + # Treat incidents after 90 days from start as a seperate event. + 'max_event_duration_days': + 90, + # Treat incidents at more than 10000 places into seperate events. + 'max_event_places': + 10000, + + # Generate property aggregations by containedInPlaces such as + # country, continent + 'aggregate_by_contained_in_place': + True, + # Disable parent place lookups for place dcids added to the event. + # When disabled, parent places could be looked up using the + # place_property_cache. + 'lookup_contained_for_place': + False, + # Cache file with properties for places including + # 'name', 'containedInPlace', 'latitude' and 'longitude'. + # It is a pickle file with a dictionary of the form: + # { + # '' : { + # '': '' + # ... + # }, + # ... + # } + # For example: + # { + # 'containedInPlace' : { + # 'geoId/06': ['Earth', 'northamerica', 'country/USA', 'usc/PacificDivision' ] + # } + # 'latitude': { + # 'geoId/06': 37.148 + # }, + # 'longitude': { + # 'geoId/06': -119.540 + # } + # } + 'place_property_cache_file': + 'gs://datcom-prod-imports/place_cache/place_properties_cache_with_s2_10.pkl', + + ### Output settings. + + # CSV delimiter for outputs + 'output_delimiter': + ',', + + # Settings for event boundary polygons. + # Add event boundary polygon covering all event affectedPlaces + # as value for the property: geoJsonCoordinatesDP1 + # To skip generating event polygons, set it to None. + 'output_affected_place_polygon': + 'geoJsonCoordinatesDP1', + # Simplify the output polygons to 0.1 degrees. + # To disable simplification, set it to None. + 'polygon_simplification_factor': + 0.1, + + # Output svobs CSV per place + 'output_place_svobs': + True, + + # List of properties for SVObs + 'output_place_svobs_properties': ['area', 'count'], + # Date formats to whcih SVObs are aggregated + 'output_place_svobs_format': ['YYYY-MM-DD', 'YYYY-MM'], + + # Enable/Disable events SVObs with eventId as observationAbout + # Disable until it is used in the UI + 'output_svobs': + False, + 'output_active_svobs': + False, + }, + ], + + # File with the state from the last pipeline run + 'pipeline_state_file': '' +} diff --git a/scripts/earthengine/events_pipeline_test.py b/scripts/earthengine/events_pipeline_test.py new file mode 100644 index 0000000000..0c32bd4065 --- /dev/null +++ b/scripts/earthengine/events_pipeline_test.py @@ -0,0 +1,156 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Test for events_pipeline.py""" + +import os +import pandas as pd +import shutil +import sys +import tempfile +import unittest + +from absl import logging + +# Allows the following module imports to work when running as a script +_MODULE_DIR = os.path.dirname(__file__) +sys.path.append(_MODULE_DIR) +sys.path.append(os.path.dirname(_MODULE_DIR)) +sys.path.append(os.path.dirname(os.path.dirname((_MODULE_DIR)))) +sys.path.append( + os.path.join(os.path.dirname(os.path.dirname((_MODULE_DIR))), 'util')) + +import file_util +import utils +import download_util + +from events_pipeline import EventPipeline +from config_map import ConfigMap + +_TESTDIR = os.path.join(os.path.dirname(os.path.realpath(__file__)), + 'test_data') + + +class EventsPipelineTest(unittest.TestCase): + + def compare_files(self, expected: str, actual: str): + '''Compare lines in files after sorting.''' + logging.info(f'Comparing files: expected:{expected}, actual: {actual}') + file, ext = os.path.splitext(expected) + if ext == '.csv': + self.compare_csv_files(expected, actual) + with file_util.FileIO(expected, 'r') as exp: + with file_util.FileIO(actual, 'r') as act: + exp_lines = sorted(exp.readlines()) + act_lines = sorted(act.readlines()) + self.assertEqual(exp_lines, act_lines) + + def compare_csv_files(self, + expected_file: str, + actual_file: str, + ignore_columns: list = []): + '''Compare CSV files with statvar obsevration data.''' + # Sort files by columns. + df_expected = pd.read_csv(expected_file) + df_actual = pd.read_csv(actual_file) + self.assertEqual( + df_expected.columns.to_list(), df_actual.columns.to_list(), + f'Found different columns in CSV files:' + + f'expected:{expected_file}:{df_expected.columns.to_list()}, ' + + f'actual:{actual_file}:{df_actual.columns.to_list()}, ') + if ignore_columns: + df_expected.drop( + columns=df_expected.columns.difference(ignore_columns), + inplace=True) + df_actual.drop(columns=df_actual.columns.difference(ignore_columns), + inplace=True) + df_expected.sort_values(by=df_expected.columns.to_list(), + inplace=True, + ignore_index=True) + df_actual.sort_values(by=df_expected.columns.to_list(), + inplace=True, + ignore_index=True) + self.assertTrue( + df_expected.equals(df_actual), f'Found diffs in CSV rows:' + + f'"{actual_file}" vs "{expected_file}":') + + def setUp(self): + self.maxDiff = None + self._config = ConfigMap(filename=os.path.join( + _TESTDIR, 'sample_fires_event_pipeline_config.py')) + + # Setup download URL response to the test input. + self.test_input_file = os.path.join(_TESTDIR, 'sample_fires_input.csv') + self.test_url = 'http://sample_test.com/data/2023' + with open(self.test_input_file, mode='r') as test_input: + download_util._PREFILLED_RESPONSE[self.test_url] = test_input.read() + + # Set temp dir in the config + self._tmp_dir = tempfile.gettempdir() + if not self._config.get('defaults', {}).get('tmp_dir'): + self._tmp_dir = tempfile.mkdtemp() + self._config.get_configs()['defaults']['tmp_dir'] = self._tmp_dir + + # Set place property cache file. + self._config.get_configs( + )['defaults']['place_property_cache_file'] = os.path.join( + _TESTDIR, 'test_s2_cells_properties.pkl') + + self._config.set_config( + 'pipeline_state_file', + os.path.join(self._tmp_dir, 'test_pipeline_state.py')) + + # Create an events pipeline for the config. + self.events_pipeline = EventPipeline(config=self._config) + + def tearDown(self): + # Delete the tmp directory + if self._tmp_dir and self._tmp_dir != tempfile.gettempdir(): + logging.info(f'Deleting tmp dir: {self._tmp_dir}') + shutil.rmtree(self._tmp_dir) + + def test_pipeline_stage_download(self): + # Run the download stage of the event pipeline. + output_files = self.events_pipeline.run_stage('download') + self.assertEqual(1, len(output_files)) + self.compare_files(self.test_input_file, output_files[0]) + + # Running download again should not return any output + output_files = self.events_pipeline.run_stage('download') + self.assertEqual(0, len(output_files)) + + def test_events_pipeline_run(self): + # Run all stages in the events pipeline. + output_files = self.events_pipeline.run() + + # Check outputs + logging.info(f'Comparing file: {output_files}') + self.assertEqual(5, len(output_files)) + self.compare_files( + os.path.join(_TESTDIR, 'sample_fires_events.csv'), + _get_matching_in_list(output_files, 'sample_fires_events.csv')) + + for file in ['place_svobs', 'svobs']: + for ext in ['.csv', '.tmcf']: + filename = f'sample_fires_{file}{ext}' + output_file = _get_matching_in_list(output_files, filename) + expected_output = os.path.join(_TESTDIR, filename) + self.compare_files(expected_output, output_file) + + +def _get_matching_in_list(items: list, pat: str) -> str: + '''Returns the element matching the pat in the items list.''' + for item in items: + if pat in item: + return item + return '' diff --git a/scripts/earthengine/flood-places.tmcf b/scripts/earthengine/flood-places.tmcf deleted file mode 100644 index 222a6be9a5..0000000000 --- a/scripts/earthengine/flood-places.tmcf +++ /dev/null @@ -1,5 +0,0 @@ -Node: E:Place->E0 -dcid: C:Place->s2CellId -typeOf: C:Place->typeOf -containedInPlace: C:Place->containedInPlace -name: C:Place->name diff --git a/scripts/earthengine/flood-statvar.mcf b/scripts/earthengine/flood-statvar.mcf deleted file mode 100644 index e6c0482b91..0000000000 --- a/scripts/earthengine/flood-statvar.mcf +++ /dev/null @@ -1,6 +0,0 @@ -Node: dcid:Area_FloodEvent -typeOf: dcs:StatisticalVariable -populationType: dcs:FloodEvent -measuredProperty: dcs:area -statType: dcs:measuredValue - diff --git a/scripts/earthengine/pipeline_stage_bigquery.py b/scripts/earthengine/pipeline_stage_bigquery.py new file mode 100644 index 0000000000..afdf1c25ec --- /dev/null +++ b/scripts/earthengine/pipeline_stage_bigquery.py @@ -0,0 +1,123 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the 'License'); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an 'AS IS' BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Class to run the events pipeline stage to export data from BigQuery. +""" + +import os +import sys + +from absl import logging +from google.cloud import bigquery + +_SCRIPTS_DIR = os.path.dirname(__file__) +sys.path.append(_SCRIPTS_DIR) +sys.path.append(os.path.dirname(_SCRIPTS_DIR)) +sys.path.append(os.path.dirname(os.path.dirname(_SCRIPTS_DIR))) +sys.path.append( + os.path.join(os.path.dirname(os.path.dirname(_SCRIPTS_DIR)), 'util')) + +from counters import Counters +from pipeline_stage_runner import StageRunner, register_stage_runner + + +class BigQueryExportRunner(StageRunner): + '''Class to download data from BigQuery tables using SQL. + Data is exported on GCS as csv. + ''' + + # SQL statement template to export query output to GCS. + _EXPORT_SQL_QUERY = ''' + EXPORT DATA + OPTIONS ( + uri = '{output}', + format = 'CSV', + overwrite = true, + header = true, + field_delimiter = ',') + AS ( + {query} + )''' + + def __init__(self, + config_dicts: list = [], + state: dict = {}, + counters=None): + self.set_up('bq_export', config_dicts, state, counters) + + def run(self, + input_files: list = None, + config_dict: dict = {}, + counters: Counters = None) -> list: + '''Returns the list of csv files exported from BigQuery.''' + # Get the query + query = self.get_bq_query(config_dict) + if not query: + logging.error( + f'No SQL query set for BigQueryExportRunner in {self.config.get_configs()}.' + ) + return [] + + # Setup query to export to output files as csv. + project_id = self.get_config('gcs_project', None, config_dict) + os.environ["GOOGLE_CLOUD_PROJECT"] = project_id + bq_client = bigquery.Client(project=project_id) + output = self.get_output_filename(config_dict=config_dict, + file_ext='-*.csv') + if not query.lower().startswith('export'): + query = self._EXPORT_SQL_QUERY.format(query=query, output=output) + else: + query_output = self.get_query_export_uri(query) + if query_output: + output = query_output + else: + logging.fatal(f'No export uri in BQ query: {query}') + + # Run the BQ query. + logging.info(f'Running query: {query}') + result = bq_client.query(query) + while (result.state == 'RUNNING'): + time.sleep(1) + logging.info( + f'Got response: {result}, state: {result.state}, errors: {result.errors} for query: {query}' + ) + if result.errors: + logging.fatal( + f'Failed to run query:{query}, Error: {result.errors}') + return [] + + # Get the output files. + output_files = file_util.file_get_matching(output) + logging.info(f'Got output: "{output_files}" for query: {query}') + return output_files + + def get_bq_query(self, config_dict: dict = {}) -> str: + '''Returns the query to select data to export.''' + query = self.get_config('bq_query', '', config_dict).strip() + if not query: + # No query in config. Export the whole table is specified. + table = config_dict.get('bq_table') + if table: + query = f'SELECT * from {table}' + return query + + def get_query_export_uri(self, query: str) -> str: + '''Returns the output URI from the export query.''' + _EXPORT_OUTPUT_REGEX = r'url *= *[\'"](?P[^\'"]*)[\'"]' + matche = re.search(_EXPORT_OUTPUT_REGEX, query) + if match: + return match.groupdict().get('output', '') + + +# Register the EventsRunner +register_stage_runner('bigquery', BigQueryExportRunner) diff --git a/scripts/earthengine/pipeline_stage_download.py b/scripts/earthengine/pipeline_stage_download.py new file mode 100644 index 0000000000..68b4e35f29 --- /dev/null +++ b/scripts/earthengine/pipeline_stage_download.py @@ -0,0 +1,135 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the 'License'); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an 'AS IS' BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Class to run the events pipeline stage to download files from a URL. +""" + +import os +import sys + +from absl import logging + +_SCRIPTS_DIR = os.path.dirname(__file__) +sys.path.append(_SCRIPTS_DIR) +sys.path.append(os.path.dirname(_SCRIPTS_DIR)) +sys.path.append(os.path.dirname(os.path.dirname(_SCRIPTS_DIR))) +sys.path.append( + os.path.join(os.path.dirname(os.path.dirname(_SCRIPTS_DIR)), 'util')) + +import file_util +import utils + +from counters import Counters +from download_util import request_url +from pipeline_stage_runner import StageRunner, register_stage_runner + + +class DownloadRunner(StageRunner): + '''Class to download data files from URL source.''' + + def __init__(self, + config_dicts: list = [], + state: dict = {}, + counters=None): + self.set_up('download', config_dicts, state, counters) + + def run(self, + input_files: list = None, + config_dict: dict = {}, + counters: Counters = None) -> list: + '''Returns the list of files downloaded from the URL in the config. + URLs are downloaded for each time period until the current date.''' + # Download data from start_date up to end_date + # advancing date by the time_period. + start_date = self.get_config('start_date', '', config_dict) + end_date = self.get_config('end_date', '', config_dict) + if not end_date: + end_date = utils.date_yesterday() + data_files = [] + while start_date and start_date <= end_date: + # Download data for the start_date + download_files = self.download_file_with_config(self.get_configs()) + if download_files: + data_files.extend(download_files) + + # Advance start_date to the next date. + start_date = utils.date_advance_by_period( + start_date, self.get_config('time_period', 'P1M', config_dict)) + if start_date: + self.set_config_dates(start_date=start_date) + return data_files + + def download_file_with_config(self, config_dict: dict = {}) -> list: + '''Returns list of files downloaded for config.''' + logging.info(f'Downloading data for config: {config_dict}') + downloaded_files = [] + urls = config_dict.get('url', []) + if not isinstance(urls, list): + urls = [urls] + for url in urls: + if not url: + continue + url_params = config_dict.get('url_params', {}) + filename = self.get_output_filename(config_dict=config_dict) + if self.should_skip_existing_output(filename): + logging.info(f'Skipping download for existing file: {filename}') + continue + + # Download the URL with retries. + download_content = '' + retry_count = 0 + retries = config_dict.get('retry_count', 5) + retry_secs = config_dict.get('retry_interval', 5) + while not download_content and retry_count < retries: + download_content = request_url( + url, + params=url_params, + method=config_dict.get('http_method', 'GET'), + output=config_dict.get('response_type', 'text'), + timeout=config_dict.get('timeout', 60), + retries=config_dict.get('retry_count', 3), + retry_secs=retry_secs) + if download_content: + # Check if the downloaded content matches the regex. + regex = config_dict.get('successful_response_regex', '') + if regex: + match = re.search(regex, download_content) + if not match: + download_content = '' + retry_count += 1 + logging.info( + f'Downloaded content for {url} does not match {regex}' + ) + if retry_count < retries: + logging.info( + f'retrying {url} #{retry_count} after {retry_secs}' + ) + time.sleep(retry_secs) + if not download_content: + logging.error( + f'Failed to download {url} after {retries} retries') + return None + + # Save downloaded content to file. + with file_util.FileIO(filename, mode='w') as file: + file.write(download_content) + logging.info( + f'Downloaded {len(download_content)} bytes from {url} into file: {filename}' + ) + downloaded_files.append(filename) + + return downloaded_files + + +# Register the DownloadRunner +register_stage_runner('download', DownloadRunner) diff --git a/scripts/earthengine/pipeline_stage_earthengine.py b/scripts/earthengine/pipeline_stage_earthengine.py new file mode 100644 index 0000000000..9844bbc436 --- /dev/null +++ b/scripts/earthengine/pipeline_stage_earthengine.py @@ -0,0 +1,71 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the 'License'); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an 'AS IS' BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Class to run the events pipeline stage to extract images form Earth Engine. +""" + +import os +import sys + +from absl import logging + +_SCRIPTS_DIR = os.path.dirname(__file__) +sys.path.append(_SCRIPTS_DIR) +sys.path.append(os.path.dirname(_SCRIPTS_DIR)) +sys.path.append(os.path.dirname(os.path.dirname(_SCRIPTS_DIR))) +sys.path.append( + os.path.join(os.path.dirname(os.path.dirname(_SCRIPTS_DIR)), 'util')) + +import earthengine_image + +from counters import Counters +from pipeline_stage_runner import StageRunner, register_stage_runner + + +class EarthEngineRunner(StageRunner): + '''Class to generate geoTif images from earth engine.''' + + def __init__(self, + config_dicts: list = [], + state: dict = {}, + counters=None): + configs = [earthengine_image.EE_DEFAULT_CONFIG] + configs.extend(config_dicts) + self.set_up('earthengine', configs, state, counters) + + def run(self, + input_files: list = None, + config_dict: dict = {}, + counters: Counters = None) -> list: + '''Returns the list of geoTif images extracted from earth engine. + If the stage's config:ee_wait_task is False, + returns the list of earth engine tasks launched. + ''' + logging.info(f'Processing earth engine config: {config_dict}') + # Generate ee images + ee_tasks = earthengine_image.ee_process(config_dict) + if not ee_tasks: + logging.info( + f'No tasks or images returned for config:{config_dict}') + return None + # Return the list of output files. + image_files = [] + for status in ee_tasks: + output_file = status.get('output_file', '') + if output_file: + image_files.append(output_file) + return image_files + + +# Register the EarthEngineRunner +register_stage_runner('earthengine', EarthEngineRunner) diff --git a/scripts/earthengine/pipeline_stage_events.py b/scripts/earthengine/pipeline_stage_events.py new file mode 100644 index 0000000000..4b28162726 --- /dev/null +++ b/scripts/earthengine/pipeline_stage_events.py @@ -0,0 +1,60 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the 'License'); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an 'AS IS' BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Class to run the events pipeline stage to generate events from CSV. +""" + +import os +import sys + +from absl import logging + +_SCRIPTS_DIR = os.path.dirname(__file__) +sys.path.append(_SCRIPTS_DIR) +sys.path.append(os.path.dirname(_SCRIPTS_DIR)) +sys.path.append(os.path.dirname(os.path.dirname(_SCRIPTS_DIR))) +sys.path.append( + os.path.join(os.path.dirname(os.path.dirname(_SCRIPTS_DIR)), 'util')) + +import process_events + +from config_map import ConfigMap +from counters import Counters +from pipeline_stage_runner import StageRunner, register_stage_runner + + +class EventsRunner(StageRunner): + '''Class to generate Events and StatvarObservations using GeoEventsProcessor.''' + + def __init__(self, + config_dicts: list = [], + state: dict = {}, + counters=None): + configs = [process_events.get_default_config()] + configs.extend(config_dicts) + self.set_up('events', configs, state, counters) + + def run(self, + input_files: list = None, + config_dict: dict = {}, + counters: Counters = None) -> list: + '''Process data for places into events.''' + config = ConfigMap(config_dict=config_dict) + output_path = self.get_output_dir(config_dict) + return process_events.process(csv_files=input_files, + output_path=output_path, + config=config) + + +# Register the EventsRunner +register_stage_runner('events', EventsRunner) diff --git a/scripts/earthengine/pipeline_stage_raster_csv.py b/scripts/earthengine/pipeline_stage_raster_csv.py new file mode 100644 index 0000000000..76dc1b89ca --- /dev/null +++ b/scripts/earthengine/pipeline_stage_raster_csv.py @@ -0,0 +1,91 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the 'License'); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an 'AS IS' BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Class to run the events pipeline stage to generate CSVs +with place typs supported by DataCOmmons, such as S2Cells +from inputs such as geoTif or CSVs downloaded form external sources with lat/lng. +""" + +import os +import sys + +from absl import logging + +_SCRIPTS_DIR = os.path.dirname(__file__) +sys.path.append(_SCRIPTS_DIR) +sys.path.append(os.path.dirname(_SCRIPTS_DIR)) +sys.path.append(os.path.dirname(os.path.dirname(_SCRIPTS_DIR))) +sys.path.append( + os.path.join(os.path.dirname(os.path.dirname(_SCRIPTS_DIR)), 'util')) + +import earthengine_image +import file_util +import raster_to_csv + +from config_map import ConfigMap +from counters import Counters +from pipeline_stage_runner import StageRunner, register_stage_runner + + +class RasterCSVRunner(StageRunner): + '''Class to generate CSV per input geoTif or CSV with lat/long.''' + + def __init__(self, + config_dicts: list = [], + state: dict = {}, + counters=None): + self.set_up('raster_csv', config_dicts, state, counters) + + def run(self, + input_files: list = None, + config_dict: dict = {}, + counters: Counters = None) -> list: + '''Returns the csv files with data per geo point generated + from the input files. + The input geoTif files are converted to data per-s2 cell grid. + Input csvs with lat,longs are also converted to data per grid point. + ''' + output_files = [] + + for filename in file_util.file_get_matching(input_files): + output_filename = self.get_output_filename(input_filename=filename) + if self.should_skip_existing_output(output_filename): + logging.info( + f'Skip processing {filename} for existing file: {output_filename}' + ) + continue + filebase, ext = os.path.splitext(filename) + input_geotif = '' + input_csv = '' + if ext == '.csv': + # Use CSV as input. It is assumed to have a date column. + input_csv = filename + else: + input_geotif = filename + # Get date from geoTif filename as bands may not have the + # date. + output_date = earthengine_image.get_date_from_filename( + filename, self.get_config('time_period', 'P1D', + config_dict)) + if output_date: + self.set_config('output_date', output_date) + config = self.get_configs() + config.update(config_dict) + raster_to_csv.process(input_geotif, input_csv, output_filename, + ConfigMap(config_dict=config), self.counters) + output_files.append(output_filename) + return output_files + + +# Register the RasterCSVRunner +register_stage_runner('raster_csv', RasterCSVRunner) diff --git a/scripts/earthengine/pipeline_stage_runner.py b/scripts/earthengine/pipeline_stage_runner.py new file mode 100644 index 0000000000..43a8b0ef28 --- /dev/null +++ b/scripts/earthengine/pipeline_stage_runner.py @@ -0,0 +1,357 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the 'License'); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an 'AS IS' BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Class for running a stage in the events pipeline. +To create a new stage in the events_pipeline, create a derived class of +StageRunner and overload run() with the stage speicifc processing. +Then register the stage runner with: + register_stage_runner() +""" + +import os +import sys + +from absl import logging + +_SCRIPTS_DIR = os.path.dirname(__file__) +sys.path.append(_SCRIPTS_DIR) +sys.path.append(os.path.dirname(_SCRIPTS_DIR)) +sys.path.append(os.path.dirname(os.path.dirname(_SCRIPTS_DIR))) +sys.path.append( + os.path.join(os.path.dirname(os.path.dirname(_SCRIPTS_DIR)), 'util')) + +import file_util +import utils + +from counters import Counters + + +class StageRunner: + '''Class to run a single stage of the pipeline. + Create a derived class with run() method calling necessary processing. + Example: + class MyStage(StageRunner): + def __init__(self, + config_dicts: list = [], + state: dict = {}, + counters=None): + # Call StageRunner.set_up() to initialize settings. + self.set_up('My-Stage', configs, state, counters) + + # Function called when the stage is run by the pipeline. + # Return a list of output files generated by this stage. + def run(self, + input_files: list = None, + config: dict = {}, + counters: Counters = None) -> list: + outputs = [] + for file in input_files: + outputs.append(my_process(file, config, counters)) + return outputs + + Then add the class to the map of stage names:_STAGE_RUNNERS below. + ''' + + def __init__(self, + config_dicts: list = [], + state: dict = {}, + counters=None): + self.set_up('runner', config_dicts, state, counters) + + def run(self, + input_files: list = None, + config: dict = {}, + counters: Counters = None) -> list: + '''Override in child class. + Returns the output files generated after running processing for this stage + on the input_files. + + Args: + input_files: List of files to process + they are outputs from previous stage along with any files + matching config['input_files']. + config: dictionary of configuration settings for this stage. + counters: global counters for the task. + Returns: + list of output files that are passed on to the next stage as inputs. + ''' + logging.fatal( + f'run() not implemented in {self.__class__}. Use a class with run() overridden.' + ) + return [] + + def set_up(self, + name: str, + config_dicts: list = [], + state: dict = {}, + counters=None): + '''Called by derived classes to set up configs and state in the base class. + Args: + name: string name of this stage, used in config + config_dicts: dictionary of settings specific to this stage + state: dictionary of parameters with current pipeline state + counters: set of names counters for the pipeline + ''' + self.name = name + # Dynamic state with parameters to be updated after run. + self.state = state + # Set config as a merged dict + self.config = _merge_dicts(config_dicts) + self.config['stage_name'] = name + # Counters for this stage. + self.counters = counters + if counters is None: + self.counters = Counters() + self.set_config_dates() + self.set_output_dir() + logging.info( + f'Created stage: {name} with config: {self.config} from configs: {config_dicts}' + ) + + def get_name(self): + '''Returns the name for this stage.''' + return self.name + + def run_stage(self, input_files: list) -> list: + '''Returns the output files after running the stage. + Args: + input_files: list of input files to be processed. + It could be output from previous stages or files listed in the config. + Returns: + list of output files gnerated. + This is passe don to the next stage as inputs. + ''' + # Get input files from args or config. + input_files = self.get_inputs(input_files) + + # Get resolved config for running stage. + self.config.update(self.state) + config = self.get_configs() + + # Run the stage + logging.info( + f'Running stage: {self.name} with {len(input_files)} inputs: {input_files} and config: {config}' + ) + output_files = self.run(input_files, config, self.counters) + logging.info(f'Got output for {self.name}: {output_files}') + + # Set the state for the stage + stage_state = self.get_state(self.name, {}) + stage_state['input'] = ','.join(input_files) + if output_files: + if isinstance(output_files, list): + stage_state['output'] = ','.join(output_files) + else: + stage_state['output'] = output_files + self.set_state(self.name, stage_state) + return output_files + + def get_inputs(self, inputs: list = []) -> list: + '''Return a set of files matching inputs of the config. + Gets files matching the pattern in the config for 'input_files' + and the patter in the inputs list. + ''' + # Get inputs from previous stage output and config. + input_list = [] + if inputs: + input_list.extend(inputs) + config_inputs = self.get_config('input_files', '') + if config_inputs: + input_list.append(config_inputs) + # Get list of existing files for the patterns. + input_pat = _format(','.join(input_list), self.config) + return file_util.file_get_matching(input_pat) + + def set_output_dir(self) -> str: + '''Sets the output directory in the config if not set.''' + if not self.get_config('output_dir', ''): + import_dir = self.get_config('import_dir', '') + output_dir = os.path.join(import_dir, self.name) + self.set_config('output_dir', output_dir) + + def get_output_dir(self, config_dict: dict = {}) -> str: + '''Returns the output directory from the config.''' + return self.get_config('output_dir', '', config_dict) + + def get_output_filename(self, + input_filename: str = '', + config_dict: dict = {}, + file_ext: str = '.csv') -> str: + '''Returns the file name for output from the output_dir in the config + and the basename of the input file with the file_ext specified.''' + filename = self.get_config('output_file', '', config_dict) + if not filename: + # Create filename from GCS settings. + output_dir = self.get_output_dir(config_dict) + stage_name = self.get_name() + if not output_dir: + gcs_bucket = self.get_config('gcs_bucket', '') + gcs_folder = self.get_config('gcs_folder', '') + if gcs_bucket and gcs_folder: + output_dir = f'gs://{gcs_bucket}/{gcs_folder}/{stage_name}' + if output_dir: + if input_filename: + filename = file_util.file_get_name(os.path.join( + output_dir, os.path.basename(input_filename)), + suffix=f'-{stage_name}') + else: + filename = f'{output_dir}/{import_name}-{stage_name}-{start_date}-{time_period}{file_ext}' + + return _format(filename, self.config) + + def should_skip_existing_output(self, filename: str) -> bool: + '''Returns True if the output filename exists and + skip_existing_output is True in the config. + This is used to skip running a stage for outputs already generated.''' + if self.get_config('skip_existing_output', True): + existing_file = file_util.file_get_matching(filename) + if existing_file: + return True + return False + + def get_config(self, + param: str, + default_value: str = '', + config_dict: dict = {}) -> str: + '''Returns the resolved config value for the param from config_dict + or object's config.''' + if config_dict: + value = config_dict.get(param, None) + if value: + return _format(value, config_dict) + value = self.config.get(param, default_value) + return _format(value, self.config) + + def set_config(self, param: str, value: str) -> str: + '''Set the value of the config parameter.''' + self.config[param] = value + return value + + def get_configs(self) -> dict: + '''Returns the dictionary of config parameter:values.''' + return _get_resolved_dict(self.config) + + def get_state(self, key: str, default_value: str = '') -> str: + '''Returns the value for the key from the processing state dict.''' + return self.state.get(key, default_value) + + def set_state(self, key: str, value: str): + '''Sets the value of the pipeline state.''' + self.state[key] = value + return value + + def set_config_dates(self, start_date: str = ''): + '''Set the dates in the config based on processing state. + if the config 'start_date' is set, then the configs for + 'year', 'month' and 'day' are also updated. + + Args: + start_date: date string in the form YYYY-MM-DD for + the start date for the stage. + ''' + # Set start_date to be the next date from the last input date + if start_date: + self.set_config('start_date', start_date) + start_date = self.get_config('start_date', '') + if not start_date: + # Set the start_date to the last processed date. + last_input_date = self.get_state('last_input_date', '') + if last_input_date: + start_date = utils.date_advance_by_period( + self.get_state('last_input_date', ''), + self.get_config('time_period', 'P1M')) + logging.info( + f'Setting start_date to {start_date} from last_input_date: {last_input_date}' + ) + if not start_date: + # No date set, set to start of year. + start_date = utils.date_today('%Y-01-01') + logging.info( + f'Setting start_date to start of year: {start_date}') + if start_date: + self.set_config('start_date', start_date) + date_tokens = start_date.split('-') + if len(date_tokens) > 0: + self.set_config('year', date_tokens[0]) + if len(date_tokens) > 1: + self.set_config('month', date_tokens[1]) + if len(date_tokens) > 2: + self.set_config('day', date_tokens[2]) + + +# List of runners for each names stage. +# Add any new classes derived from StageRunner here +# using register)_stage_runner() +_STAGE_RUNNERS = {} + + +def register_stage_runner(name: str, runner: StageRunner): + '''Register the name for a stage runner class. + Args: + name: string used as name for the stage in pipeline configs. + runner: class derived form StageRunner. + ''' + global _STAGE_RUNNERS + if name and name not in _STAGE_RUNNERS: + _STAGE_RUNNERS[name] = runner + else: + logging.fatal( + f'Invalid or existing name {name} for stage runner {runner}') + + +def get_stage_runner(name: str) -> StageRunner: + '''Returns the stage runner class for the named stage. + Args: + name: string name of the runner. + It should be registered with register_stage_runner() earlier. + + Throws a fatal exception if there is no runner registered for the name. + ''' + if name in _STAGE_RUNNERS: + return _STAGE_RUNNERS[name] + logging.fatal(f'No stage runner registered for {name}') + + +def _merge_dicts(config_dicts: list) -> dict: + config = {} + if not isinstance(config_dicts, list): + config_dicts = [config_dicts] + for d in config_dicts: + config.update(d) + return config + + +def _get_resolved_dict(config: dict) -> dict: + '''Resolve format string references in the values of the config dict.''' + resolved_config = {} + for param in config.keys(): + value = config[param] + if value and isinstance(value, str): + # Resolve string value. + resolved_config[param] = _format(value, config) + else: + resolved_config[param] = value + return resolved_config + + +def _format(string: str, params: dict) -> str: + '''Returns the string with format patterns replaced.''' + formatted_str = string + try: + if isinstance(string, str): + formatted_str = string.format(**params) + elif isinstance(string, list): + formatted_str = [_format(s, params) for s in string] + except (KeyError, IndexError) as e: + logging.error(f'Format error for {string} with {params}') + return formatted_str diff --git a/scripts/earthengine/process_events.py b/scripts/earthengine/process_events.py index fb83b211ba..ae5be1a589 100644 --- a/scripts/earthengine/process_events.py +++ b/scripts/earthengine/process_events.py @@ -16,6 +16,7 @@ import csv import datetime +import json import os import pickle import sys @@ -36,9 +37,6 @@ #os.environ['PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION'] = 'python' #from pypprof.net_http import start_pprof_server -flags.DEFINE_string('input_csv', '', - 'CSV with place data to process into events') -flags.DEFINE_string('config', '', 'JSON config file') flags.DEFINE_string('config_string', '', 'config settings that override config file') flags.DEFINE_string('input_events', '', 'File with active events to be loaded') @@ -56,7 +54,6 @@ # WHERE type = "S2CellLevel10" flags.DEFINE_string('place_cache_file', '', 'CSV file with dcid to containedInPlace mapping') -flags.DEFINE_bool('debug', False, 'Enable debug messages') flags.DEFINE_integer('pprof_port', 8081, 'HTTP port for pprof server.') _FLAGS = flags.FLAGS @@ -65,110 +62,19 @@ sys.path.append(_SCRIPTS_DIR) sys.path.append(os.path.dirname(_SCRIPTS_DIR)) sys.path.append(os.path.dirname(os.path.dirname(_SCRIPTS_DIR))) +sys.path.append( + os.path.join(os.path.dirname(os.path.dirname(_SCRIPTS_DIR)), 'util')) +import common_flags +import file_util +import statvar_dcid_generator import utils -from util.counters import Counters -from util.latlng_recon_geojson import LatLng2Places -from util.config_map import ConfigMap -from util.dc_api_wrapper import dc_api_batched_wrapper - -_DEBUG = False - -_DEFAULT_CONFIG = { - # Input settings. - # Columms of input_csv that are added as event properties - 'input_columns': [], - # Columns of input_csv that contains the place such as s2 cell id. - 'place_column': 's2CellId', - # Input column for date. - 'date_column': 'observationDate', - # Rename input columns to output columns. - 'input_rename_columns': { - # Only output columns starting with lower case are added to tmcf. - # '': '' - #'date': 'observationDate', - }, - - # Processing settings - # Maximum distance within which 2 events are merged. - 'max_overlap_distance_km': 10, - # S2 level to which data is aggregated. - 's2_level': 10, # Events are at resolution of level-10 S2 cells. - 'aggregate': 'sum', # default aggregation for all properties - # Per property filter params for input data. - 'input_filter_config': { - # '' : { - # 'min': , - # 'max': , - # 'regex': '', - # }, - }, - # Per property filter params for output events - 'output_events_filter_config': { - # '' : { - # 'min': , - # 'max': , - # 'regex': '', - # }, - }, - # Per property aggregation settings for an event across places and dates. - # For different per-date and per-place aggregations, use the settings - # 'property_config_per_date' and 'property_config_across_dates'. - 'property_config': { - 'aggregate': 'max', - 'area': { - 'aggregate': 'sum', - 'unit': 'SquareKilometer', - }, - 'affectedPlace': { - 'aggregate': 'list', - }, - }, - # Per property aggregation settings for a date across multiple places. - # Falls back to 'property_config' if not set. - # 'property_config_per_date': { - # # Default aggregation for all properties: pick max value across cells. - # 'aggregate': 'max', - # 'area': { - # 'aggregate': 'sum', - # 'unit': 'SquareKilometer', - # }, - # 's2CellId': { - # 'aggregate': 'list', - # }, - # }, - # Per property aggregation settings across multiple dates. - # Falls back to 'property_config' if not set. - # 'property_config_across_dates': { - # # Default aggregation for all properties: pick max value across cells. - # 'aggregate': 'max', - # 'area': { - # 'aggregate': 'max', - # 'unit': 'SquareKilometer', - # }, - # 's2CellId': { - # 'aggregate': 'list', - # }, - # }, - # Threshold for dates and places in events - # Treat events at the same location more than 90 days apart as separate events. - 'max_event_interval_days': 90, - 'max_event_duration_days': 90, - 'max_event_places': 10000, - - # Output settings. - 'event_type': 'FloodEvent', - 'resolve_affected_place_latlng': True, - 'output_affected_place_polygon': 'geoJsonCoordinatesDP1', - 'polygon_simplification_factor': 0.1, - - # Disable svobs output until it can be used in UI - 'output_svobs': False, - 'output_active_svobs': False, - # Disable place lookups for s2 cells to be added to affectedPlace. - 'lookup_contained_for_place': False, -} +from aggregation_util import aggregate_dict +from counters import Counters +from latlng_recon_geojson import LatLng2Places +from config_map import ConfigMap +from dc_api_wrapper import dc_api_batched_wrapper class GeoEvent: @@ -192,6 +98,7 @@ def __init__(self, self._merged_into_event = None self.start_date = '' self.end_date = '' + self._is_valid = True # Set input values if not config: @@ -201,6 +108,14 @@ def __init__(self, if place_id and date and pvs: self.add_place_pvs(place_id, date, pvs) + def __str__(self): + '''Returns a string representation of the object.''' + return f'GeoEvent:{self._event_id}, Places:{self._places}' + + def __repr__(self): + '''Returns a string representation of the object.''' + return f'GeoEvent(\'{self._event_id}\': {self._places})' + def add_place_pvs(self, place_id: str, date: str, pvs: dict): '''Add an S2Cell for a given date into this event.''' if not self._event_id: @@ -212,11 +127,11 @@ def add_place_pvs(self, place_id: str, date: str, pvs: dict): place_dates[date] = dict() self.end_date = max(self.end_date, date) place_date_pvs = place_dates[date] - utils.dict_aggregate_values( + aggregate_dict( pvs, place_date_pvs, self._config.get('property_config_per_date', self._config.get('property_config', {}))) - _DEBUG and logging.debug( + logging.level_debug() and logging.debug( f'Added {place_id}:{date}:{pvs} into event:{self._event_id}:{self._places}' ) @@ -234,7 +149,10 @@ def get_places(self) -> dict: def merge_event(self, place_event): '''Merge places and PVs from place_event into this event.''' # Check event to be merged doesn't have a parent. - if self == place_event or place_event.get_root_event() != place_event: + if self == place_event: + # Event is already merged. + return + if place_event.get_root_event() != place_event: logging.fatal( f'Cannot merge non-root event {place_event._event_id} into {self._event_id}' ) @@ -244,7 +162,7 @@ def merge_event(self, place_event): self.add_place_pvs(place_id, date, pvs) # Set current event as parent for merged event place_event._merged_into_event = self - _DEBUG and logging.debug( + logging.level_debug() and logging.debug( f'Merged events {place_event.event_id()} into {self.event_id()}: {self._places}' ) @@ -269,8 +187,7 @@ def get_event_places(self, dates: set = {}) -> list: for date, pvs in date_pvs.items(): if not dates or date in dates: place_ids.add(place_id) - if 'affectedPlace' in pvs: - place_ids.update(pvs.get('affectedPlace', '').split(',')) + place_ids.update(_get_list(pvs.get('affectedPlace', ''))) return sorted(list(place_ids)) def get_event_properties(self, dates: set = {}) -> dict: @@ -280,12 +197,12 @@ def get_event_properties(self, dates: set = {}) -> dict: per_place_pvs = {} for date, date_pvs in date_pvs.items(): if not dates or date in dates: - utils.dict_aggregate_values( + aggregate_dict( date_pvs, per_place_pvs, self._config.get( 'property_config_across_dates', self._config.get('property_config', {}))) - utils.dict_aggregate_values( + aggregate_dict( per_place_pvs, pvs, self._config.get('property_config_per_date', self._config.get('property_config', {}))) @@ -314,7 +231,7 @@ def get_event_properties_by_dates(self) -> dict: if date not in pvs_by_dates: pvs_by_dates[date] = dict() pvs_for_date = pvs_by_dates[date] - utils.dict_aggregate_values( + aggregate_dict( pvs, pvs_for_date, self._config.get('property_config_per_date', self._config.get('property_config', {}))) @@ -376,13 +293,13 @@ def __init__(self, config: ConfigMap, counters: Counters = None): # Caches self._place_cache_modified = False # dictionary from latlng to places: { ':': [] } - self._latlng_to_place_cache = utils.file_load_csv_dict( + self._latlng_to_place_cache = file_util.file_load_csv_dict( filename=self._config.get('place_cache_file'), key_column=self._config.get('place_cache_key'), value_column=self._config.get('place_cache_value'), config=self._config.get('place_cache_config', {})) # dictionary from placeid to tuple { : (lat, lng) } - self._place_property_cache = utils.file_load_py_dict( + self._place_property_cache = file_util.file_load_py_dict( self._config.get('place_property_cache_file', '')) self._place_cache_modified = False self._ll2p = None @@ -395,14 +312,22 @@ def __init__(self, config: ConfigMap, counters: Counters = None): for prop in data_columns: self._event_props.add(rename_columns.get(prop, prop)) self._event_props.add('area') + if self._config.get('debug', False): + logging.set_verbosity(2) + # dictionary of deleted events by id. + # Events are not fully deleted to preserve any references. + self._deleted_events = {} + + def get_events(self): + '''Returns dictionary of all events by id.''' + return self._event_by_id def add_geo_event(self, geo_event: GeoEvent): '''Add a geo event to the dict.''' self._event_by_id[geo_event.event_id()] = geo_event - for place_id in geo_event.get_places().keys(): - self._active_event_by_place[place_id] = geo_event + self.add_event_to_place_index(geo_event) self._counters.add_counter('geo_events_added', 1) - _DEBUG and logging.debug( + logging.level_debug() and logging.debug( f'Added event {geo_event.event_id()}, num events: {len(self._event_by_id)}, num places: {len(self._active_event_by_place)}' ) @@ -469,7 +394,7 @@ def get_events_for_place(self, place_id: str) -> list: self._counters.max_counter('max_neighbours_considered', len(neighbour_places)) - _DEBUG and logging.debug( + logging.level_debug() and logging.debug( f'Got event_ids: {event_ids} for {len(neighbour_places)} neighbors of {place_id}' ) return list(event_ids) @@ -531,24 +456,85 @@ def deactivate_old_events(self, event_ids: list, date: str) -> list: active_ids.append(event_id) else: # Event ended too long ago. Remove from active s2 cells. - _DEBUG and logging.debug( + logging.level_debug() and logging.debug( f'Deactivating event: {event_id} with end date older than {min_date}' ) - self.remove_event_from_place_index(event_id) + event = self.get_event_by_id(event_id) + if event: + places = event.get_places() + self.remove_event_from_place_index(event_id) + self._counters.add_counter('events_deactivated', 1, + event_id) + self._counters.add_counter('events_places_deactivated', + len(places), event_id) return active_ids + def add_event_to_place_index(self, event: GeoEvent): + '''Add places for an event into the lace index.''' + if not event: + return + event_id = event.event_id() + places = event.get_places().keys() + logging.level_debug() and logging.debug( + f'Adding event {event_id} to place index for: {places}') + for place_id in places: + self._active_event_by_place[place_id] = event + def remove_event_from_place_index(self, event_id: str): '''Remove the s2 cells for this event from the _active_event_by_place index.''' event = self.get_event_by_id(event_id) + if not event: + return places = event.get_places().keys() - _DEBUG and logging.debug( + logging.level_debug() and logging.debug( f'Removing event {event_id} active places: {places}') for place_id in places: - if place_id in self._active_event_by_place: + place_event = self._active_event_by_place.get(place_id, None) + if place_event and place_event.event_id() == event_id: self._active_event_by_place.pop(place_id) - self._counters.add_counter('events_deactivated', 1, event_id) - self._counters.add_counter('events_places_deactivated', len(places), - event_id) + + def merge_events(self, event_ids: list) -> GeoEvent: + '''Returns a merged event combining all event_ids. + + This is called with a list of events_ids that have places that + have started to overlap or have expanded to come close enough to each other + with addition of new places to some of these events. + They are merged into a single large event. + The 'root_event' is the event id into whcih others events are merged. + The event with the alphabetically sorted first event id, + which would be the earliest since the start date is the event id prefix, + is used as the root and others events are merged into it. + + Args: + event_ids: list of events ids to be merged into a single event. + The event with the lowest event_id is picked as the root + and other events are merged into it. + The places from all other events are added to the root event. + References to the merged event in place map is also removed. + Returns: + the merged event. + ''' + # Merge all events with into a root event with the earliest date. + sorted_ids = sorted(list(event_ids)) + logging.level_debug() and logging.debug(f'Merging events: {sorted_ids}') + if not sorted_ids: + return None + # Get the event with the earliest date. + root_event_id = sorted_ids[0] + root_event = self.get_event_by_id(root_event_id) + if not root_event: + logging.debug(f'Unable to find event for {root_event_id}') + return None + for event_id in sorted_ids[1:]: + event = self.get_event_by_id(event_id) + if event and event != root_event: + # Merge the data from event into root and + # remove references to the event. + root_event.merge_event(event) + self.delete_event(event_id) + self.add_event_to_place_index(root_event) + self._counters.add_counter('events_merged', len(sorted_ids)) + return root_event def add_place_data(self, place_id: int, date: str, pvs: dict) -> str: '''Returns the event id after adding place with PVs for a date.''' @@ -568,29 +554,22 @@ def add_place_data(self, place_id: int, date: str, pvs: dict) -> str: config=self._config) self.add_geo_event(event) event_id = event.event_id() - _DEBUG and logging.debug( + logging.level_debug() and logging.debug( f'Created new event: {event_id} for {place_id}:{date}:{pvs}') return event_id # Merge all events that new region overlaps with into a root event with # the earliest date. - sorted_ids = sorted(list(event_ids)) - _DEBUG and logging.debug( - f'Merging events for cell: {place_id}: {sorted_ids}') - # Get the event with the earliest date. - root_event_id = sorted_ids[0] - root_event = self.get_event_by_id(root_event_id) + root_event = self.merge_events(event_ids) if not root_event: - logging.fatal(f'Unable to find event for {root_event_id}') + logging.debug(f'Unable to find event for {root_event_id}') + return None + root_event_id = root_event.event_id() root_event.add_place_pvs(place_id, date, pvs) self._counters.add_counter('event_places_added', 1, root_event_id) - for event_id in sorted_ids[1:]: - event = self.get_event_by_id(event_id) - root_event.merge_event(event) - _DEBUG and logging.debug( + logging.level_debug() and logging.debug( f'Added {place_id}, {date}, {pvs} into event: {root_event_id}') self._counters.add_counter('event_mergers', 1) - self._counters.add_counter('events_merged', len(sorted_ids)) self._counters.max_counter('max_event_places', len(root_event.get_places())) self._max_date = max(self._max_date, date) @@ -601,7 +580,8 @@ def get_all_event_ids(self) -> set: event_ids = set() for event_id in self._event_by_id.keys(): event = self.get_event_by_id(event_id) - event_ids.add(event.event_id()) + if event: + event_ids.add(event.event_id()) return event_ids def cache_event_place_property(self, event_ids: list = None): @@ -620,6 +600,8 @@ def cache_event_place_property(self, event_ids: list = None): lookup_names = set() for event_id in event_ids: event = self.get_event_by_id(event_id) + if not event: + continue place_ids = event.get_event_places() for placeid in place_ids: if (not utils.is_grid_id(placeid)) and ( @@ -643,7 +625,7 @@ def cache_event_place_property(self, event_ids: list = None): 'containedInPlace', {}) for place_id, contained_place_ids in contained_place_dict.items(): if contained_place_ids: - lookup_names.update(contained_place_ids) + lookup_names.update(_get_list(contained_place_ids)) self._counters.add_counter('total', len(lookup_places)) self.prefetch_placeid_property('name', lookup_names) self.prefetch_placeid_property('typeOf', lookup_names) @@ -661,7 +643,7 @@ def prefetch_placeid_property(self, prop: str, place_ids: list = None): cache_dict = self._place_property_cache.get(prop, {}) lookup_places = [] for place in place_ids: - places = place.split(',') + places = _get_list(place) for placeid in places: placeid = utils.strip_namespace(placeid) if placeid not in cache_dict: @@ -687,7 +669,7 @@ def prefetch_placeid_property(self, prop: str, place_ids: list = None): def save_place_cache_file(self): '''Cleanup and save and caches.''' if self._place_cache_modified: - utils.file_write_py_dict( + file_util.file_write_py_dict( self._place_property_cache, self._config.get('place_property_cache_file', '')) self._place_cache_modified = False @@ -703,6 +685,10 @@ def get_place_property(self, placeid: str, prop: str) -> str: self._counters.add_counter(f'cache_place_property_{prop}_miss', 1) return value + def get_place_property_list(self, placeid: str, prop: str) -> list: + '''Returns the property values for the place as a list.''' + return _get_list(self.get_place_property(placeid, prop)) + def set_place_property(self, placeid: str, prop: str, value: str) -> bool: '''Set the property for the place id.''' if prop is None or value is None: @@ -717,16 +703,16 @@ def set_place_property(self, placeid: str, prop: str, value: str) -> bool: value = str(value) value = [value] # Add value to existing property values for the place - cache_values = cache_dict.get(placeid, None) + cache_values = _get_list(cache_dict.get(placeid, None)) if cache_values is None: cache_dict[placeid] = value value_added = True else: # Add any new values not in cache. new_values = set(cache_values) - new_values.update(value) + new_values.update(_get_list(value)) if len(new_values) != len(cache_values): - cache_dict[placeid] = list(new_values) + cache_dict[placeid] = ','.join(new_values) value_added = True if value_added: self._place_cache_modified = True @@ -756,7 +742,7 @@ def get_event_output_properties(self, event_id: str) -> dict: if not event: self._counters.add_counter('error-missing-event-for-id', 1, event_id) - logging.fatal(f'Unable to get event for {event_id}') + logging.debug(f'Unable to get event for {event_id}') return None event_pvs = dict() event_pvs['dcid'] = event_id @@ -770,6 +756,8 @@ def get_event_output_properties(self, event_id: str) -> dict: event_pvs['endDate']) event_pvs['observationPeriod'] = f'P{duration_days}D' event_pvs['DurationDays'] = duration_days + event_pvs['numberOfDays'] = len(dates) + event_pvs['observationDate'] = ','.join(dates) self._counters.max_counter('max_output_events_dates', len(dates)) # Set the start location from the place with the earliest date start_place_ids = event.get_event_places( @@ -787,28 +775,34 @@ def get_event_output_properties(self, event_id: str) -> dict: # Got lat long for place. Cache it event_pvs['startLocation'] = f'[LatLong {lat:.5f} {lng:.5f}]' event_data = event.get_event_properties() - allow_pvs = utils.dict_filter_values( - event_data, self._config.get('output_events_filter_config', {})) - if not allow_pvs: - return None # Save area as a number without units area_sqkm = event_data.get('area', 0) if area_sqkm: - event_pvs['AreaSqKm'] = area_sqkm + event_pvs['AreaSqKm'] = round(area_sqkm, 5) # Transform values into quantity ranges format_config = self._config.get('property_config', {}) per_date_config = self._config.get('property_config_per_date', {}) if per_date_config: format_config.update(per_date_config) event_pvs.update(_format_property_values(event_data, format_config)) + allow_pvs = utils.dict_filter_values( + event_pvs, self._config.get('output_events_filter_config', {})) + if not allow_pvs: + return None # Generate polygon for the event - polygon_prop = self._config.get('output_affected_place_polygon', '') + polygon_prop = self._config.get('output_affected_place_polygon', + 'geoJsonCoordinatesDP1') if polygon_prop: event_polygon = self.get_event_polygon(event_id) if event_polygon: geo_json = mapping(event_polygon) if geo_json: - event_pvs[polygon_prop] = geo_json + # TODO: remove config after confirming json format + if self._config.get('output_geojson_string', False): + event_pvs[polygon_prop] = str(geo_json) + else: + event_pvs[polygon_prop] = json.dumps( + json.dumps(geo_json)) self._counters.add_counter('output_events_with_polygon', 1) if not event_pvs.get('name', None): event_pvs['name'] = self._get_event_name(event_pvs) @@ -816,12 +810,160 @@ def get_event_output_properties(self, event_id: str) -> dict: self._set_event_places(event, event_pvs) return event_pvs + def delete_event(self, event_id): + '''Removes the event from list of events.''' + event = self.get_event_by_id(event_id) + if not event: + return + self.remove_event_from_place_index(event_id) + if event_id in self._event_by_id: + self._event_by_id.pop(event_id) + self._deleted_events[event_id] = event + self._counters.add_counter('events-deleted', 1) + + def get_place_date_output_properties(self, event_ids: list, + event_props: list) -> dict: + '''Returns a dict event properties {(place, date): {'area': NN},... } + + Args: + event_ids: list of event ids to be used. + event_props: List of event properties to add per place,date. + Example: ['area', 'count'] + + Returns: + dictionary keyed by string ',YYYY-MM-DD' with + event property values, such as { 'area': 100 } aggregated + by place and date + ''' + # Collect data for each event's (place, date) + # as a dict: {(place, date): {'area': NN},... } + place_date_pvs = dict() + _set_counter_stage(self._counters, 'collect_place_date_svobs_') + self._counters.set_counter('total', len(event_ids)) + for event_id in event_ids: + self._counters.add_counter('processed', 1) + event = self.get_event_by_id(event_id) + if not event: + self._counters.add_counter( + 'error_place_svobs_missing_event_for_id', 1, event_id) + logging.debug(f'Unable to get event for {event_id}') + continue + + # Process all places with property:values per date for the event. + for placeid, date_pvs in event.get_places().items(): + for date, pvs in date_pvs.items(): + # Collect all property:values for a given place and date. + key = f'{placeid},{date}' + date_pvs = {} + if 'count' in event_props: + # Collect unique event ids to generate counts + date_pvs['EventId'] = set( + {utils.strip_namespace(event_id)}) + for p, v in pvs.items(): + if p in event_props: + date_pvs[p] = v + if key not in place_date_pvs: + place_date_pvs[key] = dict(date_pvs) + else: + aggregate_dict(date_pvs, place_date_pvs[key], + property_config_per_date) + logging.info( + f'Generated {len(place_date_pvs)} svobs for event places and dates') + return place_date_pvs + + def aggregate_by_time_period(self, place_date_pvs: dict, + date_formats: list): + '''Aggregates the properties across dates for each place. + + Args: + place_date_pvs: dictionary of property:values keyed by ',date>' + date_formats: list of date formats to aggregate by, such as, + ['YYYY', 'YYYY-MM' ] + Returns: + dictionary of properties keyed by 'place id,date'. + ''' + if not date_formats: + # No aggregation by time period. + return + # Aggregation settings for event properties across dates for a place. + property_config_across_dates = { + 'aggregate': 'max', + 'area': { + 'aggregate': 'max' + }, + 'EventId': { + 'aggregate': 'set' + } + } + property_config_across_dates.update( + self._config.get('property_config_across_dates', {})) + + _set_counter_stage(self._counters, 'aggregate_by_date_') + self._counters.set_counter('total', len(place_date_pvs)) + num_svobs = 0 + for place_date in list(place_date_pvs.keys()): + self._counters.add_counter('processed', 1) + pvs = place_date_pvs[place_date] + placeid, date = place_date.split(',', 1) + for date_format in date_formats: + date_str = _get_date_by_format(date, date_format) + if date_str and date_str != date: + key = f'{placeid},{date_str}' + if key == place_date: + continue + if key not in place_date_pvs: + place_date_pvs[key] = dict(pvs) + num_svobs += 1 + else: + aggregate_dict(pvs, place_date_pvs[key], + property_config_across_dates) + logging.info( + f'Generated {num_svobs} SVObs for time periods: {date_formats}') + + def aggregate_by_contained_in_place(self, place_date_pvs: dict): + '''Aggregate dictionary by containedInPlace parent of each place. + Dictionary is of the form { ',': { 'area': NN' } } + The property:values for a place,date are aggregated into + each of it's parent places for the same set of dates. + ''' + _set_counter_stage(self._counters, 'aggregate_by_place_') + self._counters.set_counter('total', len(place_date_pvs)) + num_parents = 0 + for place_date in list(place_date_pvs.keys()): + self._counters.add_counter('processed', 1) + pvs = place_date_pvs[place_date] + placeid, date = place_date.split(',', 1) + parent_places = self.get_place_property_list( + placeid, 'containedInPlace') + if not parent_places: + self._counters.add_counter('aggr-no-parent-places', 1) + continue + parents = set(_get_list(parent_places)) + if placeid in parents: + parents.remove(placeid) + # Add an entry for each parent place + for parent_place in parents: + if not parent_place: + continue + key = f'{parent_place},{date}' + if key == place_date: + continue + if key not in place_date_pvs: + place_date_pvs[key] = dict(pvs) + num_parents += 1 + else: + aggregate_dict( + pvs, place_date_pvs[key], + self._config.get('property_config_per_date', + {'aggregate': 'sum'})) + logging.info(f'Generated {num_parents} SVObs for parent places,dates') + def write_events_csv(self, output_path: str, event_ids: list = None, - output_ended_events: bool = False): + output_ended_events: bool = False) -> str: '''Write the events into a csv file.''' - output_csv = utils.file_get_name(output_path, 'events', '.csv') + output_csv = file_util.file_get_name(output_path, 'events', '.csv') # Default output columns for events output_columns = [ 'dcid', @@ -831,21 +973,21 @@ def write_events_csv(self, 'endDate', 'observationPeriod', 'DurationDays', + 'numberOfDays', 'startLocation', 'affectedPlace', 'AffectedPlaceCount', #'containedInPlace', - 'ContainedInPlaceCount', 'area', 'AreaSqKm', - 'subEvents', ] # Output additional event specific properties from data source for prop in sorted(list(self._event_props)): if prop not in output_columns: output_columns.append(prop) # Add column for affected place polygon - polygon_prop = self._config.get('output_affected_place_polygon', '') + polygon_prop = self._config.get('output_affected_place_polygon', + 'geoJsonCoordinatesDP1') if polygon_prop: output_columns.append(polygon_prop) if event_ids is None: @@ -856,40 +998,45 @@ def write_events_csv(self, _set_counter_stage(self._counters, utils.strip_namespace(counter_stage)) num_output_events = 0 # Generate a csv row for each event - with open(output_csv, 'w') as csv_file: + with file_util.FileIO(output_csv, 'w') as csv_file: writer = csv.DictWriter(csv_file, fieldnames=output_columns, + delimiter=self._config.get( + 'output_delimiter', ','), escapechar='\\', extrasaction='ignore', quotechar='"', - quoting=csv.QUOTE_NONNUMERIC) + quoting=csv.QUOTE_NONNUMERIC, + doublequote=False) writer.writeheader() self._counters.set_counter('total', len(event_ids)) for event_id in event_ids: event_pvs = self.get_event_output_properties(event_id) if event_pvs: - writer.writerow(event_pvs) + writer.writerow(_format_property_values(event_pvs)) self._counters.add_counter('output_events', 1) else: + self.delete_event(event_id) self._counters.add_counter('output_events_filtered', 1) num_output_events += 1 self._counters.add_counter('processed', 1) logging.info( f'Wrote {num_output_events} events into {output_csv} with columns: {output_columns}' ) - self.write_tmcf(utils.file_get_name(output_path, 'events', '.tmcf'), + self.write_tmcf(file_util.file_get_name(output_path, 'events', '.tmcf'), output_columns) self._counters.print_counters() + return output_csv def write_tmcf(self, output_file: str, columns: list, fixed_props: dict = None, - prefix: str = 'Events'): + prefix: str = 'Events') -> str: '''Generate tMCF for columns with valid schema.''' if not prefix: prefix = 'Events' - with open(output_file, 'w') as tmcf_file: + with file_util.FileIO(output_file, 'w') as tmcf_file: tmcf_file.write(f'Node: E:{prefix}->E0') output_prop = list() skipped_prop = list() @@ -908,30 +1055,35 @@ def write_tmcf(self, logging.info( f'Wrote tMCF: {output_file} with properties:{output_prop}, skipped properties: {skipped_prop}' ) + return output_file def write_events_svobs(self, output_path: str, event_ids: list = None, output_ended_events: bool = False, - event_props: list = None, - min_date: str = '', - max_date: str = ''): + event_props: list = None) -> list: '''Write SVObs for all events into a CSV.''' - output_csv = utils.file_get_name(output_path, 'svobs', '.csv') + output_files = [] + output_csv = file_util.file_get_name(output_path, 'svobs', '.csv') output_columns = ['dcid', 'observationDate'] if not event_props: # No specific properties given. Generate SVObs for all properties. event_props = sorted(list(self._event_props)) - output_columns.extend(event_props) + for prop in event_props: + if prop not in output_columns: + output_columns.append(prop) if not event_ids: event_ids = self.get_all_event_ids() - with open(output_csv, 'w') as csv_file: + with file_util.FileIO(output_csv, 'w') as csv_file: writer = csv.DictWriter(csv_file, fieldnames=output_columns, + delimiter=self._config.get( + 'output_delimiter', ','), escapechar='\\', extrasaction='ignore', quotechar='"', - quoting=csv.QUOTE_NONNUMERIC) + quoting=csv.QUOTE_NONNUMERIC, + doublequote=False) writer.writeheader() num_output_events = 0 self._counters.set_counter('total', len(event_ids)) @@ -940,7 +1092,7 @@ def write_events_svobs(self, if not event: self._counters.add_counter('error_missing_event_for_id', 1, event_id) - logging.fatal(f'Unable to get event for {event_id}') + logging.debug(f'Unable to get event for {event_id}') continue event_dates = event.get_event_dates() if not event_dates: @@ -971,7 +1123,8 @@ def write_events_svobs(self, len(date_pvs), event_id) date_pvs['dcid'] = event_id date_pvs['observationDate'] = date - writer.writerow(date_pvs) + writer.writerow( + _format_property_values(date_pvs, digits=3)) self._counters.add_counter('processed', 1) # Track min/max counters for properties for prop, value in date_pvs.items(): @@ -984,15 +1137,18 @@ def write_events_svobs(self, self._counters.add_counter('output_events_with_svobs', 1) self._counters.max_counter('max_output_events_svobs_dates', num_output_dates) + output_files.append(output_csv) logging.info( f'Wrote {num_output_events} events into {output_csv} with columns: {output_columns}' ) - self.write_tmcf(utils.file_get_name(output_path, 'svobs', - '.tmcf'), output_columns, - {'typeOf': 'dcid:StatVarObservation'}, 'SVObs') + output_tmcf = self.write_tmcf( + file_util.file_get_name(output_path, 'svobs', '.tmcf'), + output_columns, {'typeOf': 'dcid:StatVarObservation'}, 'SVObs') + output_files.append(output_tmcf) self._counters.print_counters() + return output_files - def write_active_events(self, filename: str): + def write_active_events(self, filename: str) -> str: '''Save active events into a file.''' # Get a dict of all active events by id. active_events = {} @@ -1003,13 +1159,14 @@ def write_active_events(self, filename: str): active_events[event_id] = event.get_places() # Save the active events into a file. - utils.file_write_py_dict(active_events, filename) + file_util.file_write_py_dict(active_events, filename) self._counters.set_counter('active_events', len(active_events)) + return filename def read_active_events(self, filename: str): '''Load active events from a file.''' - _set_counter_stage(self._counters, 'load_active_events') - active_events = utils.file_load_py_dict(filename) + _set_counter_stage(self._counters, 'load_active_events_') + active_events = file_util.file_load_py_dict(filename) logging.info( f'Processing {len(active_events)} active events of size: {sys.getsizeof(active_events)} from file: {filename}' @@ -1034,29 +1191,216 @@ def read_active_events(self, filename: str): logging.info( f'Loaded {len(active_events)} events from file: {filename}') + def write_place_svobs_csv(self, place_date_pvs: dict, event_props: list, + output_path: str) -> str: + '''Returns the filename into which the svobs_pvs dict is written as CSV.''' + output_columns = [ + 'observationAbout', 'observationDate', 'observationPeriod' + ] + output_columns.extend(event_props) + output_csv = file_util.file_get_name(output_path, 'place_svobs', '.csv') + logging.info( + f'Writing {len(place_date_pvs)} place svobs with columns {output_columns} into {output_csv}' + ) + with file_util.FileIO(output_csv, 'w') as csv_file: + writer = csv.DictWriter(csv_file, + fieldnames=output_columns, + delimiter=self._config.get( + 'output_delimiter', ','), + escapechar='\\', + extrasaction='ignore', + quotechar='"', + quoting=csv.QUOTE_NONNUMERIC, + doublequote=False) + writer.writeheader() + + _set_counter_stage(self._counters, 'write_place_svobs_') + self._counters.set_counter('total', len(place_date_pvs)) + for place_date, pvs in place_date_pvs.items(): + self._counters.add_counter('processed', 1) + placeid, date = place_date.split(',', 1) + row_dict = { + 'observationAbout': placeid, + 'observationDate': date + } + # Get count of unique event ids. + if 'count' in event_props and 'EventId' in pvs: + row_dict['count'] = len(pvs['EventId']) + period = _get_observation_period_for_date(date) + if period: + row_dict['observationPeriod'] = period + # Get all other properties. + for prop in event_props: + if prop in pvs: + row_dict[prop] = pvs[prop] + writer.writerow(_format_property_values(row_dict, digits=3)) + return output_csv + + def write_place_svobs_tmcf(self, event_props: list, + output_path: str) -> str: + '''Returns the filename into which the tMCF for the SVObs for places + is generated. + + ArgsL + event_props: list of event properties for whcih SVObs are generated. + each property is converted into a statvar. + + Returns: + output tMCF filename with the reference to all columns in the SVObs csv + ''' + event_type = utils.strip_namespace( + self._config.get('event_type', 'FloodEvent')) + tmcf_nodes = [] + tmcf_prefix = 'EventPlaces' + format_config = self._config.get('property_config', + _DEFAULT_CONFIG.get('property_config')) + # Get common PVs for the statvars + # measuredProperty is set to each event_prop + default_statvar_pvs = self._config.get('default_statvar_pvs', { + 'typeOf': 'dcs:StatistcalVariable', + 'statType': 'measuredValue', + }) + if 'populationType' not in default_statvar_pvs: + default_statvar_pvs['populationType'] = event_type + + for prop in event_props: + if not prop[0].islower(): + # ignore invalid properties that don't begin with a lower case + continue + # Generate the statvar dcid with the event_prop as mProp + statvar_pvs = dict(default_statvar_pvs) + statvar_pvs['measuredProperty'] = prop + statvar_dcid = statvar_pvs.get('Node', statvar_pvs.get('dcid', '')) + if not statvar_dcid: + statvar_dcid = statvar_dcid_generator.get_statvar_dcid( + statvar_pvs) + + # Generate the tMCF node for the statvar referring to the prop + node = [] + node.append(f'Node: E:{tmcf_prefix}->E{len(tmcf_nodes)}') + node.append(f'typeOf: dcs:StatVarObservation') + node.append(f'variableMeasured: dcs:{statvar_dcid}') + node.append(f'observationAbout: C:{tmcf_prefix}->observationAbout') + node.append(f'observationDate: C:{tmcf_prefix}->observationDate') + node.append( + f'observationPeriod: C:{tmcf_prefix}->observationPeriod') + node.append(f'value: C:{tmcf_prefix}->{prop}') + # Add unit for property if needed. + unit = format_config.get(prop, {}).get('unit', '') + if unit: + node.append(f'unit: {unit}') + tmcf_nodes.append('\n'.join(node)) + output_tmcf = file_util.file_get_name(output_path, 'place_svobs', + '.tmcf') + logging.info( + f'Writing tmcf with {len(tmcf_nodes)} nodes for place svobs columns {event_props} into {output_tmcf}' + ) + with file_util.FileIO(output_tmcf, 'w') as tmcf_file: + tmcf_file.write('\n\n'.join(tmcf_nodes)) + return output_tmcf + + def write_events_place_svobs( + self, + output_path: str, + event_ids: list = None, + event_props: list = ['area', 'count'], + date_formats: list = ['YYYY-MM-DD', 'YYYY-MM', 'YYYY']) -> list: + '''Returns a list of generated CSV/tMCF files with SVObs for + the affected places of events. + + It aggregates event properties by place,date for all affected places + and generates SVObs for each property in event_props with observationAbout as + the place. + + If a list of date_formats are given, it also aggregates properties + for each place across all dates in the time period, such as month or year + using the property aggregation settings in 'property_config_across_dates'. + + If aggregate_by_contained_in_place is set in the config, + the event porperties are also aggregated across all parent places for + all dates using the property aggregation settings in config + 'property_config_across_dates'. + + Args: + output_path: string file prefix for output files. + It is combined with a suffix such as 'place_svobs.csv', 'place_svobs.tmcf' + event_ids: A list of event ids to be processed into the output files. + event_props: List of event properties for which SVObs are generated. + properties that being with a Capital letter are considered internal + and are ignored in the output. + date_formats: List of date formats, such as , 'YYYY' for year, + 'YYYY-MM' for months into whcih properties are aggregated. + + Returns: + a list of filenames for CSV and tMCF generated. + ''' + if not event_ids: + event_ids = self.get_all_event_ids() + logging.info( + f'Generating place svobs for {len(event_ids)} events for dates: {date_formats}' + ) + + # Aggregation settings for event properties across places for a date. + property_config_per_date = { + 'aggregate': 'sum', + 'area': { + 'aggregate': 'sum' + }, + 'EventId': { + 'aggregate': 'set' + } + } + property_config_per_date.update( + self._config.get('property_config_per_date', {})) + + # Collect data for each event place and date + # as a dict: {(place, date): {'area': NN},... } + place_date_pvs = self.get_place_date_output_properties( + event_ids, event_props) + + # Aggregate property values by place across time periods + self.aggregate_by_time_period(place_date_pvs, date_formats) + + # Aggregate by parent places + if self._config.get('aggregate_by_contained_in_place', False): + self.aggregate_by_contained_in_place(place_date_pvs) + + output_files = [] + # Write the place svobs. + output_files.append( + self.write_place_svobs_csv(place_date_pvs, event_props, + output_path)) + + # Generate tmcf for place svobs. + output_files.append( + self.write_place_svobs_tmcf(event_props, output_path)) + return output_files + def process_csv(self, csv_files: list, output_path: str, input_events_file: str = None, output_active_events_path: str = None, - output_active_events_state: str = None): + output_active_events_state: str = None) -> list: '''Process CSV files with data for places into events. Places can be s2 cells or grids with lat/lng. ''' if input_events_file: self.read_active_events(input_events_file) _set_counter_stage(self._counters, 'process_csv_') - input_files = utils.file_get_matching(csv_files) + input_files = file_util.file_get_matching(csv_files) for filename in input_files: - self._counters.add_counter('total', - utils.file_estimate_num_rows(filename)) + self._counters.add_counter( + 'total', file_util.file_estimate_num_rows(filename)) logging.info( f'Processing data from files: {input_files} with config: {self._config.get_configs()}' ) for filename in input_files: logging.info(f'Processing csv data file: {filename}') - with open(filename) as csvfile: - reader = csv.DictReader(csvfile) + with file_util.FileIO(filename) as csvfile: + reader = csv.DictReader(csvfile, + delimiter=self._config.get( + 'input_delimiter', ',')) if len(self._event_props) <= 1: # No event properties from config. Add all input properties. self._event_props.update(reader.fieldnames) @@ -1070,7 +1414,7 @@ def process_csv(self, break self._counters.add_counter(f'csv_rows-{filename}', 1) self._counters.add_counter('processed', 1) - self.process_event_data(input_row) + self.process_event_data(input_row, filename, num_rows) # Deactivate old events before moving to next CSV file. # Assumes event files are in increasing order by date. self.deactivate_old_events(self.get_active_event_ids(), @@ -1078,11 +1422,16 @@ def process_csv(self, logging.info( f'Created {len(self._event_by_id)} events for {num_rows} rows from file: {filename}' ) - self.output_events(output_path, output_active_events_path, - output_active_events_state) + output_files = self.output_events(output_path, + output_active_events_path, + output_active_events_state) self.save_place_cache_file() + return output_files - def process_event_data(self, data: dict) -> bool: + def process_event_data(self, + data: dict, + filename: str = '', + row_index: int = 0) -> bool: '''Process an input event with a dictionary of properties. The event is added to existing events or a new event is created if it is valid. Args: @@ -1098,16 +1447,18 @@ def process_event_data(self, data: dict) -> bool: if not place_id: self._counters.add_counter('input_dropped_invalid_placeid', 1) return False - data_pvs['affectedPlace'] = place + data_pvs['affectedPlace'] = utils.add_namespace(place) + if place_id != place: + data_pvs['affectedPlace'] += ',' + utils.add_namespace(place_id) date_column = self._config.get('date_column', 'observationDate') date = row.get(date_column, '') if not date: self._counters.add_counter('error_input_rows_missing_date', 1) - logging.error(f'Missing date in row:{filename}:{num_rows}:{row}') + logging.error(f'Missing date in row:{filename}:{row_index}:{row}') return False if date < self._max_date: self._counters.add_counter('error_input_rows_date_out_of_order', 1) - logging.error(f'Old date in row:{filename}:{num_rows}:{row}') + logging.error(f'Old date in row:{filename}:{row_index}:{row}') return False prev_date = date for p in self._event_props: @@ -1119,7 +1470,9 @@ def process_event_data(self, data: dict) -> bool: data_pvs[p] = row[p] # Compute area if required. if 'area' in self._event_props and 'area' not in data_pvs: - area = utils.place_area(place_id) + area = utils.place_area(place) + if not area: + area = utils.place_area(place_id) if area > 0: data_pvs['area'] = area # Check if row passes input filters. @@ -1130,21 +1483,31 @@ def process_event_data(self, data: dict) -> bool: self._counters.add_counter('input_dropped_by_filter', 1) return False self._counters.add_counter('events_added', 1) + self._counters.set_counter('num_events', len(self._event_by_id)) return True def get_place_id_for_event(self, place_id: str) -> str: '''Returns the place_id for the event data.''' - if not utils.is_grid_id(place_id) and self._config.get( - 'convert_place_to_grid', False): + output_place_type = self._config.get('convert_place_to_grid', '') + if output_place_type: # Converting a non-grid place to a grid_1 place. # Multiple places mapping to same grid will be # aggregated using 'property_config_per_date'. lat, lng = self._get_place_lat_lng(place_id) if lat is not None and lng is not None: # Got a location. Convert it to a grid. - grid_id = utils.grid_id_from_lat_lng(1, int(lat), int(lng)) - place_id = grid_id - self._counters.add_counter(f'place_converted_to_grid_1', 1) + if (output_place_type + == 'grid_1') and (not utils.is_grid_id(place_id)): + grid_id = utils.grid_id_from_lat_lng(1, int(lat), int(lng)) + place_id = grid_id + self._counters.add_counter(f'place_converted_to_grid_1', 1) + elif (output_place_type + == 's2_10') and (not utils.is_s2_cell_id(place_id)): + s2cell_id = utils.s2_cell_to_dcid( + utils.s2_cell_from_latlng(lat, lng, 10)) + place_id = s2cell_id + self._counters.add_counter(f'place_converted_to_s2_level10', + 1) else: self._counters.add_counter(f'place_without_lat_lng', 1) if utils.is_s2_cell_id(place_id): @@ -1166,7 +1529,8 @@ def get_place_id_for_event(self, place_id: str) -> str: def output_events(self, output_path: str, output_active_events_path: str = None, - output_active_events_state: str = None): + output_active_events_state: str = None) -> list: + output_files = [] # Output all ended events output_ended_events = False if output_active_events_path: @@ -1175,12 +1539,24 @@ def output_events(self, output_ended_events = True if self._config.get('output_events', True): _set_counter_stage(self._counters, 'emit_events_csv_') - self.write_events_csv(output_path=output_path, - output_ended_events=output_ended_events) + output_files.append( + self.write_events_csv(output_path=output_path, + output_ended_events=output_ended_events)) if self._config.get('output_svobs', False): _set_counter_stage(self._counters, 'emit_events_svobs_') - self.write_events_svobs(output_path=output_path, - output_ended_events=output_ended_events) + output_files.extend( + self.write_events_svobs( + output_path=output_path, + output_ended_events=output_ended_events)) + if self._config.get('output_place_svobs', False): + output_files.extend( + self.write_events_place_svobs( + output_path=output_path, + event_props=self._config.get( + 'output_place_svobs_properties', ['area', 'count']), + date_formats=self._config.get( + 'output_place_svobs_dates', + ['YYYY-MM-DD', 'YYYY-MM', 'YYYY']))) # Output active events into a separate set of files. active_event_ids = self.get_active_event_ids(self._max_date) self._counters.set_counter('active_events', len(active_event_ids)) @@ -1188,19 +1564,24 @@ def output_events(self, logging.info( f'Emitting {len(active_event_ids)} active events into: {output_active_events_path}' ) - if self._config.get('output_active_events', True): + if self._config.get('output_active_events', False): _set_counter_stage(self._counters, 'emit_active_events_csv_') - self.write_events_csv(output_path=output_active_events_path, - event_ids=active_event_ids, - output_ended_events=False) + output_files.append( + self.write_events_csv(output_path=output_active_events_path, + event_ids=active_event_ids, + output_ended_events=False)) if self._config.get('output_active_svobs', False): _set_counter_stage(self._counters, 'emit_active_events_svobs_') - self.write_events_svobs(output_path=output_active_events_path, - event_ids=active_event_ids, - output_ended_events=False) + output_files.extend( + self.write_events_svobs( + output_path=output_active_events_path, + event_ids=active_event_ids, + output_ended_events=False)) if output_active_events_state: _set_counter_stage(self._counters, 'emit_active_events_data_') - self.write_active_events(output_active_events_state) + output_files.append( + self.write_active_events(output_active_events_state)) + return output_files def _get_date_with_interval(self, date: str) -> str: '''Returns the date with the interval 'max_event_interval_days' applied.''' @@ -1208,23 +1589,24 @@ def _get_date_with_interval(self, date: str) -> str: return date interval_days = timedelta( days=self._config.get('max_event_interval_days', 30)) - min_date = date + min_date = _get_full_date(date) try: - min_date = (parser.parse(date) - interval_days).isoformat() + min_date = (parser.parse(min_date) - interval_days).isoformat() except parser._parser.ParserError: - logging.error(f'Unable to parse date: "{date}"') + logging.error(f'Unable to parse date: "{min_date}"') self._counters.add_counter('error_input_rows_invalid_date', 1) min_date = date return min_date - def _get_contained_for_place(self, place_id: int) -> list: + def _get_contained_for_place(self, place_id: str) -> list: '''Returns a list of containdInPlace dcids for a place.''' new_places = set({place_id}) parent_places = set() # Lookup parent places for all parents. while len(new_places) > 0: placeid = new_places.pop() - new_parents = self.get_place_property(placeid, 'containedInPlace') + new_parents = self.get_place_property_list(placeid, + 'containedInPlace') if not new_parents: # No containedInPlace for place. # Lookup place by lat/lng. @@ -1236,23 +1618,22 @@ def _get_contained_for_place(self, place_id: int) -> list: new_parents = [f'country/{suffix}'] elif placeid in self._latlng_to_place_cache: self._counters.add_counter('latlng_place_cache_hits', 1) - new_parents = self._latlng_to_place_cache[placeid].split( - ',') + new_parents = self._latlng_to_place_cache[placeid] elif self._config.get('lookup_contained_for_place', False): - lat, lng = utils.placeid_to_lat_lng( + lat, lng = utils.place_id_to_lat_lng( placeid, self._config.get('dc_api_enabled', True)) - geo_ids = self._ll2p.resolve(lat, lng) - self._latlng_to_place_cache[placeid] = geo_ids - self._counters.add_counter('latlng_place_lookups', 1) + if lat is not None and lng is not None: + new_parents = self._ll2p.resolve(lat, lng) + self._latlng_to_place_cache[placeid] = new_parents + self._counters.add_counter('latlng_place_lookups', 1) + new_parents = _get_list(new_parents) if new_parents: - # Get a list of place ids splitting comma separated strings. - new_parents = ','.join(new_parents).split(',') + # Collect all new parent places to be looked up again. for new_place in new_parents: - if new_place not in parent_places: + if new_place and new_place not in parent_places: new_places.add(new_place) parent_places.add(new_place) - parent_places.add('Earth') - contained_places = list(parent_places) + contained_places = sorted(list(parent_places)) self.set_place_property(place_id, 'containedInPlace', contained_places) return contained_places @@ -1264,7 +1645,7 @@ def _get_event_name(self, event_pvs: dict, locations: list = None) -> str: # Get a named location for the event start_location = event_pvs.get('startLocation') if not locations: - locations = event_pvs.get('affectedPlace', '').split(',') + locations = _get_list(event_pvs.get('affectedPlace', '')) location_name = '' for placeid in locations: placeid = utils.strip_namespace(placeid) @@ -1317,9 +1698,8 @@ def _set_event_places(self, event: GeoEvent, data: dict): # TODO: Create a property for containedInPlaces for Events # Until then affectedPlace is used for place aggregation. # data['affectedPlace'] = ','.join(affected_places) - data['affectedPlace'] = ','.join(contained_places) + data['affectedPlace'] = ','.join(sorted(contained_places)) data['AffectedPlaceCount'] = len(affected_places) - data['ContainedInPlaceCount'] = len(contained_places) self._counters.max_counter('max_output_events_places', len(place_ids)) def _get_place_lat_lng(self, placeid: str) -> (float, float): @@ -1364,11 +1744,16 @@ def _first(s: set): return item -def _format_property_values(pvs: dict, config: dict) -> dict: +def _format_property_values(pvs: dict, + config: dict = {}, + digits: int = 5) -> dict: '''Returns a set of properties with formatted values.''' fmt_pvs = {} for prop, value in pvs.items(): fmt_value = value + if isinstance(value, float): + # Round floats to 5 decimal places + fmt_value = round(value, digits) prop_config = config.get(prop, None) if prop_config: prop_unit = prop_config.get('unit', None) @@ -1382,8 +1767,20 @@ def _reset_counter_stage(counters: Counters, stage_name: str): counters.reset_process_stage(stage_name) +def _get_full_date(date_str: str) -> str: + parts = date_str.count('-') + if parts == 0: + # Add month to date + return date_str + '-01-01' + if parts == 1: + # Add day to date + return date_str + '-01' + return date_str + + def _get_dates_duration(start_date: str, end_date: str) -> int: - return (parser.parse(end_date) - parser.parse(start_date)).days + 1 + return (parser.parse(_get_full_date(end_date)) - + parser.parse(_get_full_date(start_date))).days + 1 def _get_place_neighbors_ids(place_id: str) -> list: @@ -1404,6 +1801,25 @@ def _is_valid_property(prop: str) -> bool: return True +def _get_date_by_format(date_str: str, date_format: str) -> str: + '''Returns the date in the given format, YYYY-MM or YYYY.''' + date_tokens = date_str.split('-') + num_tokens = date_format.count('-') + 1 + if num_tokens > len(date_tokens): + return None + return '-'.join(date_tokens[:num_tokens]) + + +def _get_observation_period_for_date(date_str: str) -> str: + '''Returns the observation period for date string.''' + date_parts = date_str.count('-') + if date_parts == 0: + return 'P1Y' + if date_parts == 1: + return 'P1M' + return '' + + def _set_counter_stage(counters: Counters, name: str): '''Set the counter prefix to the stage.''' counter_prefix = counters.get_prefix() @@ -1415,24 +1831,50 @@ def _set_counter_stage(counters: Counters, name: str): counters.set_prefix(f'{stage_count}:{name}') +def _get_list(items: str) -> list: + '''Returns a list of unique items, splitting comma separated strings.''' + items_set = set() + if items: + if isinstance(items, str): + items = items.split(',') + for item in items: + items_set.update(item.split(',')) + return sorted(items_set) + + +_DEFAULT_CONFIG = {} + + +def get_default_config() -> dict: + '''Returns dictionary with the default config GeoEventsProcessor + from event_config.py. + ''' + global _DEFAULT_CONFIG + if not _DEFAULT_CONFIG: + # Load default config from event_config.py + _DEFAULT_CONFIG = file_util.file_load_py_dict( + os.path.join(os.path.dirname(__file__), 'event_config.py')) + return _DEFAULT_CONFIG + + def process(csv_files: list, output_path: str, input_events_file: str = None, output_active_events_path: str = None, output_active_events_state: str = None, - config: ConfigMap = None): + config: ConfigMap = None) -> list: counters = Counters() if config is None: - config = ConfigMap(config_dict=_DEFAULT_CONFIG) + config = ConfigMap(config_dict=get_default_config()) events_processor = GeoEventsProcessor(config, counters) - events_processor.process_csv(csv_files, output_path, input_events_file, - output_active_events_path, - output_active_events_state) + return events_processor.process_csv(csv_files, output_path, + input_events_file, + output_active_events_path, + output_active_events_state) def main(_): - _DEBUG = _FLAGS.debug - if _DEBUG: + if _FLAGS.debug: logging.set_verbosity(2) #if _FLAGS.pprof_port > 0: # Enable pprof server. diff --git a/scripts/earthengine/process_events_test.py b/scripts/earthengine/process_events_test.py index 9efb814d99..a01f37691e 100644 --- a/scripts/earthengine/process_events_test.py +++ b/scripts/earthengine/process_events_test.py @@ -31,6 +31,7 @@ sys.path.append(os.path.dirname(os.path.dirname((_MODULE_DIR)))) import utils +import file_util _TESTDIR = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'test_data') @@ -52,8 +53,8 @@ def compare_files(self, expected: str, actual: str): file, ext = os.path.splitext(expected) if ext == '.csv': self.compare_csv_files(expected, actual) - with open(expected, 'r') as exp: - with open(actual, 'r') as act: + with file_util.FileIO(expected, 'r') as exp: + with file_util.FileIO(actual, 'r') as act: exp_lines = sorted(exp.readlines()) act_lines = sorted(act.readlines()) self.assertEqual(exp_lines, act_lines) @@ -89,7 +90,6 @@ def compare_csv_files(self, def test_process(self): with tempfile.TemporaryDirectory() as tmp_dir: - tmp_dir = '/tmp' output_prefix = os.path.join(tmp_dir, 'events_test_') test_prefix = os.path.join(_TESTDIR, 'sample_floods_') # Process flood s2 cells into events. @@ -99,7 +99,12 @@ def test_process(self): config=self._config) # Verify generated events. for file in [ - 'events.csv', 'events.tmcf', 'svobs.csv', 'svobs.tmcf' + 'events.csv', + 'events.tmcf', + 'svobs.csv', + 'svobs.tmcf', + 'place_svobs.csv', + 'place_svobs.tmcf', ]: if file.endswith('.csv'): # compare csv output without geoJson that is not deterministic diff --git a/scripts/earthengine/raster_to_csv.py b/scripts/earthengine/raster_to_csv.py index c85550f8b2..0002f7d23f 100644 --- a/scripts/earthengine/raster_to_csv.py +++ b/scripts/earthengine/raster_to_csv.py @@ -70,18 +70,21 @@ sys.path.append(_SCRIPTS_DIR) sys.path.append(os.path.dirname(_SCRIPTS_DIR)) sys.path.append(os.path.dirname(os.path.dirname(_SCRIPTS_DIR))) +sys.path.append( + os.path.join(os.path.dirname(os.path.dirname(_SCRIPTS_DIR)), 'util')) +import common_flags +import file_util import utils -from util.config_map import ConfigMap -from util.counters import Counters, CounterOptions +from config_map import ConfigMap +from counters import Counters, CounterOptions flags.DEFINE_string('input_geotiff', '', 'GeoTIFF file to process') flags.DEFINE_string('ignore_geotiff', '', 'GeoTIFF with points to be ignored set as data.') flags.DEFINE_string('allow_geotiff', '', 'GeoTIFF with points to be used set as data.') -flags.DEFINE_string('input_csv', '', 'CSV file to process') flags.DEFINE_string('ignore_csv', '', 'CSV with points to be ignored set as data.') flags.DEFINE_string('allow_csv', '', 'CSV with points to be used set as data.') @@ -103,86 +106,88 @@ 'Levels to be added as contained in place nodes into s2 place output.') flags.DEFINE_string('aggregate', 'max', 'Aggregate function for data values with same key.') -flags.DEFINE_bool('debug', False, 'Enable debug logs.') flags.DEFINE_integer('log_every_n', 10000, 'Print logs every N records.') flags.DEFINE_float('default_cell_area', 0, 'Area of the cell if the raster input is not provided.') -flags.DEFINE_string('config', '', 'Config dictionary with parameter settings.') _FLAGS = flags.FLAGS _FLAGS(sys.argv) # Allow invocation without app.run() -_DEFAULT_CONFIG = { - # Inputs - 'input_geotiff': _FLAGS.input_geotiff, - 'ignore_geotiff': _FLAGS.ignore_geotiff, - 'allow_geotiff': _FLAGS.allow_geotiff, - 'input_csv': _FLAGS.input_csv, - 'ignore_csv': _FLAGS.ignore_csv, - 'allow_csv': _FLAGS.allow_csv, - 'limit_points': _FLAGS.limit_points, - - # Output settings - 'output_csv': _FLAGS.output_csv, - 'output_mode': _FLAGS.output_mode, - 'output_columns': _FLAGS.output_columns, - 'output_date': _FLAGS.output_date, - 'output_precision': _FLAGS.output_precision, - 'output_s2_place': _FLAGS.output_s2_place, - 'output_contained_s2_level': _FLAGS.output_contained_s2_level, - - # Processing parameters - 's2_level': _FLAGS.s2_level, - # default aggregation for data values mapped to the same s2-cell+date - # that can be one of: min, max, mean, sum. - # For columns specific aggregation methods, use config:'input_data_filter'. - 'aggregate': _FLAGS.aggregate, - # generate data for all s2 cells from --s2_level upto this level. - # Default cell area if constant for the whole data set. - 'default_cell_area': _FLAGS.default_cell_area, - # Default point/cell width/height for ~1sqkm at equator, lower near poles. - 'default_cell_width': 0.009, - 'default_cell_height': 0.009, - # rename columns : - 'rename_columns': { - 'acq_date': 'date', - 'band:0': 'water', - }, - - # filter settings per column for data - # input (pre-aggregation) and output (post-aggregation) of the form: - # { - # '' : { - # 'min': , # Minimum value for - # 'max': , # Maximum value for - # 'aggregate': 'sum', # one of 'min','max','sum','mean' - # }, - # ... - # } - 'input_data_filter': { - # Add up area for points added to an s2cell. - 'area': { - 'aggregate': 'sum', + +def get_default_config(): + # Create config from command line flags. + return { + # Inputs + 'input_geotiff': _FLAGS.input_geotiff, + 'ignore_geotiff': _FLAGS.ignore_geotiff, + 'allow_geotiff': _FLAGS.allow_geotiff, + 'input_csv': _FLAGS.input_csv, + 'ignore_csv': _FLAGS.ignore_csv, + 'allow_csv': _FLAGS.allow_csv, + 'limit_points': _FLAGS.limit_points, + + # Output settings + 'output_csv': _FLAGS.output_csv, + 'output_mode': _FLAGS.output_mode, + 'output_columns': _FLAGS.output_columns, + 'output_date': _FLAGS.output_date, + 'output_precision': _FLAGS.output_precision, + 'output_s2_place': _FLAGS.output_s2_place, + 'output_contained_s2_level': _FLAGS.output_contained_s2_level, + + # Processing parameters + 's2_level': _FLAGS.s2_level, + # default aggregation for data values mapped to the same s2-cell+date + # that can be one of: min, max, mean, sum. + # For columns specific aggregation methods, use config:'input_data_filter'. + 'aggregate': _FLAGS.aggregate, + # generate data for all s2 cells from --s2_level upto this level. + # Default cell area if constant for the whole data set. + 'default_cell_area': _FLAGS.default_cell_area, + # Default point/cell width/height for ~1sqkm at equator, lower near poles. + 'default_cell_width': 0.009, + 'default_cell_height': 0.009, + # rename columns : + 'rename_columns': { + 'acq_date': 'date', + 'band:0': 'water', }, - #'confidence': { - # 'regex': r'[nh]', # pick normal or high - #} - # 'water': { # band:0 - # 'min': 1.0 - #}, - }, - 'output_data_filter': { - # 'area': { - # 'min': 1.0, # Minimum area in sqkm after aggregation + + # filter settings per column for data + # input (pre-aggregation) and output (post-aggregation) of the form: + # { + # '' : { + # 'min': , # Minimum value for + # 'max': , # Maximum value for + # 'aggregate': 'sum', # one of 'min','max','sum','mean' # }, - }, + # ... + # } + 'input_data_filter': { + # Add up area for points added to an s2cell. + 'area': { + 'aggregate': 'sum', + }, + #'confidence': { + # 'regex': r'[nh]', # pick normal or high + #} + # 'water': { # band:0 + # 'min': 1.0 + #}, + }, + 'output_data_filter': { + # 'area': { + # 'min': 1.0, # Minimum area in sqkm after aggregation + # }, + }, + + # Debug settings + 'debug': _FLAGS.debug, # Enable debug logs + 'log_every_n': + _FLAGS.log_every_n, # Show counters when counter increments by N + 'log_every': 'processed_points', # Counter to check for log_every_n + } - # Debug settings - 'debug': _FLAGS.debug, # Enable debug logs - 'log_every_n': - _FLAGS.log_every_n, # Show counters when counter increments by N - 'log_every': 'processed_points', # Counter to check for log_every_n -} _DEFAULT_COLUMNS = set({'latitude', 'longitude', 's2CellId', 'date'}) @@ -463,6 +468,9 @@ def load_raster_geotiff(filename: str) -> rasterio.io.DatasetReader: raster data set for the file. ''' logging.info(f'Loading raster GeoTiff File: {filename}') + if file_util.file_is_gcs(filename): + # RasterIO doesn't support GCS files. Copy over to a local file. + filename = file_util.file_copy(filename) src = rasterio.open(filename) _log_raster_info(src) return src @@ -516,7 +524,7 @@ def write_data_csv(data_points: dict, if not os.path.exists(filename): # File doesn't exist yet. Open in write mode and add column headers. output_mode = 'w' - with open(filename, mode=output_mode) as csv_file: + with file_util.FileIO(filename, mode=output_mode) as csv_file: writer = csv.DictWriter(csv_file, fieldnames=columns, escapechar='\\', @@ -598,7 +606,7 @@ def write_s2place_csv_tmcf(data_points: dict, place_tmcf.append('typeOf: C:Place->typeOf') place_tmcf.append('containedInPlace: C:Place->containedInPlace') place_tmcf.append('name: C:Place->name') - with open(f'{output_prefix}.tmcf', 'w') as tmcf_file: + with file_util.FileIO(f'{output_prefix}.tmcf', 'w') as tmcf_file: tmcf_file.write('\n'.join(place_tmcf)) tmcf_file.write('\n') @@ -815,15 +823,15 @@ def process_csv_points(input_csv: str, logging.info( f'Loaded {len(allow_points)} allow points from {allow_csv}') data_filter = config.get('input_data_filter', {}) - input_csv_files = utils.file_get_matching(input_csv) + input_csv_files = file_util.file_get_matching(input_csv) logging.info(f'Processing csv files: {input_csv_files}') counter.set_prefix('1:process_csv:') for filename in input_csv_files: counter.add_counter('total_points', - utils.file_estimate_num_rows(filename)) + file_util.file_estimate_num_rows(filename)) for filename in input_csv_files: counter.add_counter('input_csv_files', 1) - with open(filename) as csvfile: + with file_util.FileIO(filename) as csvfile: logging.info(f'Processing data from file {filename} ...') reader = csv.DictReader(csvfile) # Save the input columns @@ -912,7 +920,7 @@ def process(input_geotiff: str, logging.info( f'Processing raster {input_geotiff} with config: {config.get_configs()}' ) - for geotiff_file in utils.file_get_matching(input_geotiff): + for geotiff_file in file_util.file_get_matching(input_geotiff): process_raster(geotiff_file, config, data_points, counter) if input_csv: logging.info( @@ -983,7 +991,7 @@ def _log_raster_info(raster: rasterio.io.DatasetReader): def main(_): - config = ConfigMap(filename=_FLAGS.config, config_dict=_DEFAULT_CONFIG) + config = ConfigMap(filename=_FLAGS.config, config_dict=get_default_config()) if config.get('debug', False): logging.set_verbosity(2) process(_FLAGS.input_geotiff, _FLAGS.input_csv, _FLAGS.output_csv, config) diff --git a/scripts/earthengine/run.sh b/scripts/earthengine/run.sh deleted file mode 100755 index 2fa1094f12..0000000000 --- a/scripts/earthengine/run.sh +++ /dev/null @@ -1,343 +0,0 @@ -#!/bin/bash -# Script to get EarthEngine images -# It calls earthengine_image.py to extract image from EarthEngine to GCS -# and then downloads the files fomr GCS locally. -# See USAGE below. -# -# Dependancies: -# The following packeges are assumed to be installed: -# earthengine: Python package to manage EarthEngine assets and API -# Install with `pip install earthengine-api --upgrade` -# google-cloud-sdk or gsutil: tools to manage files on GCS -# Install with `sudo apt-get install google-cloud-sdk` - -# Defaults -GCS_PROJECT= # Must be provided on command line with '-p ' -GCS_BUCKET=${GCS_BUCKET:-"earth_engine_exports"} -GCS_FOLDER=${GCS_FOLDER:-$(basename $(dirname $0))} -TMP_DIR=${TMP_DIR:-"tmp"} -OUTPUT_PREFIX="ee_image_" -START_DATE=$(date -d "-1 Month" +%Y-%m-01) # Start of last month -TIME_PERIOD="P1M" -COUNT=1 -PARALLELISM=10 -# Default command line options for earthenging_image.py -FLAGS="--ee_mask=land" -FLAGS="$FLAGS --ee_dataset=dynamic_world" -FLAGS="$FLAGS --band=water --band_min=0.7 --ee_reducer=max" -USAGE="Script to launch earth engine tasks to extract geoTIFF images. -Usage: $(basename $0) -g [Options] - -Options: - -g GCS project for expoering images to cloud. - -b GCS bucket within the project for images. - Bucket can be created with 'gsutil mb gs:///' - -d Output directory in GCS for extracted images. - -e Name of the EarthEngine dataset defined in config. - -o Output file prefix for images extracted. - -od Local output directory for images and CSVs. - Default: $TMP_DIR/ - -date Date to be added into the csv. - Default: Date is extracted from the start date '-st <...>' - -oi Process images into csv. - If specified, ee tasks are not created. - -st Start date used to filter for images in a collection. - Default: last month ($START_DATE) - -p [MD] Time period over which to aggregate data. - For example: '1M' for 1 month. - -n Number of images to extract starting from start_date - at intervals of the time period. - -m Number of parallel tasks to run. Default: $PARALLELISM - --= Additional flags for the scripts earthengine_image.py - and raster_to_csv.py. - Default: $FLAGS - -w [,task2] Wait for EE tasks to complete. -" -EE_INTERVAL=60 -SCRIPT_DIR=$(dirname $0) -# Default flags for raster to csv processing -#DEFAULT_FLAGS_PROCESS="--s2_level=13 --aggregate_s2_level=10 --contained_in_s2_level=10" -DEFAULT_FLAGS_PROCESS="" - -function echo_log { - local msg="[$(date)]: $@" - if [[ -z "$QUIET" ]]; then - echo "$msg" 2>&1 - fi - if [[ -n $LOG ]]; then - echo "$msg" >> $LOG - fi -} - -function parse_options { - ARGS="$@" - while (( $# > 0 )); do - case $1 in - -g) shift; GCS_PROJECT="$1";; - -d) shift; GCS_FOLDER="$1";; - -o) shift; OUTPUT_PREFIX="$1";; - -od) shift; OUTPUT_DIR="$1";; - -da*) shift; OUTPUT_DATE="$1";; - -oi) shift; IMAGE_OUTPUTS="$IMAGE_OUTPUTS $1";; - -e) shift; EE_DATASET="$1";; - -st*) shift; START_DATE="$1";; - -p) shift; TIME_PERIOD="$1";; - -n) shift; COUNT=$1;; - -t) shift; TMP_DIR="$1";; - -w) shift; EE_TASKS="$EE_TASKS $1";; - -h) echo "$USAGE" >&2; exit 1;; - -x) set -x;; - --*) FLAGS="$FLAGS $1";; - esac - shift - done - setup $args -} - -function setup { - # Setup tmp directory - mkdir -p $TMP_DIR - LOG=$TMP_DIR/ee-process-$(date +%Y%m%d-%H%M%S).log - echo_log "Invoked command: $ARGS" - - # Setup local output directory - OUTPUT_DIR=${OUTPUT_DIR:-"$TMP_DIR/$GCS_FOLDER"} - mkdir -p $OUTPUT_DIR - - # Set flags - if [[ -n "$EE_DATASET" ]]; then - FLAGS="$FLAGS --ee_dataset=$EE_DATASET" - fi - # Add --undefok to allow FLAGS across multiple scripts. - local flags=$(echo $FLAGS | egrep -o "\-\-([A-Za-z_]*)" | sed -e 's/--//g;s/ /,/g') - FLAGS="$FLAGS --undefok=$(echo $flags | sed -e 's/ /,/g')" -} - -function setup_ee { - # Check if GCS_PROJECT is set. - if [[ -z "$GCS_PROJECT" ]]; then - echo "ERROR: Set GCS project with '-g '" >&2 - exit 1; - fi - - # Authenticate with earthengine - local ee_bin=$(which earthengine) - if [[ -z "$ee_bin" ]]; then - echo "ERROR: Unable to find 'earthengine' in PATH:$PATH. -Install with 'pip install earthengine-api --upgrade'" >&2 - exit 1; - fi - if [[ -z "$ee_auth_status" ]]; then - earthengine task list >& /dev/null - ee_auth_status=$? - if [[ $ee_auth_status != 0 ]]; then - echo "Authenticating with 'earthengine authenticate'" - earthengine authenticate - ee_auth_status=$? - if [[ $ee_auth_status != 0 ]]; then - echo "TIP: If running on a remote machine try 'earthengine authenticate --quiet'" >&2 - exit 1; - fi - fi - fi -} - - -# Run the EE image script. -# Returns the task ids of all tasks launched if successfull. -function run_ee_image { - log="$TMP_DIR/ee_image-$(date +%Y%m%d-$H%M%S).log" - cmd="python3 $SCRIPT_DIR/earthengine_image.py \ - --gcs_project=$GCS_PROJECT \ - --gcs_bucket=$GCS_BUCKET \ - --gcs_folder=$GCS_FOLDER \ - --start_date=$START_DATE \ - --time_period=$TIME_PERIOD \ - --ee_image_count=$COUNT \ - $FLAGS" - echo_log "Running command: $cmd" - $cmd 2>&1 | tee $log - cat $log >> $LOG - local tasks=$(grep -o " $ee_tasks_log - completed_tasks=$(egrep "$tasks_pat" $ee_tasks_log | egrep "COMPLETED" |\ - egrep -o "^[^ ]*") - for task in $completed_tasks; do - is_processing=$(echo "$PROCESSING_TASKS" | grep $task) - if [[ -z "$is_processing" ]]; then - PROCESSING_TASKS="$PROCESSING_TASKS $task" - get_ee_task_image $task & - sleep_while_active $PARALLELISM - fi - done - remaining_tasks=$(egrep "$tasks_pat" $ee_tasks_log | egrep "READY|RUNNING") - if [[ -n "$remaining_tasks" ]]; then - echo_log "Waiting for tasks: -$remaining_tasks" - sleep $EE_INTERVAL - fi - done - egrep "$tasks_pat" $ee_tasks_log -} - -# Download output of a task -function get_ee_task_image { - local task="$1"; shift - task_info=$(earthengine task info $task) - if [[ -n "$task_info" ]]; then - echo_log "Fetching output for task: $task_info" - has_completed=$(echo "$task_info" | grep "COMPLETED") - if [[ -z "$has_completed" ]]; then - echo_log "ERROR: Task $task not successful" - echo_log "$task_info" - return - fi - output_prefix=$(echo "$task_info" | grep Description | sed -e 's/.*Description: //') - output_uri=$(echo "$task_info" | grep "Destination URIs" | - sed -e 's,.*google.com/storage/browser/,,;') - echo_log "Copying files gs://${output_uri}${output_prefix}* to $OUTPUT_DIR" - gsutil -m cp gs://${output_uri}${output_prefix}* $OUTPUT_DIR - echo_log "Copied image files: -$(ls -l $OUTPUT_DIR/${output_prefix}*)" - # IMAGE_OUTPUTS="$IMAGE_OUTPUTS $OUTPUT_DIR/${output_prefix}" - process_image $OUTPUT_DIR/${output_prefix} - fi -} - -# Launch EE tasks for all images in the time period. -function get_all_ee_images { - setup_ee - if [[ -z "$EE_TASKS" ]]; then - # No EE tasks, launch them. - run_ee_image - fi - wait_ee_tasks $EE_TASKS - # Process images from any remaining tasks. - for task in $EE_TASKS; do - is_processing=$(echo "$PROCESSING_TASKS" | grep $task) - if [[ -z "$is_processing" ]]; then - PROCESSING_TASKS="$PROCESSING_TASKS $task" - get_ee_task_image $task & - sleep_while_active $PARALLELISM - fi - done - echo_log "Got images: $IMAGE_OUTPUTS" -} - -# Get the number of jobs in the background matching an optional task name. -function num_jobs { - local name="$1"; shift; - if [[ "$name" == "" ]]; then - echo $(jobs -r | wc -l) - else - echo $(ps -ef | egrep "$name" | wc -l) - fi -} - -# Sleep as long as N jobs of given name are running in background -function sleep_while_active { - max_jobs=$1; shift - job_name="$1"; shift - j=$(num_jobs $job_name); - while (( $j > $max_jobs )); do - sleep 1; - j=$(num_jobs $job_name); - done; -} - -# Get the date from the file name truncated by time period (month, year). -function get_date_from_name { - local name="$1"; shift - local dt=$(echo "$name" | egrep -o '[0-9]{4}-[0-9]{,2}(-[0-9]{,2})' | head -1) - local unit=$(get_time_period_unit $TIME_PERIOD) - # Extract date upto time period unit. - pat=".*" - case $unit in - y*) pat="^[0-9]*";; - m*) pat="^[0-9]*-[0-9]*";; - d*) pat="^[0-9]*-[0-9]*-[0-9]*";; - esac - echo "$dt" | egrep -o "$pat" | head -1 -} - -# Convert a geoTIFF raster image to CSV. -function process_image { - local img_input="$1"; shift - img_prefix=$(basename $img_input | sed -e 's/\.tif//') - img_dir=$(dirname $img_input) - img_dir=${img_dir:-$OUTPUT_DIR} - local log=$TMP_DIR/ee-raster-process-${img_prefix}.log - # Get date from filename - local dt=${OUTPUT_DATE:-$(get_date_from_name $img_prefix)} - cmd="python3 $SCRIPT_DIR/raster_to_csv.py \ - $DEFAULT_FLAGS_PROCESS \ - $FLAGS \ - --input_geotiff=$img_input* \ - --output_date=$dt \ - --output_s2_place=$img_dir/place/$img_prefix \ - --output_csv=$img_dir/csv/$img_prefix.csv \ - " - echo_log "Processing image $img_prefix with command: $cmd ..." - $cmd 2>&1 | tee $log - cat $log >> $LOG - echo_log "Generated outputs: -$(ls -l ${img_input}* $OUTPUT_DIR/*${img_prefix}* $OUTPUT_DIR/*/*${img_prefix}* 2>/dev/null)" -} - -# Process geoTiff images into CSVs launching one process for each image. -function process_all_images { - local images="$@" - echo_log "Processing images: $images" - for img in $images; do - process_image $img & - sleep_while_active $PARALLELISM - done - echo_log "Waiting for csv process tasks" - wait -} - -parse_options "$@" -if [[ -z "$IMAGE_OUTPUTS" ]]; then - get_all_ee_images -fi -process_all_images $IMAGE_OUTPUTS - diff --git a/scripts/earthengine/run_events.sh b/scripts/earthengine/run_events.sh deleted file mode 100755 index 914a79d610..0000000000 --- a/scripts/earthengine/run_events.sh +++ /dev/null @@ -1,96 +0,0 @@ -#!/bin/bash -# Script to process fires events. -scripts_dir=$(dirname $0) -input_dir="$(dirname $scripts_dir)/output/csv/" -output_dir="$(dirname $scripts_dir)/output/events" -# input_file=firms-input-2022-09-04-10days-s2_13.csv - -mkdir -p $output_dir - -function num_jobs { - local name="$1"; shift; - if [[ "$name" == "" ]]; then - echo $(jobs -r | wc -l) - else - echo $(ps -ef | egrep "$name" | wc -l) - fi -} - -function sleep_while_active { - max_jobs=$1; shift - job_name="$1"; shift - j=$(num_jobs $job_name); - while (( $j > ${max_jobs:-10} )); do - sleep 1; - j=$(num_jobs $job_name); - done; -} - -active_events_opt="" -#for yr in {2012..2022}; do -# for month in {01..12}; do -# time python3 $scripts_dir/process_events.py \ -# --config=$scripts_dir/event_config_fires.py \ -# --input_csv="$input_dir/firms-input-$yr-$month*.csv" \ -# --output_path=$output_dir/firms_events_30d_${yr}_${month}_ \ -# --output_events=$output_dir/firms_active_events_30d_${yr}_${month}.pkl \ -# $active_events_opt \ -# 2>&1 | tee tmp/fires-events-${yr}-${month}.log -# active_events_opt="--input_events=$output_dir/firms_active_events_30d_${yr}_$month.pkl" -# done -#done - -#set -x -#output_type="py" -#output_type="pkl" -#declare -i port=8181 -#for yr in {2012..2022}; do -# output_file=$output_dir/firms_active_events_10d_${yr}.$output_type -# if [[ -f "$output_file" ]]; then -# echo "Skipping year: $yr: existing file: $output_file" -# else -# time python3 $scripts_dir/process_events.py \ -# --config=$scripts_dir/event_config_fires.py \ -# --input_csv="$input_dir/firms-input-$yr*.csv" \ -# --output_path=$output_dir/firms_events_10d_${yr}_ \ -# --output_events=$output_file \ -# --pprof_port=$port \ -# $active_events_opt \ -# 2>&1 | tee tmp/fires-events-${yr}.log & -# fi -# active_events_opt="--input_events=$output_file" -# port+=1 -# sleep_while_active 5 process_events.py -#done -# -#set +x -#exit - - -# Shard by s2 cell -#for yr in {2012..2022}; do -# python3 scripts/shard_csv.py --input_csv="output/csv/firms-input-${yr}-*.csv" --output_path=tmp/shards/firms-${yr} & -#done; wait - -# Process each shard -shards=$(ls tmp/shards/*.csv | sed -e 's/.*shard_//;s/\.csv//' | sort | uniq) -declare -i port=8181 -for s in $shards; -do - output_file=$output_dir/shards/firms_active_events_10d_shard_${s}.$output_type - if [[ -f "$output_file" ]]; then - echo "Skipping year: $yr: existing file: $output_file" - else - time python3 $scripts_dir/process_events.py \ - --config=$scripts_dir/event_config_fires.py \ - --input_csv="tmp/shards/firms*_shard_${s}*.csv" \ - --output_path=$output_dir/shards/firms_events_10d_${s}_ \ - --output_events=$output_file \ - --output_active_path=$output_dir/shards/firms_events_10d_${s}_active_ \ - --pprof_port=$port \ - 2>&1 | tee tmp/fires-events-${s}.log & - fi - port+=1 - sleep_while_active 5 process_events.py -done |& tee tmp/fires-events-shards.log - diff --git a/scripts/earthengine/shard_csv.py b/scripts/earthengine/shard_csv.py deleted file mode 100644 index 1b24b7b5e4..0000000000 --- a/scripts/earthengine/shard_csv.py +++ /dev/null @@ -1,126 +0,0 @@ -# Copyright 2022 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the 'License'); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# https://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an 'AS IS' BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -"""Script to shard csv with goe columns.""" - -import csv -import io -import os -import sys - -from absl import app -from absl import flags -from absl import logging -from typing import Union - -_SCRIPTS_DIR = os.path.dirname(os.path.dirname(__file__)) -sys.path.append(_SCRIPTS_DIR) -sys.path.append(os.path.dirname(_SCRIPTS_DIR)) - -import utils - -from util.counters import Counters -from util.config_map import ConfigMap - -flags.DEFINE_string('input_csv', '', 'CSV with S2 cell data to process') -flags.DEFINE_string('output_path', '', 'Output prefix for CSV files') -flags.DEFINE_string('config', '', 'JSOn file with config parameter settings.') - -_FLAGS = flags.FLAGS - - -def shard_csv_file(filenames: str, - output_path: str, - config: ConfigMap, - counters=Counters): - '''Shard a set of CSV files by the config.''' - if counters is None: - counters = Counters() - input_files = utils.file_get_matching(filenames) - logging.info(f'Processing csv files: {input_files}') - shard_files = {} - for filename in input_files: - counters.add_counter('total', utils.file_estimate_num_rows(filename)) - output_columns = [] - # Process rows form each input file - for filename in input_files: - with open(filename, 'r') as csvfile: - logging.info(f'Processing csv data file: {filename}') - reader = csv.DictReader(csvfile) - counters.add_counter('input-files', 1, filename) - num_rows = 0 - output_columns = reader.fieldnames - for row in reader: - num_rows += 1 - if num_rows > config.get('input_rows', sys.maxsize): - break - counters.add_counter('inputs', 1, filename) - # Get the shard for the row - shard_id = _get_s2_shard_for_data( - row, config.get('s2_shard_level', 1)) - if shard_id not in shard_files: - shard_files[shard_id] = _get_shard_csv_writer( - output_path, shard_id, output_columns) - counters.add_counter('num_shards', 1, filename) - # Write the row into the corresponding shard file - shard_files[shard_id][1].writerow(row) - counters.add_counter(f'shard-rows-{shard_id}', 1, filename) - counters.print_counters_periodically() - logging.info(f'Processed {num_rows} rows from {filename}') - - # Close all open shard files. - for filep, writer in shard_files.values(): - filep.close() - logging.info(f'Generated {len(shard_files)} shard files in {output_path}') - counters.print_counters() - - -def _get_s2_shard_for_data(data_pvs: dict, s2_shard_level: int) -> str: - '''Returns the shard for the data dictionary. - If the data includes s2CellId, uses the s2_shard_level parent as the shard. - ''' - data_s2_cell = utils.s2_cell_from_dcid(data_pvs.get('s2CellId', None)) - if not data_s2_cell: - if 'latitude' in data_pvs and 'longitude' in data_pvs: - data_s2_cell = s2_cell_from_latlng(data_pvs.get('latitude', 0), - data_pvs.get('longitude', 0), - s2_shard_level) - return utils.s2_cell_to_hex_str(data_s2_cell.parent(s2_shard_level).id()) - - -def _get_shard_csv_writer(file_prefix: str, shard_id: str, - columns: list) -> (io.TextIOWrapper, csv.DictWriter): - '''Returns a CSV dict writer wiht the given file prefix.''' - - csv_filename = utils.file_get_name(file_prefix, f'_shard_{shard_id}', - '.csv') - logging.info(f'Creating shrad file: {csv_filename}') - filep = open(csv_filename, 'w') - writer = csv.DictWriter(filep, - fieldnames=columns, - escapechar='\\', - extrasaction='ignore', - quotechar='"', - quoting=csv.QUOTE_NONNUMERIC) - writer.writeheader() - return filep, writer - - -def main(_): - config = ConfigMap(filename=_FLAGS.config) - counters = Counters() - shard_csv_file(_FLAGS.input_csv, _FLAGS.output_path, config, counters) - - -if __name__ == '__main__': - app.run(main) diff --git a/scripts/earthengine/test_data/event_config.py b/scripts/earthengine/test_data/event_config.py index 60748368b7..1bbda3a8b3 100644 --- a/scripts/earthengine/test_data/event_config.py +++ b/scripts/earthengine/test_data/event_config.py @@ -41,5 +41,10 @@ 'output_svobs': True, 'output_active_svobs': True, 'output_affected_place_polygon': 'geoJsonCoordinatesDP1', + 'output_geojson_string': True, 'place_property_cache_file': '/tmp/s2_cell_place_properties.py', + # Output svobs per place + 'output_place_svobs': True, + 'output_place_svobs_properties': ['area', 'count'], + 'output_place_svobs_dates': ['YYYY-MM-DD', 'YYYY-MM', 'YYYY'], } diff --git a/scripts/earthengine/test_data/sample_fires_event_pipeline_config.py b/scripts/earthengine/test_data/sample_fires_event_pipeline_config.py new file mode 100644 index 0000000000..fe9f787b3a --- /dev/null +++ b/scripts/earthengine/test_data/sample_fires_event_pipeline_config.py @@ -0,0 +1,112 @@ +{ + 'defaults': { + 'import_name': 'Sample', + 'start_date': '2023-01-01', + 'time_period': 'P1Y', + 'tmp_dir': '', # Filled in by the test + 'place_property_cache_file': 'test_data/test_s2_cells_properties.pkl', + }, + 'pipeline_state_file': + '', # Set by the test + 'stages': [ + { + 'stage': 'download', + 'url': 'http://sample_test.com/data/{year}', + 'output_file': '{tmp_dir}/{stage}/{year}/fire_input_data.csv', + }, + # convert lat/longs to s2 cells. + { + 'stage': 'raster_csv', + 'time_period': 'P1D', + 's2_level': 13, + 'aggregate': None, + 'input_data_filter': { + 'area': { + # pick max area for s2 cell. + # each fire in input is a fixed region. + 'aggregate': 'max' + }, + }, + 'input_files': '{tmp_dir}/download/{year}/*.csv', + 'output_dir': '{tmp_dir}/{stage}/{year}', + }, + { + 'stage': 'events', + + # Process all data files for the whole year. + 'input_files': '{tmp_dir}/raster_csv/{year}/*raster_csv.csv', + 'output_dir': '{tmp_dir}/{stage}/{year}/sample_fires_', + 'event_type': 'FireEvent', + + # Input settings. + # Columms of input_csv that are added as event properties + 'data_columns': [ + 'area', 'frp', 'bright_ti4', 'bright_ti5', 'confidence' + ], + # Columns of input_csv that contains the s2 cell id. + 'place_column': 's2CellId', + # Input column for date. + 'date_column': 'acq_date', + + # Processing settings + # Maximum distance within which 2 events are merged. + 'max_overlap_distance_km': 0, + # Maximum number of cells of same level in between 2 events to be merged. + 'max_overlap_place_hop': 1, + # S2 level to which data is aggregated. + 's2_level': 10, # Events are at resolution of level-10 S2 cells. + 'aggregate': 'sum', # default aggregation for all properties + # Per property settings + 'property_config': { + 'area': { + 'aggregate': 'sum', + 'unit': 'SquareKilometer', + }, + 'affectedPlace': { + 'aggregate': 'list', + }, + }, + # Per property filter params for input data. + 'input_filter_config': { + 'confidence': { + 'regex': '[nh]', + } + }, + 'output_events_filter_config': { + 'AreaSqKm': { + # Only allow fire events with atleast 4sqkm (10%) of events. + 'min': 2.0, + }, + }, + # Per property settings + 'property_config': { + 'area': { + 'aggregate': 'sum', + 'unit': 'SquareKilometer', + }, + }, + # Treat events at the same location beyond 3 days as separate events. + 'max_event_interval_days': 3, + # Limit time range for an event to 3 months, roughly a season + 'max_event_duration_days': 90, + # Limit event affected region to 1000 L10 s2 cells, roughly 100K sqkm. + 'max_event_places': 1000, + + # Enable DC API lookup for place properties + 'dc_api_enabled': False, + 'dc_api_batch_size': 200, + + # Output settings. + 'output_svobs': True, + 'output_delimiter': ',', + 'output_affected_place_polygon': 'geoJsonCoordinatesDP1', + 'polygon_simplification_factor': None, + 'output_geojson_string': True, + + # Output svobs per place + 'output_place_svobs': True, + 'output_place_svobs_properties': ['area', 'count'], + 'output_place_svobs_dates': ['YYYY-MM-DD', 'YYYY-MM', 'YYYY'], + }, + ] +} diff --git a/scripts/earthengine/test_data/sample_fires_events.csv b/scripts/earthengine/test_data/sample_fires_events.csv new file mode 100644 index 0000000000..d6634dd8f7 --- /dev/null +++ b/scripts/earthengine/test_data/sample_fires_events.csv @@ -0,0 +1,176 @@ +"dcid","typeOf","name","startDate","endDate","observationPeriod","DurationDays","numberOfDays","startLocation","affectedPlace","AffectedPlaceCount","area","AreaSqKm","bright_ti4","bright_ti5","confidence","frp","observationDate","geoJsonCoordinatesDP1" +"fireEvent/2023-01-31_0x80837b0000000000","FireEvent","FireEvent at L10 S2 Cell 0x8083630000000000 on 2023-01-31","2023-01-31","2023-01-31","P1D",1,1,"[LatLong 39.07645 -122.15757]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06011,dcid:northamerica,dcid:s2CellId/0x808362bc00000000,dcid:s2CellId/0x8083630000000000,dcid:s2CellId/0x80837a5400000000,dcid:s2CellId/0x80837b0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.03855 SquareKilometer]",2.03855,335.81,288.82,"n",2.01,"2023-01-31","{'type': 'MultiPolygon', 'coordinates': [(((-122.26538872869685, 39.104064455903135), (-122.26538872869685, 39.17888461552509), (-122.17460498684162, 39.20690582223145), (-122.17460498684162, 39.132070524198696), (-122.26538872869685, 39.104064455903135)),), (((-122.08374449567627, 39.160007530943815), (-122.08374449567627, 39.08507197362498), (-122.17460498684162, 39.057150204742555), (-122.17460498684162, 39.132070524198696), (-122.08374449567627, 39.160007530943815)),)]}" +"fireEvent/2023-02-06_0x8094af0000000000","FireEvent","FireEvent at L10 S2 Cell 0x8094af0000000000 on 2023-02-06","2023-02-06","2023-02-06","P1D",1,1,"[LatLong 36.10040 -120.02030]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06031,dcid:northamerica,dcid:s2CellId/0x8094af0000000000,dcid:s2CellId/0x8094af1c00000000,dcid:s2CellId/0x8094af2400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.28556 SquareKilometer]",2.28556,334.6,287.55,"n",4.13,"2023-02-06","{'type': 'Polygon', 'coordinates': (((-120.06652363285929, 36.12725014536185), (-120.06652363285929, 36.04806788044641), (-119.97405342347365, 36.07349347026282), (-119.97405342347365, 36.15269831052497), (-120.06652363285929, 36.12725014536185)),)}" +"fireEvent/2023-01-12_0x80d65d0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d65d0000000000 on 2023-01-12","2023-01-12","2023-01-12","P1D",1,1,"[LatLong 32.59410 -114.57772]","dcid:Earth,dcid:country/USA,dcid:geoId/04,dcid:geoId/04027,dcid:northamerica,dcid:s2CellId/0x80d65c3400000000,dcid:s2CellId/0x80d65d0000000000,dcid:s2CellId/0x80d65e6400000000,dcid:s2CellId/0x80d65e6c00000000,dcid:s2CellId/0x80d65f0000000000,dcid:usc/MountainDivision,dcid:usc/WestRegion",5,"[3.9386 SquareKilometer]",3.9386,367.0,293.19,"n",16.15,"2023-01-12","{'type': 'Polygon', 'coordinates': (((-114.52426397902158, 32.53615314436677), (-114.61928990191176, 32.516455336320426), (-114.61928990191176, 32.601380600508776), (-114.61928990191176, 32.686238988626556), (-114.52426397902158, 32.705990765439765), (-114.52426397902158, 32.62110549021124), (-114.52426397902158, 32.53615314436677)),)}" +"fireEvent/2023-02-14_0x80ea570000000000","FireEvent","FireEvent at L10 S2 Cell 0x80ea570000000000 on 2023-02-14","2023-02-14","2023-02-14","P1D",1,1,"[LatLong 35.50403 -119.27856]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06029,dcid:northamerica,dcid:s2CellId/0x80ea570000000000,dcid:s2CellId/0x80ea577400000000,dcid:s2CellId/0x80eafaec00000000,dcid:s2CellId/0x80eafb0000000000,dcid:s2CellId/0x80eafd0000000000,dcid:s2CellId/0x80eafd0400000000,dcid:s2CellId/0x80eaff0000000000,dcid:s2CellId/0x80eaff2400000000,dcid:s2CellId/0x80eaff2c00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",9,"[5.84321 SquareKilometer]",5.84321,340.56,292.86,"n",8.12,"2023-02-14","{'type': 'MultiPolygon', 'coordinates': [(((-119.23207840138082, 35.47625041156115), (-119.32503466239531, 35.45162141848549), (-119.32503466239531, 35.53175350399878), (-119.23207840138082, 35.556406222206114), (-119.23207840138082, 35.47625041156115)),), (((-119.23207840138082, 35.63648603631758), (-119.32503466239531, 35.61180980810941), (-119.32503466239531, 35.53175350399878), (-119.41793235298398, 35.50702987289793), (-119.41793235298398, 35.58706253975614), (-119.41793235298401, 35.66701930371646), (-119.32503466239531, 35.69178999395241), (-119.23207840138082, 35.716489517297106), (-119.23207840138082, 35.63648603631758)),)]}" +"fireEvent/2023-02-15_0x8092db0000000000","FireEvent","FireEvent at L10 S2 Cell 0x8092db0000000000 on 2023-02-15","2023-02-15","2023-02-15","P1D",1,1,"[LatLong 35.89531 -121.03351]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06053,dcid:northamerica,dcid:s2CellId/0x8092db0000000000,dcid:s2CellId/0x8092dbec00000000,dcid:s2CellId/0x8092dbf400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.26338 SquareKilometer]",2.26338,333.02,292.38,"n",3.38,"2023-02-15","{'type': 'Polygon', 'coordinates': (((-121.07937052658627, 35.92160807483137), (-121.07937052658627, 35.842757347952094), (-120.98763211526173, 35.8689609102411), (-120.98763211526173, 35.947835377412154), (-121.07937052658627, 35.92160807483137)),)}" +"fireEvent/2023-01-02_0x80d7070000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d7070000000000 on 2023-01-02","2023-01-02","2023-01-02","P1D",1,1,"[LatLong 32.65892 -115.07625]","dcid:Earth,dcid:country/MEX,dcid:northamerica,dcid:s2CellId/0x80d7061400000000,dcid:s2CellId/0x80d7066c00000000,dcid:s2CellId/0x80d7070000000000,dcid:wikidataId/Q1477270,dcid:wikidataId/Q58731",3,"[2.61267 SquareKilometer]",2.61267,356.58,300.12,"n",19.19,"2023-01-02","{'type': 'Polygon', 'coordinates': (((-115.09404500241959, 32.671008212834636), (-115.09404500241959, 32.58635275421574), (-114.99914638140322, 32.60647972155236), (-114.99914638140322, 32.69116258740858), (-115.09404500241959, 32.671008212834636)),)}" +"fireEvent/2023-02-10_0x8083270000000000","FireEvent","FireEvent at L10 S2 Cell 0x8083270000000000 on 2023-02-10","2023-02-10","2023-02-11","P2D",2,2,"[LatLong 39.69439 -121.81640]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06007,dcid:northamerica,dcid:s2CellId/0x8083260400000000,dcid:s2CellId/0x8083270000000000,dcid:s2CellId/0x8083274c00000000,dcid:s2CellId/0x8083275400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.01116 SquareKilometer]",2.01116,340.04,285.06,"n",3.14,"2023-02-10,2023-02-11","{'type': 'Polygon', 'coordinates': (((-121.90179543138471, 39.73802301630229), (-121.90179543138471, 39.66366133679624), (-121.81070794913828, 39.69147458174664), (-121.81070794913828, 39.76584973823246), (-121.90179543138471, 39.73802301630229)),)}" +"fireEvent/2023-02-23_0x80eae30000000000","FireEvent","FireEvent at L10 S2 Cell 0x80eae30000000000 on 2023-02-23","2023-02-23","2023-02-23","P1D",1,1,"[LatLong 35.71937 -119.37149]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06029,dcid:northamerica,dcid:s2CellId/0x80eae30000000000,dcid:s2CellId/0x80eae36400000000,dcid:s2CellId/0x80eae3ac00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.32886 SquareKilometer]",2.32886,326.92,287.13,"n",3.53,"2023-02-23","{'type': 'Polygon', 'coordinates': (((-119.41793235298398, 35.74689982999827), (-119.41793235298401, 35.66701930371646), (-119.32503466239531, 35.69178999395241), (-119.32503466239531, 35.77169372701799), (-119.41793235298398, 35.74689982999827)),)}" +"fireEvent/2023-02-08_0x809b990000000000","FireEvent","FireEvent at L10 S2 Cell 0x809b990000000000 on 2023-02-08","2023-02-08","2023-02-08","P1D",1,1,"[LatLong 39.21832 -120.75798]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06061,dcid:northamerica,dcid:s2CellId/0x809b990000000000,dcid:s2CellId/0x809b996400000000,dcid:s2CellId/0x809b997400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.07602 SquareKilometer]",2.07602,305.34,276.36,"n",1.07,"2023-02-08","{'type': 'Polygon', 'coordinates': (((-120.80394744373855, 39.24263772504066), (-120.80394744373855, 39.16714989698495), (-120.7120023484522, 39.193946808225185), (-120.7120023484522, 39.269449088826086), (-120.80394744373855, 39.24263772504066)),)}" +"fireEvent/2023-03-18_0x80dd350000000000","FireEvent","FireEvent at L10 S2 Cell 0x80dd350000000000 on 2023-03-18","2023-03-18","2023-03-18","P1D",1,1,"[LatLong 33.82611 -118.24681]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06037,dcid:northamerica,dcid:s2CellId/0x80dd34fc00000000,dcid:s2CellId/0x80dd350000000000,dcid:s2CellId/0x80dd359c00000000,dcid:s2CellId/0x80dd4b0000000000,dcid:s2CellId/0x80dd4bac00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",5,"[3.70076 SquareKilometer]",3.70076,297.55,284.36,"n",0.7,"2023-03-18","{'type': 'Polygon', 'coordinates': (((-118.20587682407124, 33.8722154192009), (-118.20587682407124, 33.79003345093331), (-118.29943499572406, 33.76679933456592), (-118.39294170620582, 33.74349483462569), (-118.39294170620582, 33.82562180473932), (-118.29943499572406, 33.848953872494164), (-118.20587682407124, 33.8722154192009)),)}" +"fireEvent/2023-02-22_0x8090f90000000000","FireEvent","FireEvent at L10 S2 Cell 0x8090f70000000000 on 2023-02-22","2023-02-22","2023-02-22","P1D",1,1,"[LatLong 37.81896 -120.84989]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06099,dcid:northamerica,dcid:s2CellId/0x8090f70000000000,dcid:s2CellId/0x8090f7f400000000,dcid:s2CellId/0x8090f81c00000000,dcid:s2CellId/0x8090f90000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.16141 SquareKilometer]",2.16141,353.83,289.55,"n",5.74,"2023-02-22","{'type': 'Polygon', 'coordinates': (((-120.80394744373855, 37.71662016196677), (-120.89582422732902, 37.69006636052178), (-120.89582422732902, 37.76714783509468), (-120.89582422732902, 37.84414693051973), (-120.80394744373855, 37.870737535489965), (-120.80394744373855, 37.79372014425884), (-120.80394744373855, 37.71662016196677)),)}" +"fireEvent/2023-02-10_0x80d7b50000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d64d0000000000 on 2023-02-10","2023-02-10","2023-02-12","P3D",3,3,"[LatLong 32.38917 -114.89829]","dcid:Earth,dcid:country/MEX,dcid:northamerica,dcid:s2CellId/0x80d64cb400000000,dcid:s2CellId/0x80d64d0000000000,dcid:s2CellId/0x80d7b50000000000,dcid:s2CellId/0x80d7b5cc00000000,dcid:s2CellId/0x80d7c90000000000,dcid:s2CellId/0x80d7c91c00000000,dcid:s2CellId/0x80d7cb0000000000,dcid:s2CellId/0x80d7cb6c00000000,dcid:wikidataId/Q1477270,dcid:wikidataId/Q58731",8,"[5.27073 SquareKilometer]",5.27073,341.66,301.14,"n",12.68,"2023-02-10,2023-02-11,2023-02-12","{'type': 'MultiPolygon', 'coordinates': [(((-114.90422082333554, 32.287028613932726), (-114.90422082333554, 32.20198930823536), (-114.99914638140322, 32.182076294930475), (-115.09404500241959, 32.16208932703202), (-115.09404500241959, 32.24707198896053), (-114.99914638140322, 32.26708735189506), (-114.99914638140322, 32.35203367788002), (-114.90422082333554, 32.37200299165679), (-114.90422082333554, 32.287028613932726)),), (((-114.80926906488743, 32.47683458066355), (-114.80926906488743, 32.39189787714385), (-114.90422082333554, 32.37200299165679), (-114.90422082333554, 32.45691198535573), (-114.80926906488743, 32.47683458066355)),)]}" +"fireEvent/2023-02-16_0x80d7490000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d7490000000000 on 2023-02-16","2023-02-16","2023-02-16","P1D",1,1,"[LatLong 33.07521 -115.34895]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06025,dcid:northamerica,dcid:s2CellId/0x80d748e400000000,dcid:s2CellId/0x80d748ec00000000,dcid:s2CellId/0x80d7490000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.58433 SquareKilometer]",2.58433,340.42,296.24,"n",4.19,"2023-02-16","{'type': 'Polygon', 'coordinates': (((-115.3785719022423, 33.11612672382202), (-115.3785719022423, 33.03195811961158), (-115.28375849518459, 33.052472062640916), (-115.28375849518459, 33.13666731039678), (-115.3785719022423, 33.11612672382202)),)}" +"fireEvent/2023-03-27_0x80c2d10000000000","FireEvent","FireEvent at L10 S2 Cell 0x80c2d10000000000 on 2023-03-27","2023-03-27","2023-03-27","P1D",1,1,"[LatLong 34.06595 -118.02446]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06037,dcid:northamerica,dcid:s2CellId/0x80c2d0b400000000,dcid:s2CellId/0x80c2d0c400000000,dcid:s2CellId/0x80c2d10000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.46115 SquareKilometer]",2.46115,323.9,278.28,"n",2.3,"2023-03-27","{'type': 'Polygon', 'coordinates': (((-118.1122678531936, 34.059614889814924), (-118.1122678531936, 33.97754564726115), (-118.01860874756083, 34.00069236114518), (-118.01860874756083, 34.08278833318326), (-118.1122678531936, 34.059614889814924)),)}" +"fireEvent/2023-02-14_0x8093770000000000","FireEvent","FireEvent at L10 S2 Cell 0x8093770000000000 on 2023-02-14","2023-02-14","2023-02-14","P1D",1,1,"[LatLong 36.47132 -120.38967]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06019,dcid:northamerica,dcid:s2CellId/0x8093770000000000,dcid:s2CellId/0x8093777400000000,dcid:s2CellId/0x8093790000000000,dcid:s2CellId/0x809379cc00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.25413 SquareKilometer]",2.25413,331.82,291.3,"n",4.78,"2023-02-14","{'type': 'Polygon', 'coordinates': (((-120.43576307692442, 36.41906007532748), (-120.43576307692442, 36.49768733054752), (-120.3435506342276, 36.52354795442271), (-120.25127284433846, 36.54933860162116), (-120.25127284433846, 36.47066792590074), (-120.3435506342276, 36.44489892762193), (-120.43576307692442, 36.41906007532748)),)}" +"fireEvent/2023-03-25_0x80936f0000000000","FireEvent","FireEvent at L10 S2 Cell 0x8093650000000000 on 2023-03-25","2023-03-25","2023-03-25","P1D",1,1,"[LatLong 36.33966 -120.29742]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06019,dcid:northamerica,dcid:s2CellId/0x8093650000000000,dcid:s2CellId/0x8093655400000000,dcid:s2CellId/0x80936f0000000000,dcid:s2CellId/0x80936ffc00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.26092 SquareKilometer]",2.26092,338.76,290.16,"n",5.64,"2023-03-25","{'type': 'Polygon', 'coordinates': (((-120.43576307692442, 36.26157181199122), (-120.43576307692442, 36.340354799856954), (-120.34355063422758, 36.36617166395524), (-120.25127284433846, 36.391918797186285), (-120.25127284433846, 36.313091522676416), (-120.3435506342276, 36.28736647095043), (-120.43576307692442, 36.26157181199122)),)}" +"fireEvent/2023-03-01_0x80845b0000000000","FireEvent","FireEvent at L10 S2 Cell 0x8084450000000000 on 2023-03-01","2023-03-01","2023-03-03","P3D",3,3,"[LatLong 38.55335 -122.54293]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06055,dcid:geoId/06097,dcid:northamerica,dcid:s2CellId/0x808444b400000000,dcid:s2CellId/0x808444dc00000000,dcid:s2CellId/0x808444e400000000,dcid:s2CellId/0x808444fc00000000,dcid:s2CellId/0x8084450000000000,dcid:s2CellId/0x8084470000000000,dcid:s2CellId/0x8084473c00000000,dcid:s2CellId/0x80845a1400000000,dcid:s2CellId/0x80845a1c00000000,dcid:s2CellId/0x80845a5400000000,dcid:s2CellId/0x80845acc00000000,dcid:s2CellId/0x80845b0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion,dcid:wikidataId/Q213205,dcid:wikidataId/Q3271661",12,"[6.18521 SquareKilometer]",6.18521,337.37,290.81,"n",12.81,"2023-03-01,2023-03-02,2023-03-03","{'type': 'Polygon', 'coordinates': (((-122.44672381753844, 38.52196905593188), (-122.5372740990185, 38.49387172650253), (-122.62774550019422, 38.465707290702724), (-122.71813749631639, 38.437476047170406), (-122.71813749631639, 38.51280040712088), (-122.62774550019422, 38.541048824246204), 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2023-02-02","2023-02-02","2023-02-04","P3D",3,2,"[LatLong 32.26175 -115.09998]","dcid:Earth,dcid:country/MEX,dcid:northamerica,dcid:s2CellId/0x80d7b81c00000000,dcid:s2CellId/0x80d7b90000000000,dcid:s2CellId/0x80d7c0c400000000,dcid:s2CellId/0x80d7c10000000000,dcid:s2CellId/0x80d7c30000000000,dcid:s2CellId/0x80d7c35400000000,dcid:s2CellId/0x80d7c4ac00000000,dcid:s2CellId/0x80d7c50000000000,dcid:s2CellId/0x80d7db0000000000,dcid:s2CellId/0x80d7db5400000000,dcid:wikidataId/Q1477270,dcid:wikidataId/Q58731",10,"[6.59638 SquareKilometer]",6.59638,342.82,306.64,"n",19.32,"2023-02-02,2023-02-04","{'type': 'MultiPolygon', 'coordinates': [(((-115.18891595142229, 32.2269827091063), (-115.18891595142229, 32.31187249427941), (-115.09404500241959, 32.33199011749119), (-115.09404500241959, 32.24707198896053), (-115.18891595142229, 32.2269827091063)),), (((-115.09404500241959, 32.07704259018568), (-115.09404500241959, 31.99193223931182), (-115.18891595142229, 31.971929178501046), (-115.18891595142229, 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-114.00123]","dcid:Earth,dcid:country/USA,dcid:geoId/04,dcid:geoId/04027,dcid:northamerica,dcid:s2CellId/0x80d5d10000000000,dcid:s2CellId/0x80d5d11c00000000,dcid:s2CellId/0x80d5d6ec00000000,dcid:s2CellId/0x80d5d70000000000,dcid:usc/MountainDivision,dcid:usc/WestRegion",4,"[2.63233 SquareKilometer]",2.63233,351.31,297.55,"n",9.3,"2023-01-27","{'type': 'Polygon', 'coordinates': (((-113.95364658268294, 32.73786508789439), (-113.95364658268294, 32.652753258290254), (-114.0488007261198, 32.63350963491579), (-114.14393537153407, 32.61418990174488), (-114.14393537153407, 32.69924914124556), (-114.0488007261198, 32.71859524067644), (-113.95364658268294, 32.73786508789439)),)}" +"fireEvent/2023-02-13_0x54d2cf0000000000","FireEvent","FireEvent at L10 S2 Cell 0x54d2cf0000000000 on 2023-02-13","2023-02-13","2023-02-15","P3D",3,3,"[LatLong 40.33882 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2023-02-12","2023-02-12","2023-02-13","P2D",2,2,"[LatLong 36.31641 -120.25704]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06019,dcid:northamerica,dcid:s2CellId/0x8093640400000000,dcid:s2CellId/0x8093641c00000000,dcid:s2CellId/0x8093650000000000,dcid:s2CellId/0x809366a400000000,dcid:s2CellId/0x8093670000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",5,"[3.39951 SquareKilometer]",3.39951,351.49,300.49,"n",27.39,"2023-02-12,2023-02-13","{'type': 'Polygon', 'coordinates': (((-120.34355063422758, 36.36617166395524), (-120.25127284433846, 36.391918797186285), (-120.25127284433846, 36.313091522676416), (-120.25127284433846, 36.23418641187698), (-120.3435506342276, 36.208483658436926), (-120.3435506342276, 36.28736647095043), (-120.34355063422758, 36.36617166395524)),)}" +"fireEvent/2023-01-24_0x80c3170000000000","FireEvent","FireEvent at L10 S2 Cell 0x80c3170000000000 on 2023-01-24","2023-01-24","2023-01-24","P1D",1,1,"[LatLong 34.36849 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32.5661512898709)),)]}" +"fireEvent/2023-01-22_0x80d7730000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d7730000000000 on 2023-01-22","2023-01-22","2023-01-24","P3D",3,2,"[LatLong 32.66256 -115.33117]","dcid:Earth,dcid:country/MEX,dcid:northamerica,dcid:s2CellId/0x80d7730000000000,dcid:s2CellId/0x80d7734400000000,dcid:s2CellId/0x80d7770000000000,dcid:s2CellId/0x80d777e400000000,dcid:wikidataId/Q1477270,dcid:wikidataId/Q58731",4,"[2.61009 SquareKilometer]",2.61009,332.31,298.7,"n",2.4,"2023-01-22,2023-01-24","{'type': 'MultiPolygon', 'coordinates': [(((-115.3785719022423, 32.69460416981107), (-115.28375849518459, 32.71500954782312), (-115.28375849518459, 32.63047572713295), (-115.3785719022423, 32.610097988335994), (-115.3785719022423, 32.69460416981107)),), (((-115.3785719022423, 32.52552561351063), (-115.47335544292073, 32.505101778412154), (-115.47335544292073, 32.58964617062371), (-115.3785719022423, 32.610097988335994), (-115.3785719022423, 32.52552561351063)),)]}" 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-120.48184]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06047,dcid:northamerica,dcid:s2CellId/0x8091430000000000,dcid:s2CellId/0x8091434c00000000,dcid:s2CellId/0x80914f0000000000,dcid:s2CellId/0x80914f9400000000,dcid:s2CellId/0x80914fec00000000,dcid:s2CellId/0x8091501400000000,dcid:s2CellId/0x8091510000000000,dcid:s2CellId/0x80915acc00000000,dcid:s2CellId/0x80915b0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",9,"[4.41107 SquareKilometer]",4.41107,356.61,284.68,"n",6.12,"2023-02-06,2023-02-07","{'type': 'MultiPolygon', 'coordinates': [(((-120.34355063422758, 37.305669184325005), (-120.3435506342276, 37.38343796695286), (-120.25127284433846, 37.4094525873983), (-120.25127284433846, 37.33166450998572), (-120.25127284433846, 37.25379475261621), (-120.3435506342276, 37.227818933892436), (-120.43576307692442, 37.20177205672942), (-120.43576307692442, 37.27960268252231), (-120.34355063422758, 37.305669184325005)),), (((-120.52790957361556, 37.3311951171772), 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+"fireEvent/2023-01-06_0x80dce70000000000","FireEvent","FireEvent at L10 S2 Cell 0x80dcc30000000000 on 2023-01-06","2023-01-06","2023-01-07","P2D",2,2,"[LatLong 33.71042 -117.69042]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06059,dcid:northamerica,dcid:s2CellId/0x80dcc30000000000,dcid:s2CellId/0x80dcc31c00000000,dcid:s2CellId/0x80dce70000000000,dcid:s2CellId/0x80dce73400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.49041 SquareKilometer]",2.49041,303.65,278.77,"n",0.6,"2023-01-06,2023-01-07","{'type': 'MultiPolygon', 'coordinates': [(((-117.73733730424752, 33.5751727543498), (-117.83114280240233, 33.55240330188513), (-117.83114280240233, 33.63497147549895), (-117.73733730424752, 33.65776852203245), (-117.73733730424752, 33.5751727543498)),), (((-117.73733730424752, 33.74029521156066), (-117.64348435403741, 33.7630480860941), (-117.64348435403741, 33.68049415262919), (-117.73733730424752, 33.65776852203245), (-117.73733730424752, 33.74029521156066)),)]}" +"fireEvent/2023-01-25_0x80ec050000000000","FireEvent","FireEvent at L10 S2 Cell 0x80ec050000000000 on 2023-01-25","2023-01-25","2023-01-25","P1D",1,1,"[LatLong 34.74818 -120.29742]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06083,dcid:northamerica,dcid:s2CellId/0x80ec050000000000,dcid:s2CellId/0x80ec057c00000000,dcid:s2CellId/0x80ec0e8400000000,dcid:s2CellId/0x80ec0f0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.34865 SquareKilometer]",2.34865,329.35,294.47,"n",2.69,"2023-01-25","{'type': 'Polygon', 'coordinates': (((-120.25127284433846, 34.72062891210619), (-120.3435506342276, 34.69539140251545), (-120.3435506342276, 34.7756870620793), (-120.3435506342276, 34.855911425114904), (-120.25127284433846, 34.881201654610386), (-120.25127284433846, 34.80095104252741), (-120.25127284433846, 34.72062891210619)),)}" +"fireEvent/2023-02-14_0x8094a50000000000","FireEvent","FireEvent at L10 S2 Cell 0x8094a50000000000 on 2023-02-14","2023-02-14","2023-02-14","P1D",1,1,"[LatLong 36.19279 -120.02608]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06019,dcid:geoId/06031,dcid:northamerica,dcid:s2CellId/0x8094a45c00000000,dcid:s2CellId/0x8094a50000000000,dcid:s2CellId/0x8094af0000000000,dcid:s2CellId/0x8094af3400000000,dcid:s2CellId/0x8094b27400000000,dcid:s2CellId/0x8094b30000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",6,"[3.42808 SquareKilometer]",3.42808,335.21,293.78,"n",5.68,"2023-02-14","{'type': 'MultiPolygon', 'coordinates': [(((-120.06652363285929, 36.20635508236253), (-119.97405342347365, 36.23182560661413), (-119.97405342347365, 36.15269831052497), (-119.97405342347365, 36.07349347026282), (-120.06652363285929, 36.04806788044641), (-120.06652363285929, 36.12725014536185), (-120.06652363285929, 36.20635508236253)),), (((-119.881520291274, 36.0988488632732), (-119.881520291274, 36.01954412977965), (-119.97405342347365, 35.99421140364652), (-119.97405342347365, 36.07349347026282), (-119.881520291274, 36.0988488632732)),)]}" +"fireEvent/2023-01-31_0x8094290000000000","FireEvent","FireEvent at L10 S2 Cell 0x8094250000000000 on 2023-01-31","2023-01-31","2023-02-04","P5D",5,4,"[LatLong 37.22554 -119.64992]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06039,dcid:northamerica,dcid:s2CellId/0x8094250000000000,dcid:s2CellId/0x809425b400000000,dcid:s2CellId/0x8094286400000000,dcid:s2CellId/0x8094287c00000000,dcid:s2CellId/0x8094289400000000,dcid:s2CellId/0x809428bc00000000,dcid:s2CellId/0x809428c400000000,dcid:s2CellId/0x8094290000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",8,"[3.34329 SquareKilometer]",3.34329,338.9,283.46,"n",5.43,"2023-01-31,2023-02-01,2023-02-02,2023-02-04","{'type': 'MultiPolygon', 'coordinates': [(((-119.60354950502408, 37.35552745160059), (-119.51077084299, 37.380906429606696), (-119.51077084299, 37.302718937652955), (-119.60354950502408, 37.27735895346938), (-119.60354950502408, 37.35552745160059)),), (((-119.60354950502408, 37.19910814898932), (-119.69626771448172, 37.173694542784204), (-119.69626771448172, 37.25192602751666), (-119.60354950502408, 37.27735895346938), (-119.60354950502408, 37.19910814898932)),)]}" +"fireEvent/2023-03-03_0x80948f0000000000","FireEvent","FireEvent at L10 S2 Cell 0x8094850000000000 on 2023-03-03","2023-03-03","2023-03-03","P1D",1,1,"[LatLong 36.49539 -120.02030]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06019,dcid:northamerica,dcid:s2CellId/0x8094850000000000,dcid:s2CellId/0x8094859c00000000,dcid:s2CellId/0x80948e4400000000,dcid:s2CellId/0x80948f0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.26479 SquareKilometer]",2.26479,339.48,291.4,"n",5.26,"2023-03-03","{'type': 'Polygon', 'coordinates': (((-119.881520291274, 36.57303994189822), (-119.881520291274, 36.49420457905506), (-119.97405342347365, 36.46873908649985), (-120.06652363285929, 36.44320277938829), (-120.06652363285929, 36.52199526983154), (-119.97405342347365, 36.54755307417071), (-119.881520291274, 36.57303994189822)),)}" +"fireEvent/2023-02-22_0x809ab50000000000","FireEvent","FireEvent at L10 S2 Cell 0x809ab50000000000 on 2023-02-22","2023-02-22","2023-02-22","P1D",1,1,"[LatLong 38.28943 -121.57696]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06067,dcid:northamerica,dcid:s2CellId/0x809ab45400000000,dcid:s2CellId/0x809ab50000000000,dcid:s2CellId/0x809ac90000000000,dcid:s2CellId/0x809ac97c00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.10594 SquareKilometer]",2.10594,332.24,288.45,"n",4.85,"2023-02-22","{'type': 'MultiPolygon', 'coordinates': [(((-121.53700031324804, 38.26805113233758), (-121.62830983522124, 38.24075768997389), (-121.62830983522124, 38.31686847929773), (-121.53700031324804, 38.344179224155184), (-121.53700031324804, 38.26805113233758)),), (((-121.53700031324804, 38.420223862477606), (-121.44561789291927, 38.44748195173517), (-121.44561789291927, 38.37142033485118), (-121.53700031324804, 38.344179224155184), (-121.53700031324804, 38.420223862477606)),)]}" +"fireEvent/2023-02-08_0x8094250000000000","FireEvent","FireEvent at L10 S2 Cell 0x8094250000000000 on 2023-02-08","2023-02-08","2023-02-09","P2D",2,2,"[LatLong 37.23862 -119.65571]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06039,dcid:northamerica,dcid:s2CellId/0x8094244c00000000,dcid:s2CellId/0x8094250000000000,dcid:s2CellId/0x80942ea400000000,dcid:s2CellId/0x80942eac00000000,dcid:s2CellId/0x80942eb400000000,dcid:s2CellId/0x80942f0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",6,"[3.34742 SquareKilometer]",3.34742,346.83,294.81,"n",10.98,"2023-02-08,2023-02-09","{'type': 'Polygon', 'coordinates': (((-119.69626771448172, 37.173694542784204), (-119.69626771448172, 37.25192602751666), (-119.60354950502408, 37.27735895346938), (-119.51077084299, 37.302718937652955), (-119.51077084299, 37.22444893017269), (-119.60354950502408, 37.19910814898932), (-119.69626771448172, 37.173694542784204)),)}" +"fireEvent/2023-01-31_0x809cc10000000000","FireEvent","FireEvent at L10 S2 Cell 0x809cc10000000000 on 2023-01-31","2023-01-31","2023-02-01","P2D",2,2,"[LatLong 39.64345 -121.33701]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06007,dcid:northamerica,dcid:s2CellId/0x809cc0dc00000000,dcid:s2CellId/0x809cc10000000000,dcid:s2CellId/0x809cc12400000000,dcid:s2CellId/0x809cc12c00000000,dcid:s2CellId/0x809cc13400000000,dcid:s2CellId/0x809cc15400000000,dcid:s2CellId/0x809cc15c00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",7,"[4.06547 SquareKilometer]",4.06547,367.0,291.92,"n",40.6,"2023-01-31,2023-02-01","{'type': 'Polygon', 'coordinates': (((-121.35416313685073, 39.680326313083874), (-121.35416313685073, 39.60562152971405), (-121.26263661074441, 39.63296572194452), (-121.26263661074441, 39.70768396595418), (-121.35416313685073, 39.680326313083874)),)}" +"fireEvent/2023-02-14_0x8094f70000000000","FireEvent","FireEvent at L10 S2 Cell 0x8094f70000000000 on 2023-02-14","2023-02-14","2023-02-14","P1D",1,1,"[LatLong 36.67586 -119.64992]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06019,dcid:northamerica,dcid:s2CellId/0x8094f70000000000,dcid:s2CellId/0x8094f77400000000,dcid:s2CellId/0x8094fb0000000000,dcid:s2CellId/0x8094fb5400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.269 SquareKilometer]",2.269,331.0,288.63,"n",2.34,"2023-02-14","{'type': 'MultiPolygon', 'coordinates': [(((-119.69626771448172, 36.6237998027113), (-119.69626771448172, 36.70259781153337), (-119.60354950502408, 36.727891074425536), (-119.60354950502408, 36.6490722675175), (-119.69626771448172, 36.6237998027113)),), (((-119.51077084299, 36.674272739182356), (-119.51077084299, 36.59535309054964), (-119.60354950502408, 36.57017350866958), (-119.60354950502408, 36.6490722675175), (-119.51077084299, 36.674272739182356)),)]}" +"fireEvent/2023-01-16_0x80eaf90000000000","FireEvent","FireEvent at L10 S2 Cell 0x80eaf90000000000 on 2023-01-16","2023-01-16","2023-01-18","P3D",3,2,"[LatLong 35.58413 -119.27856]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06029,dcid:northamerica,dcid:s2CellId/0x80eaf90000000000,dcid:s2CellId/0x80eaf95c00000000,dcid:s2CellId/0x80eaff0000000000,dcid:s2CellId/0x80eaff3c00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.33749 SquareKilometer]",2.33749,332.85,278.88,"n",2.59,"2023-01-16,2023-01-18","{'type': 'Polygon', 'coordinates': (((-119.23207840138082, 35.63648603631758), (-119.23207840138082, 35.556406222206114), (-119.32503466239531, 35.53175350399878), (-119.41793235298398, 35.50702987289793), (-119.41793235298398, 35.58706253975614), (-119.32503466239531, 35.61180980810941), (-119.23207840138082, 35.63648603631758)),)}" +"fireEvent/2023-02-16_0x80d7a90000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d7a50000000000 on 2023-02-16","2023-02-16","2023-02-16","P1D",1,1,"[LatLong 32.45876 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2023-02-13","2023-02-13","2023-02-15","P3D",3,2,"[LatLong 37.57910 -121.06217]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06077,dcid:geoId/06099,dcid:northamerica,dcid:s2CellId/0x809052bc00000000,dcid:s2CellId/0x809052c400000000,dcid:s2CellId/0x8090530000000000,dcid:s2CellId/0x8090570000000000,dcid:s2CellId/0x8090578c00000000,dcid:s2CellId/0x8090579400000000,dcid:s2CellId/0x809057f400000000,dcid:s2CellId/0x8090582400000000,dcid:s2CellId/0x8090590000000000,dcid:s2CellId/0x8090597400000000,dcid:s2CellId/0x8090f65400000000,dcid:s2CellId/0x8090f70000000000,dcid:s2CellId/0x8090f73400000000,dcid:s2CellId/0x8091b2b400000000,dcid:s2CellId/0x8091b30000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",15,"[8.65243 SquareKilometer]",8.65243,339.36,300.29,"n",42.79,"2023-02-13,2023-02-15","{'type': 'MultiPolygon', 'coordinates': [(((-120.98763211526173, 37.74050506353507), (-120.98763211526173, 37.81748574806016), (-120.89582422732902, 37.84414693051973), (-120.80394744373855, 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2023-01-21","2023-01-21","2023-01-31","P11D",11,8,"[LatLong 38.53926 -122.58817]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06055,dcid:geoId/06097,dcid:northamerica,dcid:s2CellId/0x8084446400000000,dcid:s2CellId/0x8084448400000000,dcid:s2CellId/0x808444bc00000000,dcid:s2CellId/0x8084450000000000,dcid:s2CellId/0x80844f0000000000,dcid:s2CellId/0x80844f5c00000000,dcid:s2CellId/0x8084506c00000000,dcid:s2CellId/0x8084510000000000,dcid:s2CellId/0x80845a3c00000000,dcid:s2CellId/0x80845a8400000000,dcid:s2CellId/0x80845ab400000000,dcid:s2CellId/0x80845abc00000000,dcid:s2CellId/0x80845b0000000000,dcid:s2CellId/0x80845d0000000000,dcid:s2CellId/0x80845d7400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion,dcid:wikidataId/Q213205,dcid:wikidataId/Q3271661",15,"[5.15431 SquareKilometer]",5.15431,346.56,295.09,"n",4.76,"2023-01-21,2023-01-23,2023-01-24,2023-01-25,2023-01-26,2023-01-28,2023-01-30,2023-01-31","{'type': 'Polygon', 'coordinates': (((-122.44672381753844, 38.52196905593188), 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2023-02-23","2023-02-23","2023-02-23","P1D",1,1,"[LatLong 35.67612 -119.21464]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06029,dcid:northamerica,dcid:s2CellId/0x80eaf08c00000000,dcid:s2CellId/0x80eaf10000000000,dcid:s2CellId/0x80eaf90000000000,dcid:s2CellId/0x80eaf9ac00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.33702 SquareKilometer]",2.33702,337.32,284.91,"n",8.92,"2023-02-23","{'type': 'MultiPolygon', 'coordinates': [(((-119.23207840138082, 35.556406222206114), (-119.32503466239531, 35.53175350399878), (-119.32503466239531, 35.61180980810941), (-119.23207840138082, 35.63648603631758), (-119.23207840138082, 35.556406222206114)),), (((-119.23207840138082, 35.716489517297106), (-119.13906420284766, 35.74111761532614), (-119.13906420284766, 35.66109096570328), (-119.23207840138082, 35.63648603631758), (-119.23207840138082, 35.716489517297106)),)]}" +"fireEvent/2023-02-17_0x8084c10000000000","FireEvent","FireEvent at L10 S2 Cell 0x8084c10000000000 on 2023-02-17","2023-02-17","2023-02-17","P1D",1,1,"[LatLong 38.80086 -121.95300]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06113,dcid:northamerica,dcid:s2CellId/0x8084c05c00000000,dcid:s2CellId/0x8084c06400000000,dcid:s2CellId/0x8084c10000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.06506 SquareKilometer]",2.06506,342.8,271.77,"n",6.09,"2023-02-17","{'type': 'Polygon', 'coordinates': (((-121.99280779590266, 38.81227184229434), (-121.99280779590266, 38.73689733332498), (-121.90179543138471, 38.764602101272494), (-121.90179543138471, 38.83999267404077), (-121.99280779590266, 38.81227184229434)),)}" +"fireEvent/2023-02-06_0x80845b0000000000","FireEvent","FireEvent at L10 S2 Cell 0x8084430000000000 on 2023-02-06","2023-02-06","2023-02-08","P3D",3,2,"[LatLong 38.59279 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2023-03-26","2023-03-26","2023-03-27","P2D",2,2,"[LatLong 37.58756 -120.84989]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06099,dcid:northamerica,dcid:s2CellId/0x8091010000000000,dcid:s2CellId/0x8091018400000000,dcid:s2CellId/0x8091022c00000000,dcid:s2CellId/0x8091024c00000000,dcid:s2CellId/0x8091030000000000,dcid:s2CellId/0x80911b0000000000,dcid:s2CellId/0x80911b3c00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",7,"[3.26345 SquareKilometer]",3.26345,341.18,293.6,"n",4.45,"2023-03-26,2023-03-27","{'type': 'MultiPolygon', 'coordinates': [(((-120.89582422732902, 37.612902773234545), (-120.80394744373855, 37.6394378546288), (-120.7120023484522, 37.665902427887914), (-120.7120023484522, 37.588619247244885), (-120.80394744373858, 37.56217349052067), (-120.89582422732902, 37.535657341922445), (-120.89582422732902, 37.612902773234545)),), (((-120.61998952842978, 37.61499433591427), (-120.61998952842978, 37.537610243626965), (-120.7120023484522, 37.511254067709565), 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39.74688824941822)),)}" +"fireEvent/2023-01-31_0x80d13f0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d13d0000000000 on 2023-01-31","2023-01-31","2023-02-02","P3D",3,2,"[LatLong 33.64814 -114.63710]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06065,dcid:northamerica,dcid:s2CellId/0x80d13c3400000000,dcid:s2CellId/0x80d13d0000000000,dcid:s2CellId/0x80d13e5400000000,dcid:s2CellId/0x80d13f0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.56762 SquareKilometer]",2.56762,342.18,295.34,"n",6.63,"2023-01-31,2023-02-02","{'type': 'Polygon', 'coordinates': (((-114.52426397902158, 33.71922177939378), (-114.52426397902158, 33.635175624754545), (-114.61928990191176, 33.615140915382845), (-114.71429184441094, 33.59502928061842), (-114.71429184441097, 33.67902618540428), (-114.61928990191176, 33.69916251294337), (-114.52426397902158, 33.71922177939378)),)}" +"fireEvent/2023-03-11_0x80938d0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80938d0000000000 on 2023-03-11","2023-03-11","2023-03-13","P3D",3,2,"[LatLong 36.78493 -120.26858]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06019,dcid:geoId/06039,dcid:northamerica,dcid:s2CellId/0x80938c1c00000000,dcid:s2CellId/0x80938c2400000000,dcid:s2CellId/0x80938c3c00000000,dcid:s2CellId/0x80938d0000000000,dcid:s2CellId/0x80938ea400000000,dcid:s2CellId/0x80938f0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",6,"[3.35804 SquareKilometer]",3.35804,339.25,291.16,"n",7.09,"2023-03-11,2023-03-13","{'type': 'Polygon', 'coordinates': (((-120.34355063422758, 36.83735562297489), (-120.25127284433846, 36.8632307113465), (-120.25127284433846, 36.784876873442236), (-120.25127284433846, 36.706443376822236), (-120.34355063422758, 36.680610078824635), (-120.3435506342276, 36.75902257287933), (-120.34355063422758, 36.83735562297489)),)}" +"fireEvent/2023-02-13_0x8095170000000000","FireEvent","FireEvent at L10 S2 Cell 0x8095170000000000 on 2023-02-13","2023-02-13","2023-02-15","P3D",3,3,"[LatLong 36.56427 -119.18558]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06107,dcid:northamerica,dcid:s2CellId/0x8095170000000000,dcid:s2CellId/0x809517b400000000,dcid:s2CellId/0x809517bc00000000,dcid:s2CellId/0x80953d0000000000,dcid:s2CellId/0x80953d0c00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",5,"[2.28707 SquareKilometer]",2.28707,328.26,287.55,"n",4.19,"2023-02-13,2023-02-14,2023-02-15","{'type': 'Polygon', 'coordinates': (((-119.23207840138082, 36.59139591977724), (-119.13906420284766, 36.616264807982425), (-119.13906420284766, 36.53710170085306), (-119.13906420284766, 36.45785850302791), (-119.23207840138082, 36.433031486044094), (-119.23207840138082, 36.512253642746515), (-119.23207840138082, 36.59139591977724)),)}" +"fireEvent/2023-02-17_0x8085210000000000","FireEvent","FireEvent at L10 S2 Cell 0x8085210000000000 on 2023-02-17","2023-02-17","2023-02-17","P1D",1,1,"[LatLong 38.49527 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SquareKilometer]",2.5781,304.21,280.73,"n",1.05,"2023-01-17","{'type': 'Polygon', 'coordinates': (((-117.07940822560565, 32.39872950090179), (-117.07940822560565, 32.31480850427524), (-116.98524219342079, 32.33651897516448), (-116.98524219342079, 32.42047001297981), (-117.07940822560565, 32.39872950090179)),)}" +"fireEvent/2023-02-20_0x54d10d0000000000","FireEvent","FireEvent at L10 S2 Cell 0x54d10d0000000000 on 2023-02-20","2023-02-20","2023-02-20","P1D",1,1,"[LatLong 41.22318 -123.91735]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06023,dcid:northamerica,dcid:s2CellId/0x54d10d0000000000,dcid:s2CellId/0x54d10ddc00000000,dcid:s2CellId/0x54d10e5c00000000,dcid:s2CellId/0x54d10e6400000000,dcid:s2CellId/0x54d10e6c00000000,dcid:s2CellId/0x54d10e7400000000,dcid:s2CellId/0x54d10f0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",7,"[5.15135 SquareKilometer]",5.15135,354.76,291.81,"n",27.17,"2023-02-20","{'type': 'Polygon', 'coordinates': (((-123.83537783956557, 41.21221558284898), (-123.92787048065873, 41.18143411603011), (-123.99940295441057, 41.234067876044605), (-124.07112954251315, 41.28671512267137), (-123.97844908119757, 41.3177409275206), (-123.90681624160965, 41.26497132163325), (-123.83537783956557, 41.21221558284898)),)}" +"fireEvent/2023-01-23_0x80e97f0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80e97f0000000000 on 2023-01-23","2023-01-23","2023-01-27","P5D",5,5,"[LatLong 34.84521 -119.47016]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06083,dcid:northamerica,dcid:s2CellId/0x80e97e2c00000000,dcid:s2CellId/0x80e97e3400000000,dcid:s2CellId/0x80e97e4c00000000,dcid:s2CellId/0x80e97f0000000000,dcid:s2CellId/0x80e97fa400000000,dcid:s2CellId/0x80e97fac00000000,dcid:s2CellId/0x80e97fb400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",7,"[2.37517 SquareKilometer]",2.37517,350.81,295.74,"n",9.94,"2023-01-23,2023-01-24,2023-01-25,2023-01-26,2023-01-27","{'type': 'Polygon', 'coordinates': (((-119.51077084299, 34.83948061816375), (-119.51077084299, 34.758805996121794), (-119.41793235298398, 34.783376641123795), (-119.41793235298398, 34.86407698186899), (-119.51077084299, 34.83948061816375)),)}" +"fireEvent/2023-03-08_0x8094c90000000000","FireEvent","FireEvent at L10 S2 Cell 0x8094c90000000000 on 2023-03-08","2023-03-08","2023-03-08","P1D",1,1,"[LatLong 36.17639 -119.74260]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06031,dcid:northamerica,dcid:s2CellId/0x8094c90000000000,dcid:s2CellId/0x8094c97400000000,dcid:s2CellId/0x8094c99c00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.29198 SquareKilometer]",2.29198,337.34,278.61,"n",3.48,"2023-03-08","{'type': 'Polygon', 'coordinates': (((-119.78892484955995, 36.20338340883046), (-119.78892484955995, 36.12413379123651), (-119.69626771448172, 36.149347987538164), (-119.69626771448172, 36.228619807644506), (-119.78892484955995, 36.20338340883046)),)}" +"fireEvent/2023-02-13_0x80903f0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80903d0000000000 on 2023-02-13","2023-02-13","2023-02-13","P1D",1,1,"[LatLong 37.73247 -121.35988]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06077,dcid:northamerica,dcid:s2CellId/0x80903c2400000000,dcid:s2CellId/0x80903d0000000000,dcid:s2CellId/0x80903eac00000000,dcid:s2CellId/0x80903f0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.1488 SquareKilometer]",2.1488,340.66,294.6,"n",4.78,"2023-02-13","{'type': 'Polygon', 'coordinates': (((-121.26263661074441, 37.81392448887689), (-121.26263661074441, 37.73708152324151), (-121.35416313685073, 37.710140825873815), (-121.44561789291927, 37.68313095604201), (-121.44561789291927, 37.75993648447068), (-121.35416313685073, 37.78696513099894), (-121.26263661074441, 37.81392448887689)),)}" +"fireEvent/2023-01-23_0x8096d50000000000","FireEvent","FireEvent at L10 S2 Cell 0x8096d50000000000 on 2023-01-23","2023-01-23","2023-01-26","P4D",4,3,"[LatLong 37.79749 -120.11273]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06109,dcid:northamerica,dcid:s2CellId/0x8096d50000000000,dcid:s2CellId/0x8096d57c00000000,dcid:s2CellId/0x8096d59c00000000,dcid:s2CellId/0x80972a9c00000000,dcid:s2CellId/0x80972b0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",5,"[2.18166 SquareKilometer]",2.18166,340.54,287.01,"n",3.78,"2023-01-23,2023-01-25,2023-01-26","{'type': 'Polygon', 'coordinates': (((-120.06652363285929, 37.771745570591364), (-120.15893030899788, 37.74580020187008), (-120.15893030899788, 37.8231938580761), (-120.15893030899788, 37.90050398235046), (-120.06652363285929, 37.926485165746335), (-120.06652363285929, 37.84915723847933), (-120.06652363285929, 37.771745570591364)),)}" +"fireEvent/2023-02-06_0x80d16d0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d16d0000000000 on 2023-02-06","2023-02-06","2023-02-06","P1D",1,1,"[LatLong 33.85517 -114.47674]","dcid:Earth,dcid:country/USA,dcid:geoId/04,dcid:geoId/04012,dcid:northamerica,dcid:s2CellId/0x80d16d0000000000,dcid:s2CellId/0x80d16d1400000000,dcid:s2CellId/0x80d16d2400000000,dcid:s2CellId/0x80d16d3400000000,dcid:s2CellId/0x80d16d4400000000,dcid:s2CellId/0x80d16d6400000000,dcid:s2CellId/0x80d16d6c00000000,dcid:usc/MountainDivision,dcid:usc/WestRegion",7,"[7.67347 SquareKilometer]",7.67347,367.0,357.96,"n",331.14,"2023-02-06","{'type': 'Polygon', 'coordinates': (((-114.52426397902158, 33.88709555416414), (-114.52426397902158, 33.80319522777779), (-114.42921481897034, 33.82320149214735), (-114.42921481897034, 33.90712585436565), (-114.52426397902158, 33.88709555416414)),)}" +"fireEvent/2023-02-06_0x8090530000000000","FireEvent","FireEvent at L10 S2 Cell 0x80904d0000000000 on 2023-02-06","2023-02-06","2023-02-06","P1D",1,1,"[LatLong 37.58483 -121.12521]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06099,dcid:northamerica,dcid:s2CellId/0x80904d0000000000,dcid:s2CellId/0x80904d7c00000000,dcid:s2CellId/0x80904f0000000000,dcid:s2CellId/0x80904f9400000000,dcid:s2CellId/0x8090522400000000,dcid:s2CellId/0x8090530000000000,dcid:s2CellId/0x8091b4dc00000000,dcid:s2CellId/0x8091b50000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",8,"[4.32708 SquareKilometer]",4.32708,338.03,287.68,"n",2.83,"2023-02-06","{'type': 'MultiPolygon', 'coordinates': [(((-120.98763211526173, 37.58629746111499), (-121.07937052658627, 37.55962219720914), (-121.1710388833767, 37.53287726197025), (-121.1710388833767, 37.60998399136611), (-121.1710388833767, 37.68700924798782), (-121.07937052658627, 37.713792107889624), (-121.07937052658627, 37.636747995836885), (-120.98763211526173, 37.6634422122698), (-120.98763211526173, 37.58629746111499)),), (((-121.17103888337672, 37.45568932972217), (-121.26263661074441, 37.4288944060384), (-121.26263661074441, 37.50606293735081), (-121.1710388833767, 37.53287726197025), (-121.17103888337672, 37.45568932972217)),)]}" +"fireEvent/2023-02-12_0x8094290000000000","FireEvent","FireEvent at L10 S2 Cell 0x8094290000000000 on 2023-02-12","2023-02-12","2023-02-12","P1D",1,1,"[LatLong 37.32915 -119.55717]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06039,dcid:northamerica,dcid:s2CellId/0x8094290000000000,dcid:s2CellId/0x8094293c00000000,dcid:s2CellId/0x8094294c00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.23055 SquareKilometer]",2.23055,299.47,274.3,"n",1.16,"2023-02-12","{'type': 'Polygon', 'coordinates': (((-119.60354950502408, 37.35552745160059), (-119.60354950502408, 37.27735895346938), (-119.51077084299, 37.302718937652955), (-119.51077084299, 37.380906429606696), (-119.60354950502408, 37.35552745160059)),)}" +"fireEvent/2023-02-20_0x54d3e30000000000","FireEvent","FireEvent at L10 S2 Cell 0x54d15f0000000000 on 2023-02-20","2023-02-20","2023-02-20","P1D",1,1,"[LatLong 40.93394 -123.88475]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06023,dcid:northamerica,dcid:s2CellId/0x54d15e3400000000,dcid:s2CellId/0x54d15e4c00000000,dcid:s2CellId/0x54d15f0000000000,dcid:s2CellId/0x54d15fb400000000,dcid:s2CellId/0x54d3e10000000000,dcid:s2CellId/0x54d3e1f400000000,dcid:s2CellId/0x54d3e1fc00000000,dcid:s2CellId/0x54d3e21c00000000,dcid:s2CellId/0x54d3e30000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",9,"[6.10311 SquareKilometer]",6.10311,343.04,294.93,"n",46.97,"2023-02-20","{'type': 'Polygon', 'coordinates': (((-124.01120455766761, 40.849147421528926), (-123.91946070957886, 40.87972665089066), (-123.99050231911558, 40.93193999734144), (-123.8985725188299, 40.962569950683395), (-123.8276237504466, 40.91023590743991), (-123.7568661838358, 40.85791688622407), (-123.84860998990712, 40.827527949546344), (-123.94026150527637, 40.79706911642794), (-124.01120455766761, 40.849147421528926)),)}" +"fireEvent/2023-03-25_0x8084c10000000000","FireEvent","FireEvent at L10 S2 Cell 0x8084c10000000000 on 2023-03-25","2023-03-25","2023-03-27","P3D",3,2,"[LatLong 38.80681 -121.96437]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06113,dcid:northamerica,dcid:s2CellId/0x8084c06c00000000,dcid:s2CellId/0x8084c10000000000,dcid:s2CellId/0x8084c25400000000,dcid:s2CellId/0x8084c30000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.06751 SquareKilometer]",2.06751,326.05,293.34,"n",5.44,"2023-03-25,2023-03-27","{'type': 'Polygon', 'coordinates': (((-121.99280779590266, 38.81227184229434), (-121.90179543138471, 38.83999267404077), (-121.90179543138471, 38.764602101272494), (-121.90179543138471, 38.68912724158433), (-121.99280779590266, 38.66143874752344), (-121.99280779590266, 38.73689733332498), (-121.99280779590266, 38.81227184229434)),)}" +"fireEvent/2023-02-17_0x8090990000000000","FireEvent","FireEvent at L10 S2 Cell 0x8090990000000000 on 2023-02-17","2023-02-17","2023-02-19","P3D",3,2,"[LatLong 38.21902 -120.54518]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06009,dcid:northamerica,dcid:s2CellId/0x8090988c00000000,dcid:s2CellId/0x8090989400000000,dcid:s2CellId/0x809098bc00000000,dcid:s2CellId/0x8090990000000000,dcid:s2CellId/0x8090997c00000000,dcid:s2CellId/0x80909b0000000000,dcid:s2CellId/0x80909bd400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",7,"[3.21676 SquareKilometer]",3.21676,339.62,288.39,"n",2.84,"2023-02-17,2023-02-19","{'type': 'Polygon', 'coordinates': (((-120.52790957361556, 38.257532040519735), (-120.52790957361556, 38.18079594647173), (-120.61998952842978, 38.154366127206046), (-120.7120023484522, 38.12786456645258), (-120.7120023484522, 38.2045663181075), (-120.61998952842978, 38.23108510610075), (-120.52790957361556, 38.257532040519735)),)}" +"fireEvent/2023-02-21_0x80d7950000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d7950000000000 on 2023-02-21","2023-02-21","2023-02-21","P1D",1,1,"[LatLong 32.22197 -115.33709]","dcid:Earth,dcid:country/MEX,dcid:northamerica,dcid:s2CellId/0x80d794e400000000,dcid:s2CellId/0x80d7950000000000,dcid:s2CellId/0x80d7951c00000000,dcid:wikidataId/Q1477270,dcid:wikidataId/Q58731",3,"[2.62994 SquareKilometer]",2.62994,341.66,312.54,"n",35.63,"2023-02-21","{'type': 'Polygon', 'coordinates': (((-115.3785719022423, 32.27141580503958), (-115.3785719022423, 32.1865831450277), (-115.28375849518459, 32.20681969840767), (-115.28375849518459, 32.291680994135106), (-115.3785719022423, 32.27141580503958)),)}" +"fireEvent/2023-02-22_0x809aa70000000000","FireEvent","FireEvent at L10 S2 Cell 0x809aa10000000000 on 2023-02-22","2023-02-22","2023-02-22","P1D",1,1,"[LatLong 38.14519 -121.30841]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06077,dcid:northamerica,dcid:s2CellId/0x809aa10000000000,dcid:s2CellId/0x809aa14c00000000,dcid:s2CellId/0x809aa6c400000000,dcid:s2CellId/0x809aa70000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.12355 SquareKilometer]",2.12355,328.55,287.85,"n",2.58,"2023-02-22","{'type': 'Polygon', 'coordinates': (((-121.44561789291927, 38.06633970127007), (-121.44561789291927, 38.14273448666555), (-121.35416313685073, 38.169853815308585), (-121.26263661074441, 38.196903281604015), (-121.26263661074441, 38.12047318795499), (-121.35416313685073, 38.09344131890122), (-121.44561789291927, 38.06633970127007)),)}" +"fireEvent/2023-02-08_0x80848f0000000000","FireEvent","FireEvent at L10 S2 Cell 0x8084850000000000 on 2023-02-08","2023-02-08","2023-02-09","P2D",2,2,"[LatLong 38.93064 -122.22001]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06011,dcid:geoId/06113,dcid:northamerica,dcid:s2CellId/0x8084850000000000,dcid:s2CellId/0x8084858400000000,dcid:s2CellId/0x80848e4c00000000,dcid:s2CellId/0x80848f0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.0522 SquareKilometer]",2.0522,334.11,295.76,"n",13.85,"2023-02-08,2023-02-09","{'type': 'Polygon', 'coordinates': (((-122.17460498684162, 38.83188135199408), (-122.26538872869685, 38.80393792806426), (-122.26538872869685, 38.87909599346539), (-122.26538872869685, 38.95416992095992), (-122.17460498684162, 38.9821450862104), (-122.17460498684162, 38.907055393086274), (-122.17460498684162, 38.83188135199408)),)}" +"fireEvent/2023-01-31_0x8084990000000000","FireEvent","FireEvent at L10 S2 Cell 0x8084970000000000 on 2023-01-31","2023-01-31","2023-02-01","P2D",2,2,"[LatLong 38.90934 -121.99849]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06011,dcid:geoId/06113,dcid:northamerica,dcid:s2CellId/0x8084962400000000,dcid:s2CellId/0x8084963400000000,dcid:s2CellId/0x8084970000000000,dcid:s2CellId/0x8084990000000000,dcid:s2CellId/0x8084997400000000,dcid:s2CellId/0x80849a3c00000000,dcid:s2CellId/0x80849b0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",7,"[4.10807 SquareKilometer]",4.10807,354.76,288.07,"n",7.09,"2023-01-31,2023-02-01","{'type': 'Polygon', 'coordinates': (((-121.99280779590266, 39.0378885979975), (-121.99280779590266, 38.96276770349571), (-121.99280779590266, 38.88756204233199), (-122.08374449567626, 38.85975615372649), (-122.08374449567626, 38.93494605995725), (-122.17460498684162, 38.907055393086274), (-122.17460498684162, 38.9821450862104), (-122.08374449567627, 39.01005140863375), (-121.99280779590266, 39.0378885979975)),)}" +"fireEvent/2023-02-08_0x54d4990000000000","FireEvent","FireEvent at L10 S2 Cell 0x54d4990000000000 on 2023-02-08","2023-02-08","2023-02-11","P4D",4,3,"[LatLong 40.14521 -123.46228]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06105,dcid:northamerica,dcid:s2CellId/0x54d498b400000000,dcid:s2CellId/0x54d498bc00000000,dcid:s2CellId/0x54d4990000000000,dcid:s2CellId/0x54d4a26400000000,dcid:s2CellId/0x54d4a2e400000000,dcid:s2CellId/0x54d4a2ec00000000,dcid:s2CellId/0x54d4a2f400000000,dcid:s2CellId/0x54d4a30000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",8,"[4.93369 SquareKilometer]",4.93369,344.72,294.21,"n",62.5,"2023-02-08,2023-02-10,2023-02-11","{'type': 'Polygon', 'coordinates': (((-123.60320855276242, 40.159382098605334), (-123.51283904569657, 40.188930829812435), (-123.44368098277349, 40.13738797622512), (-123.37470731145442, 40.0858635123691), (-123.4648917259653, 40.056547606398325), (-123.53395808290452, 40.107955842950716), (-123.60320855276242, 40.159382098605334)),)}" +"fireEvent/2023-02-08_0x8083730000000000","FireEvent","FireEvent at L10 S2 Cell 0x8083130000000000 on 2023-02-08","2023-02-08","2023-02-09","P2D",2,2,"[LatLong 39.41636 -122.14622]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06011,dcid:northamerica,dcid:s2CellId/0x8083124400000000,dcid:s2CellId/0x8083130000000000,dcid:s2CellId/0x8083730000000000,dcid:s2CellId/0x8083737400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.0239 SquareKilometer]",2.0239,340.79,292.33,"n",12.31,"2023-02-08,2023-02-09","{'type': 'MultiPolygon', 'coordinates': [(((-122.17460498684162, 39.28165587862677), (-122.26538872869685, 39.25361974158061), (-122.26538872869685, 39.328269615478135), (-122.17460498684162, 39.35632047530068), (-122.17460498684162, 39.28165587862677)),), (((-122.17460498684162, 39.430899396295715), (-122.08374449567626, 39.45889527860518), (-122.08374449567626, 39.38430194908448), (-122.17460498684162, 39.35632047530068), (-122.17460498684162, 39.430899396295715)),)]}" +"fireEvent/2023-01-27_0x80d65f0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d65f0000000000 on 2023-01-27","2023-01-27","2023-01-27","P1D",1,1,"[LatLong 32.62272 -114.54208]","dcid:Earth,dcid:country/USA,dcid:geoId/04,dcid:geoId/04027,dcid:northamerica,dcid:s2CellId/0x80d65e0c00000000,dcid:s2CellId/0x80d65e3400000000,dcid:s2CellId/0x80d65f0000000000,dcid:usc/MountainDivision,dcid:usc/WestRegion",3,"[2.6251 SquareKilometer]",2.6251,367.0,298.2,"n",4.84,"2023-01-27","{'type': 'Polygon', 'coordinates': (((-114.61928990191176, 32.686238988626556), (-114.61928990191176, 32.601380600508776), (-114.52426397902158, 32.62110549021124), (-114.52426397902158, 32.705990765439765), (-114.61928990191176, 32.686238988626556)),)}" +"fireEvent/2023-03-07_0x80a27b0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80a27b0000000000 on 2023-03-07","2023-03-07","2023-03-08","P2D",2,2,"[LatLong 39.61225 -118.55062]","dcid:Earth,dcid:country/USA,dcid:geoId/32,dcid:geoId/32001,dcid:northamerica,dcid:s2CellId/0x80a27a4c00000000,dcid:s2CellId/0x80a27a5400000000,dcid:s2CellId/0x80a27abc00000000,dcid:s2CellId/0x80a27aec00000000,dcid:s2CellId/0x80a27af400000000,dcid:s2CellId/0x80a27afc00000000,dcid:s2CellId/0x80a27b0000000000,dcid:s2CellId/0x80a27b2400000000,dcid:s2CellId/0x80a27b3400000000,dcid:s2CellId/0x80a27b3c00000000,dcid:s2CellId/0x80a27bac00000000,dcid:usc/MountainDivision,dcid:usc/WestRegion",11,"[7.40379 SquareKilometer]",7.40379,352.23,283.64,"n",17.63,"2023-03-07,2023-03-08","{'type': 'Polygon', 'coordinates': (((-118.57979810860881, 39.63771777073999), (-118.57979810860881, 39.56163680447531), (-118.4863962961138, 39.5865742114197), (-118.4863962961138, 39.66266778628226), (-118.57979810860881, 39.63771777073999)),)}" +"fireEvent/2023-01-06_0x80cf5d0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80cf430000000000 on 2023-01-06","2023-01-06","2023-01-06","P1D",1,1,"[LatLong 35.55573 -115.42597]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06071,dcid:northamerica,dcid:s2CellId/0x80cf430000000000,dcid:s2CellId/0x80cf432c00000000,dcid:s2CellId/0x80cf5cac00000000,dcid:s2CellId/0x80cf5d0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.43909 SquareKilometer]",2.43909,343.4,283.86,"n",3.87,"2023-01-06","{'type': 'Polygon', 'coordinates': (((-115.5681083893613, 35.482715048732345), (-115.5681083893613, 35.56460070429775), (-115.47335544292073, 35.58600617105782), (-115.3785719022423, 35.60733295233472), (-115.3785719022423, 35.52540546365499), (-115.47335544292073, 35.50409953767375), (-115.5681083893613, 35.482715048732345)),)}" +"fireEvent/2023-03-26_0x8094790000000000","FireEvent","FireEvent at L10 S2 Cell 0x8094770000000000 on 2023-03-26","2023-03-26","2023-03-27","P2D",2,2,"[LatLong 36.78430 -120.11273]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06019,dcid:northamerica,dcid:s2CellId/0x8094770000000000,dcid:s2CellId/0x809477cc00000000,dcid:s2CellId/0x8094790000000000,dcid:s2CellId/0x809479c400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.24538 SquareKilometer]",2.24538,336.19,293.13,"n",2.34,"2023-03-26,2023-03-27","{'type': 'Polygon', 'coordinates': (((-120.06652363285929, 36.679343295179756), (-120.15893030899788, 36.653672228439554), (-120.15893030899788, 36.732206182076574), (-120.15893030899788, 36.810660560355714), (-120.06652363285929, 36.83637336328723), (-120.06652363285929, 36.75789822396875), (-120.06652363285929, 36.679343295179756)),)}" +"fireEvent/2023-02-14_0x8083250000000000","FireEvent","FireEvent at L10 S2 Cell 0x8083250000000000 on 2023-02-14","2023-02-14","2023-02-17","P4D",4,3,"[LatLong 39.64036 -121.85626]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06007,dcid:northamerica,dcid:s2CellId/0x8083250000000000,dcid:s2CellId/0x8083257c00000000,dcid:s2CellId/0x8083258400000000,dcid:s2CellId/0x8083259c00000000,dcid:s2CellId/0x808325bc00000000,dcid:s2CellId/0x80832f0000000000,dcid:s2CellId/0x80832fbc00000000,dcid:s2CellId/0x80833ac400000000,dcid:s2CellId/0x80833b0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",9,"[4.03851 SquareKilometer]",4.03851,345.96,293.21,"n",15.18,"2023-02-14,2023-02-15,2023-02-17","{'type': 'Polygon', 'coordinates': (((-121.90179543138471, 39.66366133679624), (-121.81070794913828, 39.69147458174664), (-121.71954589932093, 39.71921697980668), (-121.71954589932093, 39.64474111961013), (-121.81070794913828, 39.617012297346776), (-121.81070794913828, 39.54246309252981), (-121.90179543138471, 39.51467741266122), (-121.90179543138471, 39.58921273290782), (-121.90179543138471, 39.66366133679624)),)}" +"fireEvent/2023-02-13_0x80d13b0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d1390000000000 on 2023-02-13","2023-02-13","2023-02-13","P1D",1,1,"[LatLong 33.58312 -114.57178]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06065,dcid:northamerica,dcid:s2CellId/0x80d1390000000000,dcid:s2CellId/0x80d1397c00000000,dcid:s2CellId/0x80d1398400000000,dcid:s2CellId/0x80d13a2c00000000,dcid:s2CellId/0x80d13b0000000000,dcid:s2CellId/0x80d13bd400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",6,"[5.14447 SquareKilometer]",5.14447,355.7,289.95,"n",15.57,"2023-02-13","{'type': 'Polygon', 'coordinates': (((-114.71429184441094, 33.51096047591866), (-114.71429184441094, 33.59502928061842), (-114.61928990191176, 33.615140915382845), (-114.52426397902158, 33.635175624754545), (-114.52426397902158, 33.55105718216274), (-114.61928990191176, 33.53104722357586), (-114.71429184441094, 33.51096047591866)),)}" +"fireEvent/2023-03-07_0x8094a50000000000","FireEvent","FireEvent at L10 S2 Cell 0x8094a50000000000 on 2023-03-07","2023-03-07","2023-03-08","P2D",2,2,"[LatLong 36.20234 -119.99140]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06019,dcid:geoId/06031,dcid:northamerica,dcid:s2CellId/0x8094a4c400000000,dcid:s2CellId/0x8094a50000000000,dcid:s2CellId/0x8094ae5c00000000,dcid:s2CellId/0x8094af0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.28421 SquareKilometer]",2.28421,332.69,294.9,"n",2.39,"2023-03-07,2023-03-08","{'type': 'Polygon', 'coordinates': (((-120.06652363285929, 36.20635508236253), (-119.97405342347365, 36.23182560661413), (-119.97405342347365, 36.15269831052497), (-119.97405342347365, 36.07349347026282), (-120.06652363285929, 36.04806788044641), (-120.06652363285929, 36.12725014536185), (-120.06652363285929, 36.20635508236253)),)}" +"fireEvent/2023-02-20_0x80c3690000000000","FireEvent","FireEvent at L10 S2 Cell 0x80c3690000000000 on 2023-02-20","2023-02-20","2023-02-20","P1D",1,1,"[LatLong 34.42872 -117.37927]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06071,dcid:northamerica,dcid:s2CellId/0x80c3686c00000000,dcid:s2CellId/0x80c3690000000000,dcid:s2CellId/0x80c36f0000000000,dcid:s2CellId/0x80c36f1400000000,dcid:s2CellId/0x80c36f6c00000000,dcid:s2CellId/0x80c3720400000000,dcid:s2CellId/0x80c3730000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",7,"[4.90832 SquareKilometer]",4.90832,355.21,304.63,"n",9.43,"2023-02-20","{'type': 'MultiPolygon', 'coordinates': [(((-117.4556388069492, 34.38460909769327), (-117.4556388069492, 34.46664522632916), (-117.4556388069492, 34.54860813299157), (-117.36164757079143, 34.57137699422246), (-117.36164757079143, 34.489389141032945), (-117.36164757079143, 34.40732785707689), (-117.4556388069492, 34.38460909769327)),), (((-117.54958462854715, 34.525765807815226), (-117.54958462854715, 34.607630244794315), (-117.4556388069492, 34.630497439767254), (-117.4556388069492, 34.54860813299157), (-117.54958462854715, 34.525765807815226)),)]}" 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-114.60147]","dcid:Earth,dcid:country/USA,dcid:geoId/04,dcid:geoId/04027,dcid:northamerica,dcid:s2CellId/0x80d65ea400000000,dcid:s2CellId/0x80d65eac00000000,dcid:s2CellId/0x80d65f0000000000,dcid:usc/MountainDivision,dcid:usc/WestRegion",3,"[2.62533 SquareKilometer]",2.62533,347.6,299.35,"n",28.6,"2023-01-04","{'type': 'Polygon', 'coordinates': (((-114.61928990191176, 32.686238988626556), (-114.61928990191176, 32.601380600508776), (-114.52426397902158, 32.62110549021124), (-114.52426397902158, 32.705990765439765), (-114.61928990191176, 32.686238988626556)),)}" +"fireEvent/2023-02-13_0x8090690000000000","FireEvent","FireEvent at L10 S2 Cell 0x8090650000000000 on 2023-02-13","2023-02-13","2023-02-15","P3D",3,2,"[LatLong 37.97433 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-121.94731]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06113,dcid:northamerica,dcid:s2CellId/0x8084c30000000000,dcid:s2CellId/0x8084c37c00000000,dcid:s2CellId/0x8084c48400000000,dcid:s2CellId/0x8084c50000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.07172 SquareKilometer]",2.07172,327.93,290.03,"n",5.75,"2023-03-08","{'type': 'Polygon', 'coordinates': (((-121.81070794913828, 38.792237598880945), (-121.81070794913828, 38.71674657625675), (-121.90179543138471, 38.68912724158433), (-121.99280779590266, 38.66143874752344), (-121.99280779590266, 38.73689733332498), (-121.90179543138471, 38.764602101272494), (-121.81070794913828, 38.792237598880945)),)}" +"fireEvent/2023-02-22_0x8083690000000000","FireEvent","FireEvent at L10 S2 Cell 0x8083690000000000 on 2023-02-22","2023-02-22","2023-02-22","P1D",1,1,"[LatLong 39.28620 -122.03829]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06011,dcid:northamerica,dcid:s2CellId/0x8083690000000000,dcid:s2CellId/0x8083696400000000,dcid:s2CellId/0x8083696c00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.03153 SquareKilometer]",2.03153,346.39,290.44,"n",6.02,"2023-02-22","{'type': 'Polygon', 'coordinates': (((-122.08374449567626, 39.30962273731574), (-122.08374449567627, 39.23485785874378), (-121.99280779590266, 39.26274043589892), (-121.99280779590266, 39.337520028847024), (-122.08374449567626, 39.30962273731574)),)}" +"fireEvent/2023-02-15_0x8085050000000000","FireEvent","FireEvent at L10 S2 Cell 0x8085010000000000 on 2023-02-15","2023-02-15","2023-02-17","P3D",3,2,"[LatLong 38.37512 -122.31075]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06055,dcid:northamerica,dcid:s2CellId/0x8085010000000000,dcid:s2CellId/0x8085010c00000000,dcid:s2CellId/0x8085050000000000,dcid:s2CellId/0x8085053400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion,dcid:wikidataId/Q213205,dcid:wikidataId/Q3271661",4,"[2.0825 SquareKilometer]",2.0825,331.0,285.88,"n",3.64,"2023-02-15,2023-02-17","{'type': 'MultiPolygon', 'coordinates': [(((-122.17460498684162, 38.379078759434165), (-122.17460498684162, 38.3033208084114), (-122.26538872869685, 38.27549513645561), (-122.26538872869685, 38.35123562794486), (-122.17460498684162, 38.379078759434165)),), (((-122.35609518371197, 38.32332484178081), (-122.35609518371197, 38.39896548537001), (-122.26538872869685, 38.42689363138317), (-122.26538872869685, 38.35123562794486), (-122.35609518371197, 38.32332484178081)),)]}" +"fireEvent/2023-03-18_0x8094c30000000000","FireEvent","FireEvent at L10 S2 Cell 0x8094c30000000000 on 2023-03-18","2023-03-18","2023-03-18","P1D",1,1,"[LatLong 36.35999 -119.64992]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06031,dcid:geoId/06107,dcid:northamerica,dcid:s2CellId/0x8094c30000000000,dcid:s2CellId/0x8094c3f400000000,dcid:s2CellId/0x8094c3fc00000000,dcid:s2CellId/0x8094e26c00000000,dcid:s2CellId/0x8094e30000000000,dcid:s2CellId/0x8094e70000000000,dcid:s2CellId/0x8094e7bc00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",7,"[4.56314 SquareKilometer]",4.56314,352.28,289.38,"n",5.79,"2023-03-18","{'type': 'MultiPolygon', 'coordinates': [(((-119.60354950502408, 36.33300058072124), (-119.69626771448172, 36.30781343778186), (-119.69626771448172, 36.38692856339861), (-119.60354950502408, 36.4121373569022), (-119.60354950502408, 36.33300058072124)),), (((-119.51077084299, 36.59535309054964), (-119.41793235298398, 36.62046053996235), (-119.41793235298398, 36.54144005071771), (-119.51077084299, 36.516353582387346), (-119.51077084299, 36.59535309054964)),), 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-114.85675]","dcid:Earth,dcid:country/MEX,dcid:northamerica,dcid:s2CellId/0x80d6330000000000,dcid:s2CellId/0x80d6337400000000,dcid:s2CellId/0x80d6337c00000000,dcid:s2CellId/0x80d6338c00000000,dcid:s2CellId/0x80d6339400000000,dcid:s2CellId/0x80d633ec00000000,dcid:s2CellId/0x80d633f400000000,dcid:s2CellId/0x80d6343c00000000,dcid:s2CellId/0x80d6344400000000,dcid:s2CellId/0x80d634e400000000,dcid:s2CellId/0x80d6350000000000,dcid:s2CellId/0x80d6351c00000000,dcid:s2CellId/0x80d7b4d400000000,dcid:s2CellId/0x80d7b50000000000,dcid:s2CellId/0x80d7b6cc00000000,dcid:s2CellId/0x80d7b6d400000000,dcid:s2CellId/0x80d7b70000000000,dcid:wikidataId/Q1477270,dcid:wikidataId/Q58731",17,"[11.87124 SquareKilometer]",11.87124,367.0,344.76,"n",83.76,"2023-01-01,2023-01-02,2023-01-03,2023-01-05","{'type': 'MultiPolygon', 'coordinates': [(((-114.99914638140322, 32.26708735189506), (-115.09404500241959, 32.24707198896053), (-115.09404500241959, 32.33199011749119), (-114.99914638140322, 32.35203367788002), 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-120.02030]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06109,dcid:northamerica,dcid:s2CellId/0x8096d70000000000,dcid:s2CellId/0x8096d70c00000000,dcid:s2CellId/0x8096d71400000000,dcid:s2CellId/0x8096d76400000000,dcid:s2CellId/0x8096d76c00000000,dcid:s2CellId/0x8096d77400000000,dcid:s2CellId/0x8096d8e400000000,dcid:s2CellId/0x8096d8fc00000000,dcid:s2CellId/0x8096d90000000000,dcid:s2CellId/0x8096d90c00000000,dcid:s2CellId/0x8096d91400000000,dcid:s2CellId/0x8096d91c00000000,dcid:s2CellId/0x8096d9b400000000,dcid:s2CellId/0x8096d9bc00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",14,"[10.93174 SquareKilometer]",10.93174,352.33,295.8,"n",30.2,"2023-02-10,2023-02-12,2023-02-13","{'type': 'Polygon', 'coordinates': (((-119.881520291274, 37.90086572453295), (-119.881520291274, 37.823418373939894), (-119.97405342347365, 37.79761838238845), (-120.06652363285929, 37.771745570591364), (-120.06652363285929, 37.84915723847933), (-119.97405342347365, 37.87504794829335), 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2023-01-02","2023-01-02","2023-01-02","P1D",1,1,"[LatLong 33.87834 -118.34619]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06037,dcid:northamerica,dcid:s2CellId/0x80c2b50000000000,dcid:s2CellId/0x80c2b53c00000000,dcid:s2CellId/0x80dd345400000000,dcid:s2CellId/0x80dd350000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.46579 SquareKilometer]",2.46579,301.96,283.36,"n",0.85,"2023-01-02","{'type': 'MultiPolygon', 'coordinates': [(((-118.39294170620582, 33.82562180473932), (-118.39294170620582, 33.90767960394744), (-118.29943499572406, 33.9310390246925), (-118.29943499572406, 33.848953872494164), (-118.39294170620582, 33.82562180473932)),), (((-118.20587682407124, 33.8722154192009), (-118.20587682407124, 33.79003345093331), (-118.29943499572406, 33.76679933456592), (-118.29943499572406, 33.848953872494164), (-118.20587682407124, 33.8722154192009)),)]}" +"fireEvent/2023-02-06_0x8091050000000000","FireEvent","FireEvent at L10 S2 Cell 0x8091030000000000 on 2023-02-06","2023-02-06","2023-02-09","P4D",4,3,"[LatLong 37.61405 -120.75798]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06047,dcid:geoId/06099,dcid:northamerica,dcid:s2CellId/0x8091030000000000,dcid:s2CellId/0x8091039c00000000,dcid:s2CellId/0x8091050000000000,dcid:s2CellId/0x8091053400000000,dcid:s2CellId/0x80910f0000000000,dcid:s2CellId/0x80910f4400000000,dcid:s2CellId/0x8091130000000000,dcid:s2CellId/0x8091131400000000,dcid:s2CellId/0x8091133c00000000,dcid:s2CellId/0x8091170000000000,dcid:s2CellId/0x8091179400000000,dcid:s2CellId/0x80913f0000000000,dcid:s2CellId/0x80913fa400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",13,"[6.55418 SquareKilometer]",6.55418,351.31,291.56,"n",4.7,"2023-02-06,2023-02-07,2023-02-09","{'type': 'MultiPolygon', 'coordinates': [(((-120.80394744373858, 37.40739967641065), (-120.80394744373858, 37.484827340180566), (-120.80394744373858, 37.56217349052067), (-120.80394744373855, 37.6394378546288), (-120.7120023484522, 37.665902427887914), 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2023-02-06","2023-02-06","2023-02-07","P2D",2,2,"[LatLong 38.04605 -121.12521]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06077,dcid:northamerica,dcid:s2CellId/0x8090710000000000,dcid:s2CellId/0x809071ec00000000,dcid:s2CellId/0x8090750000000000,dcid:s2CellId/0x8090751400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.13425 SquareKilometer]",2.13425,326.64,277.29,"n",3.01,"2023-02-06,2023-02-07","{'type': 'MultiPolygon', 'coordinates': [(((-121.26263661074441, 38.043960006034105), (-121.26263661074441, 38.12047318795499), (-121.1710388833767, 38.147435026035545), (-121.1710388833767, 38.07090414902015), (-121.26263661074441, 38.043960006034105)),), (((-121.07937052658627, 38.097778093730795), (-121.07937052658627, 38.021146378682644), (-121.1710388833767, 37.994290226708266), (-121.1710388833767, 38.07090414902015), (-121.07937052658627, 38.097778093730795)),)]}" +"fireEvent/2023-03-16_0x80d16f0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d16f0000000000 on 2023-03-16","2023-03-16","2023-03-16","P1D",1,1,"[LatLong 33.90313 -114.42327]","dcid:Earth,dcid:country/USA,dcid:geoId/04,dcid:geoId/04012,dcid:northamerica,dcid:s2CellId/0x80d16e0400000000,dcid:s2CellId/0x80d16e1c00000000,dcid:s2CellId/0x80d16f0000000000,dcid:usc/MountainDivision,dcid:usc/WestRegion",3,"[2.5576 SquareKilometer]",2.5576,345.63,297.05,"n",9.57,"2023-03-16","{'type': 'Polygon', 'coordinates': (((-114.42921481897034, 33.90712585436565), (-114.42921481897034, 33.82320149214735), (-114.33414316655818, 33.843130223746485), (-114.33414316655818, 33.92707848788263), (-114.42921481897034, 33.90712585436565)),)}" +"fireEvent/2023-02-07_0x80c2b10000000000","FireEvent","FireEvent at L10 S2 Cell 0x80c2b10000000000 on 2023-02-07","2023-02-07","2023-02-09","P3D",3,2,"[LatLong 33.93697 -118.43968]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06037,dcid:northamerica,dcid:s2CellId/0x80c2b10000000000,dcid:s2CellId/0x80c2b15400000000,dcid:s2CellId/0x80c2b30000000000,dcid:s2CellId/0x80c2b3fc00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.45871 SquareKilometer]",2.45871,343.53,302.66,"n",13.39,"2023-02-07,2023-02-09","{'type': 'Polygon', 'coordinates': (((-118.4863962961138, 33.966210733729376), (-118.39294170620582, 33.9896678408122), (-118.39294170620582, 33.90767960394744), (-118.39294170620582, 33.82562180473932), (-118.4863962961138, 33.8022194627579), (-118.4863962961138, 33.884249771818084), (-118.4863962961138, 33.966210733729376)),)}" +"fireEvent/2023-02-04_0x80d7a50000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d7a50000000000 on 2023-02-04","2023-02-04","2023-02-06","P3D",3,2,"[LatLong 32.44917 -115.14148]","dcid:Earth,dcid:country/MEX,dcid:northamerica,dcid:s2CellId/0x80d7a50000000000,dcid:s2CellId/0x80d7a5fc00000000,dcid:s2CellId/0x80d7a6cc00000000,dcid:s2CellId/0x80d7a70000000000,dcid:wikidataId/Q1477270,dcid:wikidataId/Q58731",4,"[2.61953 SquareKilometer]",2.61953,333.43,302.76,"n",6.19,"2023-02-04,2023-02-06","{'type': 'Polygon', 'coordinates': (((-115.09404500241959, 32.416843256562224), (-115.18891595142229, 32.396697488156796), (-115.18891595142229, 32.48145723709342), (-115.18891595142229, 32.5661512898709), (-115.09404500241959, 32.58635275421574), (-115.09404500241959, 32.50163095253783), (-115.09404500241959, 32.416843256562224)),)}" +"fireEvent/2023-02-04_0x80da430000000000","FireEvent","FireEvent at L10 S2 Cell 0x80da430000000000 on 2023-02-04","2023-02-04","2023-02-05","P2D",2,2,"[LatLong 33.50381 -116.08867]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06065,dcid:northamerica,dcid:s2CellId/0x80da430000000000,dcid:s2CellId/0x80da436400000000,dcid:s2CellId/0x80da5ce400000000,dcid:s2CellId/0x80da5d0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.54069 SquareKilometer]",2.54069,348.27,307.03,"n",3.33,"2023-02-04,2023-02-05","{'type': 'Polygon', 'coordinates': (((-116.04138886338704, 33.472693644443034), (-116.13594306437999, 33.45139667485967), (-116.13594306437999, 33.53486765773682), (-116.13594306437999, 33.61826847586996), (-116.04138886338704, 33.63961794361283), (-116.04138886338704, 33.55619097791635), (-116.04138886338704, 33.472693644443034)),)}" +"fireEvent/2023-01-25_0x8085070000000000","FireEvent","FireEvent at L10 S2 Cell 0x8085030000000000 on 2023-01-25","2023-01-25","2023-01-28","P4D",4,3,"[LatLong 38.40301 -122.22001]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06055,dcid:geoId/06097,dcid:northamerica,dcid:s2CellId/0x8085030000000000,dcid:s2CellId/0x808503d400000000,dcid:s2CellId/0x8085069400000000,dcid:s2CellId/0x8085070000000000,dcid:s2CellId/0x8085a70000000000,dcid:s2CellId/0x8085a7c400000000,dcid:s2CellId/0x8085aedc00000000,dcid:s2CellId/0x8085af0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion,dcid:wikidataId/Q213205,dcid:wikidataId/Q3271661",8,"[4.16365 SquareKilometer]",4.16365,340.07,291.31,"n",4.05,"2023-01-25,2023-01-26,2023-01-28","{'type': 'MultiPolygon', 'coordinates': [(((-122.26538872869685, 38.35123562794486), (-122.26538872869685, 38.27549513645561), (-122.35609518371197, 38.24760192398743), (-122.35609518371197, 38.32332484178081), (-122.26538872869685, 38.35123562794486)),), (((-122.5372740990185, 38.267301489341314), (-122.44672381753844, 38.295346696588034), (-122.44672381753844, 38.2196414669709), (-122.5372740990185, 38.19161406269585), 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SquareKilometer]",2.23399,345.09,293.0,"n",4.64,"2023-02-18,2023-02-19","{'type': 'MultiPolygon', 'coordinates': [(((-119.69626771448172, 37.173694542784204), (-119.69626771448172, 37.25192602751666), (-119.60354950502408, 37.27735895346938), (-119.60354950502408, 37.19910814898932), (-119.69626771448172, 37.173694542784204)),), (((-119.51077084299, 37.22444893017269), (-119.51077084299, 37.14609669288529), (-119.60354950502408, 37.12077532426294), (-119.60354950502408, 37.19910814898932), (-119.51077084299, 37.22444893017269)),)]}" +"fireEvent/2023-01-02_0x80c2c30000000000","FireEvent","FireEvent at L10 S2 Cell 0x80c2c30000000000 on 2023-01-02","2023-01-02","2023-01-02","P1D",1,1,"[LatLong 34.17095 -118.15908]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06037,dcid:northamerica,dcid:s2CellId/0x80c2c30000000000,dcid:s2CellId/0x80c2c3c400000000,dcid:s2CellId/0x80c2c3cc00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.45141 SquareKilometer]",2.45141,298.34,277.71,"n",0.45,"2023-01-02","{'type': 'Polygon', 'coordinates': (((-118.20587682407124, 34.2002433918674), (-118.20587682407124, 34.118342161375), (-118.1122678531936, 34.14161353880244), (-118.1122678531936, 34.22354120793316), (-118.20587682407124, 34.2002433918674)),)}" +"fireEvent/2023-02-22_0x80d9df0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d9df0000000000 on 2023-02-22","2023-02-22","2023-02-22","P1D",1,1,"[LatLong 32.74909 -115.71018]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06025,dcid:northamerica,dcid:s2CellId/0x80d9df0000000000,dcid:s2CellId/0x80d9dfb400000000,dcid:s2CellId/0x80d9dfbc00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.59256 SquareKilometer]",2.59256,306.94,283.45,"n",1.61,"2023-02-22","{'type': 'Polygon', 'coordinates': (((-115.75751959733307, 32.78083278420529), (-115.75751959733307, 32.69657070793154), (-115.66283001554785, 32.71729983340048), (-115.66283001554785, 32.80158972121298), (-115.75751959733307, 32.78083278420529)),)}" +"fireEvent/2023-03-27_0x809a150000000000","FireEvent","FireEvent at L10 S2 Cell 0x809a150000000000 on 2023-03-27","2023-03-27","2023-03-27","P1D",1,1,"[LatLong 38.59576 -120.49912]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06017,dcid:northamerica,dcid:s2CellId/0x809a14ec00000000,dcid:s2CellId/0x809a150000000000,dcid:s2CellId/0x809a3f0000000000,dcid:s2CellId/0x809a3ff400000000,dcid:s2CellId/0x809a400c00000000,dcid:s2CellId/0x809a410000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",6,"[3.18127 SquareKilometer]",3.18127,339.22,291.42,"n",5.62,"2023-03-27","{'type': 'Polygon', 'coordinates': (((-120.52790957361556, 38.56362878155043), (-120.52790957361556, 38.63993981922657), (-120.61998952842978, 38.613410423372706), (-120.61998952842978, 38.689619841758045), (-120.52790957361556, 38.716165110244546), (-120.43576307692442, 38.74263759514314), (-120.43576307692442, 38.66639654013268), (-120.43576307692442, 38.590069533051576), (-120.52790957361556, 38.56362878155043)),)}" +"fireEvent/2023-03-02_0x8084970000000000","FireEvent","FireEvent at L10 S2 Cell 0x8084970000000000 on 2023-03-02","2023-03-02","2023-03-02","P1D",1,1,"[LatLong 38.91128 -122.03829]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06011,dcid:geoId/06113,dcid:northamerica,dcid:s2CellId/0x8084970000000000,dcid:s2CellId/0x8084978c00000000,dcid:s2CellId/0x8084983c00000000,dcid:s2CellId/0x8084990000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.05367 SquareKilometer]",2.05367,336.55,286.93,"n",2.33,"2023-03-02","{'type': 'Polygon', 'coordinates': (((-121.99280779590266, 38.88756204233199), (-122.08374449567626, 38.85975615372649), (-122.08374449567626, 38.93494605995725), (-122.08374449567627, 39.01005140863375), (-121.99280779590266, 39.0378885979975), (-121.99280779590266, 38.96276770349571), (-121.99280779590266, 38.88756204233199)),)}" +"fireEvent/2023-02-13_0x809a150000000000","FireEvent","FireEvent at L10 S2 Cell 0x809a150000000000 on 2023-02-13","2023-02-13","2023-02-15","P3D",3,2,"[LatLong 38.59868 -120.52215]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06017,dcid:northamerica,dcid:s2CellId/0x809a14d400000000,dcid:s2CellId/0x809a14dc00000000,dcid:s2CellId/0x809a150000000000,dcid:s2CellId/0x809a152400000000,dcid:s2CellId/0x809a154400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",5,"[2.123 SquareKilometer]",2.123,334.54,295.88,"n",22.5,"2023-02-13,2023-02-15","{'type': 'Polygon', 'coordinates': (((-120.52790957361556, 38.63993981922657), (-120.52790957361556, 38.56362878155043), (-120.43576307692442, 38.590069533051576), (-120.43576307692442, 38.66639654013268), (-120.52790957361556, 38.63993981922657)),)}" +"fireEvent/2023-01-24_0x80d7c70000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d7b90000000000 on 2023-01-24","2023-01-24","2023-01-27","P4D",4,4,"[LatLong 32.27950 -115.14148]","dcid:Earth,dcid:country/MEX,dcid:northamerica,dcid:s2CellId/0x80d7b90000000000,dcid:s2CellId/0x80d7b94400000000,dcid:s2CellId/0x80d7c62400000000,dcid:s2CellId/0x80d7c70000000000,dcid:s2CellId/0x80d7cb0000000000,dcid:s2CellId/0x80d7cb0400000000,dcid:s2CellId/0x80d7ce4c00000000,dcid:s2CellId/0x80d7cf0000000000,dcid:wikidataId/Q1477270,dcid:wikidataId/Q58731",8,"[5.27353 SquareKilometer]",5.27353,341.03,300.06,"n",10.57,"2023-01-24,2023-01-25,2023-01-26,2023-01-27","{'type': 'MultiPolygon', 'coordinates': [(((-115.18891595142229, 32.2269827091063), (-115.18891595142229, 32.31187249427941), (-115.09404500241959, 32.33199011749119), (-115.09404500241959, 32.24707198896053), (-115.09404500241959, 32.16208932703202), (-115.18891595142229, 32.14202858870148), (-115.18891595142229, 32.2269827091063)),), (((-114.90422082333554, 32.287028613932726), (-114.90422082333554, 32.20198930823536), (-114.99914638140322, 32.182076294930475), (-114.99914638140322, 32.26708735189506), 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2023-03-03","2023-03-03","2023-03-04","P2D",2,2,"[LatLong 32.87473 -115.52074]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06025,dcid:northamerica,dcid:s2CellId/0x80d75d0000000000,dcid:s2CellId/0x80d75df400000000,dcid:s2CellId/0x80d7690000000000,dcid:s2CellId/0x80d7694400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.59547 SquareKilometer]",2.59547,338.41,304.97,"n",25.48,"2023-03-03,2023-03-04","{'type': 'MultiPolygon', 'coordinates': [(((-115.3785719022423, 32.86341617929968), (-115.3785719022423, 32.779043713972804), (-115.47335544292073, 32.75853653053172), (-115.47335544292073, 32.84288161267371), (-115.3785719022423, 32.86341617929968)),), (((-115.5681083893613, 32.82227272901859), (-115.5681083893613, 32.90652316752118), (-115.47335544292073, 32.92715937663604), (-115.47335544292073, 32.84288161267371), (-115.5681083893613, 32.82227272901859)),)]}" +"fireEvent/2023-02-15_0x8095b50000000000","FireEvent","FireEvent at L10 S2 Cell 0x8095b10000000000 on 2023-02-15","2023-02-15","2023-02-21","P7D",7,6,"[LatLong 37.00267 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SquareKilometer]",2.44911,321.27,273.97,"n",2.81,"2023-01-28","{'type': 'Polygon', 'coordinates': (((-117.64348435403741, 34.502850247756115), (-117.64348435403741, 34.42093763167103), (-117.54958462854715, 34.4438279801098), (-117.54958462854715, 34.525765807815226), (-117.64348435403741, 34.502850247756115)),)}" +"fireEvent/2023-03-26_0x8090750000000000","FireEvent","FireEvent at L10 S2 Cell 0x8090750000000000 on 2023-03-26","2023-03-26","2023-03-27","P2D",2,2,"[LatLong 38.09571 -121.21685]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06077,dcid:northamerica,dcid:s2CellId/0x8090750000000000,dcid:s2CellId/0x8090757400000000,dcid:s2CellId/0x809aa0cc00000000,dcid:s2CellId/0x809aa0d400000000,dcid:s2CellId/0x809aa10000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",5,"[3.19035 SquareKilometer]",3.19035,334.35,294.95,"n",2.22,"2023-03-26,2023-03-27","{'type': 'MultiPolygon', 'coordinates': [(((-121.1710388833767, 38.147435026035545), (-121.1710388833767, 38.07090414902015), 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(-118.96248174499246, 41.85528577165443), (-119.0267373723986, 41.91291619013493)),)}" +"fireEvent/2023-01-23_0x80853f0000000000","FireEvent","FireEvent at L10 S2 Cell 0x8085390000000000 on 2023-01-23","2023-01-23","2023-01-23","P1D",1,1,"[LatLong 38.28629 -121.85626]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06095,dcid:northamerica,dcid:s2CellId/0x8085390000000000,dcid:s2CellId/0x808539ec00000000,dcid:s2CellId/0x80853f0000000000,dcid:s2CellId/0x80853ffc00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion,dcid:wikidataId/Q213205,dcid:wikidataId/Q3271661",4,"[2.09856 SquareKilometer]",2.09856,297.63,277.58,"n",0.5,"2023-01-23","{'type': 'Polygon', 'coordinates': (((-121.99280779590266, 38.20693488934502), (-121.99280779590266, 38.282892940885574), (-121.90179543138471, 38.31049689758648), (-121.81070794913828, 38.33803225682059), (-121.81070794913828, 38.26203923045015), (-121.90179543138471, 38.23452130172675), (-121.99280779590266, 38.20693488934502)),)}" 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-117.59654]","dcid:Earth,dcid:country/USA,dcid:geoId/32,dcid:geoId/32013,dcid:northamerica,dcid:s2CellId/0x80a0e90000000000,dcid:s2CellId/0x80a0e92c00000000,dcid:s2CellId/0x80a0e93400000000,dcid:usc/MountainDivision,dcid:usc/WestRegion",3,"[2.03742 SquareKilometer]",2.03742,343.23,296.22,"n",20.01,"2023-03-17","{'type': 'Polygon', 'coordinates': (((-117.64348435403741, 41.1646741177087), (-117.64348435403741, 41.090082392578815), (-117.54958462854715, 41.11439677948815), (-117.54958462854715, 41.18899708980876), (-117.64348435403741, 41.1646741177087)),)}" +"fireEvent/2023-02-18_0x80ea5b0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80ea5b0000000000 on 2023-02-18","2023-02-18","2023-02-18","P1D",1,1,"[LatLong 35.47196 -119.19139]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06029,dcid:northamerica,dcid:s2CellId/0x80ea5a3400000000,dcid:s2CellId/0x80ea5a3c00000000,dcid:s2CellId/0x80ea5a4c00000000,dcid:s2CellId/0x80ea5b0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[3.52191 SquareKilometer]",3.52191,301.47,271.49,"n",1.49,"2023-02-18","{'type': 'Polygon', 'coordinates': (((-119.23207840138082, 35.47625041156115), (-119.23207840138082, 35.396018943340835), (-119.13906420284766, 35.420553079599216), (-119.13906420284766, 35.50080836032674), (-119.23207840138082, 35.47625041156115)),)}" +"fireEvent/2023-03-25_0x8094e70000000000","FireEvent","FireEvent at L10 S2 Cell 0x8094e30000000000 on 2023-03-25","2023-03-25","2023-03-27","P3D",3,2,"[LatLong 36.53855 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'Polygon', 'coordinates': (((-121.1710388833767, 39.66023770903055), (-121.1710388833767, 39.58541818705814), (-121.26263661074441, 39.55815975879043), (-121.35416313685073, 39.53082922928807), (-121.35416313685073, 39.60562152971405), (-121.26263661074441, 39.63296572194452), (-121.1710388833767, 39.66023770903055)),)}" +"fireEvent/2023-02-14_0x8094c10000000000","FireEvent","FireEvent at L10 S2 Cell 0x8094930000000000 on 2023-02-14","2023-02-14","2023-02-16","P3D",3,2,"[LatLong 36.49371 -119.82944]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06019,dcid:geoId/06031,dcid:northamerica,dcid:s2CellId/0x8094928c00000000,dcid:s2CellId/0x8094930000000000,dcid:s2CellId/0x8094c10000000000,dcid:s2CellId/0x8094c16400000000,dcid:s2CellId/0x8094c21400000000,dcid:s2CellId/0x8094c30000000000,dcid:s2CellId/0x8094e70000000000,dcid:s2CellId/0x8094e7b400000000,dcid:s2CellId/0x8094ecdc00000000,dcid:s2CellId/0x8094ecf400000000,dcid:s2CellId/0x8094ed0000000000,dcid:s2CellId/0x8094ef0000000000,dcid:s2CellId/0x8094ef3c00000000,dcid:s2CellId/0x8094ef4400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",14,"[9.10435 SquareKilometer]",9.10435,332.38,292.18,"n",11.85,"2023-02-14,2023-02-16","{'type': 'MultiPolygon', 'coordinates': [(((-119.78892484955995, 36.36164840353892), (-119.69626771448172, 36.38692856339861), (-119.60354950502408, 36.4121373569022), (-119.60354950502408, 36.33300058072124), (-119.69626771448172, 36.30781343778186), (-119.78892484955995, 36.28255505122062), 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-115.42597]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06025,dcid:northamerica,dcid:s2CellId/0x80d7690000000000,dcid:s2CellId/0x80d7692400000000,dcid:s2CellId/0x80d7692c00000000,dcid:s2CellId/0x80d7693c00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[3.89745 SquareKilometer]",3.89745,349.12,308.56,"n",47.43,"2023-01-19","{'type': 'Polygon', 'coordinates': (((-115.47335544292073, 32.84288161267371), (-115.47335544292073, 32.75853653053172), (-115.3785719022423, 32.779043713972804), (-115.3785719022423, 32.86341617929968), (-115.47335544292073, 32.84288161267371)),)}" +"fireEvent/2023-02-20_0x80833b0000000000","FireEvent","FireEvent at L10 S2 Cell 0x8083250000000000 on 2023-02-20","2023-02-20","2023-02-22","P3D",3,3,"[LatLong 39.64036 -121.85626]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06007,dcid:northamerica,dcid:s2CellId/0x8083250000000000,dcid:s2CellId/0x8083259400000000,dcid:s2CellId/0x808326d400000000,dcid:s2CellId/0x8083270000000000,dcid:s2CellId/0x8083272c00000000,dcid:s2CellId/0x80833adc00000000,dcid:s2CellId/0x80833b0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",7,"[3.02584 SquareKilometer]",3.02584,352.15,292.84,"n",11.25,"2023-02-20,2023-02-21,2023-02-22","{'type': 'Polygon', 'coordinates': (((-121.81070794913828, 39.54246309252981), (-121.90179543138471, 39.51467741266122), (-121.90179543138471, 39.58921273290782), (-121.90179543138471, 39.66366133679624), (-121.90179543138471, 39.73802301630229), (-121.81070794913828, 39.76584973823246), (-121.81070794913828, 39.69147458174664), (-121.81070794913828, 39.617012297346776), (-121.81070794913828, 39.54246309252981)),)}" +"fireEvent/2023-01-02_0x80c49d0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80c49d0000000000 on 2023-01-02","2023-01-02","2023-01-02","P1D",1,1,"[LatLong 34.61964 -117.09706]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06071,dcid:northamerica,dcid:s2CellId/0x80c49cbc00000000,dcid:s2CellId/0x80c49cc400000000,dcid:s2CellId/0x80c49d0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.45544 SquareKilometer]",2.45544,298.73,274.81,"n",0.82,"2023-01-02","{'type': 'Polygon', 'coordinates': (((-117.17353159273283, 34.61669341815171), (-117.17353159273283, 34.53465606824912), (-117.07940822560565, 34.557178631747604), (-117.07940822560565, 34.6392405323175), (-117.17353159273283, 34.61669341815171)),)}" +"fireEvent/2023-01-05_0x80d79f0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d7750000000000 on 2023-01-05","2023-01-05","2023-01-07","P3D",3,3,"[LatLong 32.59005 -115.34895]","dcid:Earth,dcid:country/MEX,dcid:northamerica,dcid:s2CellId/0x80d7744400000000,dcid:s2CellId/0x80d7750000000000,dcid:s2CellId/0x80d79d0000000000,dcid:s2CellId/0x80d79d8400000000,dcid:s2CellId/0x80d79f0000000000,dcid:s2CellId/0x80d79f4400000000,dcid:wikidataId/Q1477270,dcid:wikidataId/Q58731",6,"[3.92016 SquareKilometer]",3.92016,340.55,292.36,"n",4.52,"2023-01-05,2023-01-06,2023-01-07","{'type': 'Polygon', 'coordinates': (((-115.3785719022423, 32.44088749173266), (-115.47335544292073, 32.42049183911604), (-115.47335544292073, 32.505101778412154), (-115.3785719022423, 32.52552561351063), (-115.3785719022423, 32.610097988335994), (-115.28375849518459, 32.63047572713295), (-115.28375849518459, 32.54587551383132), (-115.28375849518459, 32.46120935428951), (-115.3785719022423, 32.44088749173266)),)}" +"fireEvent/2023-03-15_0x80835d0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80835d0000000000 on 2023-03-15","2023-03-15","2023-03-16","P2D",2,2,"[LatLong 39.22798 -121.90749]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06011,dcid:northamerica,dcid:s2CellId/0x80835c0c00000000,dcid:s2CellId/0x80835d0000000000,dcid:s2CellId/0x80835f0000000000,dcid:s2CellId/0x80835f3c00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",4,"[2.04312 SquareKilometer]",2.04312,337.62,290.53,"n",4.12,"2023-03-15,2023-03-16","{'type': 'Polygon', 'coordinates': (((-121.99280779590266, 39.26274043589892), (-121.90179543138471, 39.29055326593883), (-121.90179543138471, 39.21567320309416), (-121.90179543138471, 39.14070749598967), (-121.99280779590266, 39.11292450020048), (-121.99280779590266, 39.18787518661573), (-121.99280779590266, 39.26274043589892)),)}" +"fireEvent/2023-02-02_0x8090a50000000000","FireEvent","FireEvent at L10 S2 Cell 0x8090a50000000000 on 2023-02-02","2023-02-02","2023-02-02","P1D",1,1,"[LatLong 38.25870 -120.38967]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06009,dcid:northamerica,dcid:s2CellId/0x8090a50000000000,dcid:s2CellId/0x8090a58400000000,dcid:s2CellId/0x8090a59c00000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.14773 SquareKilometer]",2.14773,297.02,274.4,"n",0.59,"2023-02-02","{'type': 'Polygon', 'coordinates': (((-120.43576307692442, 38.283906850968414), (-120.43576307692442, 38.20715375350994), (-120.3435506342276, 38.23343927918502), (-120.3435506342276, 38.310209268657324), (-120.43576307692442, 38.283906850968414)),)}" +"fireEvent/2023-03-09_0x80eb050000000000","FireEvent","FireEvent at L10 S2 Cell 0x80eb050000000000 on 2023-03-09","2023-03-09","2023-03-09","P1D",1,1,"[LatLong 35.58257 -119.52817]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06029,dcid:northamerica,dcid:s2CellId/0x80eb046c00000000,dcid:s2CellId/0x80eb047400000000,dcid:s2CellId/0x80eb050000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.33127 SquareKilometer]",2.33127,310.66,274.9,"n",1.96,"2023-03-09","{'type': 'Polygon', 'coordinates': (((-119.60354950502408, 35.617265464719935), (-119.60354950502408, 35.5373559257604), (-119.51077084299, 35.56224449162536), (-119.51077084299, 35.642177706706846), (-119.60354950502408, 35.617265464719935)),)}" +"fireEvent/2023-02-19_0x80d7650000000000","FireEvent","FireEvent at L10 S2 Cell 0x80d7650000000000 on 2023-02-19","2023-02-19","2023-02-20","P2D",2,2,"[LatLong 32.70606 -115.52074]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06025,dcid:northamerica,dcid:s2CellId/0x80d7650000000000,dcid:s2CellId/0x80d7650400000000,dcid:s2CellId/0x80d7658c00000000,dcid:s2CellId/0x80d765ac00000000,dcid:s2CellId/0x80d765f400000000,dcid:s2CellId/0x80d76f0000000000,dcid:s2CellId/0x80d76f6400000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",7,"[3.89998 SquareKilometer]",3.89998,352.22,313.34,"n",22.51,"2023-02-19,2023-02-20","{'type': 'Polygon', 'coordinates': (((-115.5681083893613, 32.65357093757281), (-115.5681083893613, 32.737955172648526), (-115.47335544292073, 32.75853653053172), (-115.3785719022423, 32.779043713972804), (-115.3785719022423, 32.69460416981107), (-115.47335544292073, 32.67412456932842), (-115.5681083893613, 32.65357093757281)),)}" +"fireEvent/2023-02-12_0x80921d0000000000","FireEvent","FireEvent at L10 S2 Cell 0x80921d0000000000 on 2023-02-12","2023-02-12","2023-02-12","P1D",1,1,"[LatLong 36.79488 -121.35988]","dcid:Earth,dcid:country/USA,dcid:geoId/06,dcid:geoId/06069,dcid:northamerica,dcid:s2CellId/0x80921c1c00000000,dcid:s2CellId/0x80921c2400000000,dcid:s2CellId/0x80921d0000000000,dcid:usc/PacificDivision,dcid:usc/WestRegion",3,"[2.20223 SquareKilometer]",2.20223,340.59,291.48,"n",9.06,"2023-02-12","{'type': 'Polygon', 'coordinates': (((-121.44561789291927, 36.83295988739003), (-121.44561789291927, 36.75519608151651), (-121.35416313685073, 36.78196379162144), (-121.35416313685073, 36.85974897343489), (-121.44561789291927, 36.83295988739003)),)}" diff --git a/scripts/earthengine/test_data/sample_fires_events.tmcf b/scripts/earthengine/test_data/sample_fires_events.tmcf new file mode 100644 index 0000000000..8ecbf97c53 --- /dev/null +++ b/scripts/earthengine/test_data/sample_fires_events.tmcf @@ -0,0 +1,15 @@ +Node: E:Events->E0 +dcid: C:Events->dcid +typeOf: C:Events->typeOf +name: C:Events->name +startDate: C:Events->startDate +endDate: C:Events->endDate +observationPeriod: C:Events->observationPeriod +numberOfDays: C:Events->numberOfDays +startLocation: C:Events->startLocation +affectedPlace: C:Events->affectedPlace +area: C:Events->area +confidence: C:Events->confidence +frp: C:Events->frp +observationDate: C:Events->observationDate +geoJsonCoordinatesDP1: C:Events->geoJsonCoordinatesDP1 \ No newline at end of file diff --git a/scripts/earthengine/test_data/sample_fires_input.csv b/scripts/earthengine/test_data/sample_fires_input.csv new file mode 100644 index 0000000000..f1d3a6ed7e --- /dev/null +++ b/scripts/earthengine/test_data/sample_fires_input.csv @@ -0,0 +1,2846 @@ +latitude,longitude,bright_ti4,scan,track,acq_date,acq_time,satellite,instrument,confidence,version,bright_ti5,frp,daynight +40.50785,-122.40483,329.72,0.5,0.41,2023-01-01,2125,N,VIIRS,n,2.0NRT,285.15,4.68,D +39.15154,-122.65713,301.45,0.39,0.36,2023-01-01,1004,N,VIIRS,n,2.0NRT,274.29,0.82,N +32.33466,-114.90607,350.27,0.33,0.55,2023-01-01,2122,N,VIIRS,n,2.0NRT,290.71,4.61,D +37.56531,-120.96957,335.37,0.53,0.42,2023-01-01,2122,N,VIIRS,n,2.0NRT,287.82,6.25,D +37.56533,-120.97165,328.62,0.53,0.42,2023-01-01,2122,N,VIIRS,n,2.0NRT,287.04,6.29,D +40.50793,-122.40673,328.22,0.5,0.41,2023-01-01,2125,N,VIIRS,n,2.0NRT,285.36,2.7,D +38.62836,-123.32542,327.13,0.39,0.36,2023-01-01,1004,N,VIIRS,n,2.0NRT,280.42,7.14,N +38.62769,-123.32096,296.41,0.39,0.36,2023-01-01,1004,N,VIIRS,n,2.0NRT,277.48,2.73,N +38.072,-122.13904,306.65,0.38,0.36,2023-01-01,1004,N,VIIRS,n,2.0NRT,288.49,1.62,N 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dcs:Count_FireEvent +observationAbout: C:EventPlaces->observationAbout +observationDate: C:EventPlaces->observationDate +observationPeriod: C:EventPlaces->observationPeriod +value: C:EventPlaces->count \ No newline at end of file diff --git a/scripts/earthengine/test_data/sample_fires_svobs.csv b/scripts/earthengine/test_data/sample_fires_svobs.csv new file mode 100644 index 0000000000..1d37bb6b8b --- /dev/null +++ b/scripts/earthengine/test_data/sample_fires_svobs.csv @@ -0,0 +1,303 @@ +"dcid","observationDate","affectedPlace","area","bright_ti4","bright_ti5","confidence","frp" +"fireEvent/2023-01-31_0x80837b0000000000","2023-01-31","dcid:s2CellId/0x808362bc00000000,dcid:s2CellId/0x8083630000000000,dcid:s2CellId/0x80837a5400000000,dcid:s2CellId/0x80837b0000000000",2.039,335.81,288.82,"n",2.01 +"fireEvent/2023-02-10_0x80c3570000000000","2023-02-10","dcid:s2CellId/0x80c3570000000000,dcid:s2CellId/0x80c3576c00000000,dcid:s2CellId/0x80c3577400000000",2.472,333.96,286.31,"n",4.91 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+"fireEvent/2023-01-25_0x80ec050000000000","2023-01-25","dcid:s2CellId/0x80ec050000000000,dcid:s2CellId/0x80ec057c00000000,dcid:s2CellId/0x80ec0e8400000000,dcid:s2CellId/0x80ec0f0000000000",2.349,329.35,294.47,"n",2.69 +"fireEvent/2023-02-14_0x8094a50000000000","2023-02-14","dcid:s2CellId/0x8094a45c00000000,dcid:s2CellId/0x8094a50000000000,dcid:s2CellId/0x8094af0000000000,dcid:s2CellId/0x8094af3400000000,dcid:s2CellId/0x8094b27400000000,dcid:s2CellId/0x8094b30000000000",3.428,335.21,293.78,"n",5.68 +"fireEvent/2023-01-31_0x8094290000000000","2023-01-31","dcid:s2CellId/0x8094286400000000,dcid:s2CellId/0x8094287c00000000,dcid:s2CellId/0x8094290000000000",2.228,337.58,283.46,"n",5.27 +"fireEvent/2023-01-31_0x8094290000000000","2023-02-01","dcid:s2CellId/0x8094289400000000,dcid:s2CellId/0x8094290000000000",1.114,337.34,283.02,"n",4.45 +"fireEvent/2023-01-31_0x8094290000000000","2023-02-02","dcid:s2CellId/0x809428c400000000,dcid:s2CellId/0x8094290000000000",1.115,311.76,272.21,"n",1.21 +"fireEvent/2023-01-31_0x8094290000000000","2023-02-04","dcid:s2CellId/0x8094250000000000,dcid:s2CellId/0x809425b400000000,dcid:s2CellId/0x809428bc00000000,dcid:s2CellId/0x8094290000000000",2.23,338.9,268.73,"n",5.43 +"fireEvent/2023-03-03_0x80948f0000000000","2023-03-03","dcid:s2CellId/0x8094850000000000,dcid:s2CellId/0x8094859c00000000,dcid:s2CellId/0x80948e4400000000,dcid:s2CellId/0x80948f0000000000",2.265,339.48,291.4,"n",5.26 +"fireEvent/2023-02-22_0x809ab50000000000","2023-02-22","dcid:s2CellId/0x809ab45400000000,dcid:s2CellId/0x809ab50000000000,dcid:s2CellId/0x809ac90000000000,dcid:s2CellId/0x809ac97c00000000",2.106,332.24,288.45,"n",4.85 +"fireEvent/2023-03-15_0x80835d0000000000","2023-03-15","dcid:s2CellId/0x80835c0c00000000,dcid:s2CellId/0x80835d0000000000",1.021,337.62,290.53,"n",4.12 +"fireEvent/2023-03-15_0x80835d0000000000","2023-03-16","dcid:s2CellId/0x80835f3c00000000,dcid:s2CellId/0x80835f0000000000",1.023,326.55,288.36,"n",2.72 +"fireEvent/2023-02-02_0x8090a50000000000","2023-02-02","dcid:s2CellId/0x8090a50000000000,dcid:s2CellId/0x8090a58400000000,dcid:s2CellId/0x8090a59c00000000",2.148,297.02,274.4,"n",0.59 +"fireEvent/2023-02-08_0x8094250000000000","2023-02-08","dcid:s2CellId/0x8094244c00000000,dcid:s2CellId/0x8094250000000000,dcid:s2CellId/0x80942eb400000000,dcid:s2CellId/0x80942f0000000000",2.231,346.83,291.85,"n",10.8 +"fireEvent/2023-02-08_0x8094250000000000","2023-02-09","dcid:s2CellId/0x80942ea400000000,dcid:s2CellId/0x80942eac00000000,dcid:s2CellId/0x80942f0000000000",2.232,335.27,294.81,"n",10.98 +"fireEvent/2023-02-15_0x80845b0000000000","2023-02-15","dcid:s2CellId/0x80845b5400000000,dcid:s2CellId/0x80845b0000000000",1.03,334.51,291.53,"n",2.63 +"fireEvent/2023-02-15_0x80845b0000000000","2023-02-17","dcid:s2CellId/0x8084450000000000,dcid:s2CellId/0x8084454c00000000,dcid:s2CellId/0x8084570000000000,dcid:s2CellId/0x8084572400000000",2.065,336.42,291.42,"n",3.5 +"fireEvent/2023-01-31_0x809cc10000000000","2023-01-31","dcid:s2CellId/0x809cc0dc00000000,dcid:s2CellId/0x809cc10000000000,dcid:s2CellId/0x809cc12400000000,dcid:s2CellId/0x809cc15400000000,dcid:s2CellId/0x809cc15c00000000",4.065,355.49,291.3,"n",40.6 +"fireEvent/2023-01-31_0x809cc10000000000","2023-02-01","dcid:s2CellId/0x809cc10000000000,dcid:s2CellId/0x809cc12c00000000,dcid:s2CellId/0x809cc13400000000",2.033,367.0,291.92,"n",25.99 +"fireEvent/2023-01-31_0x8084990000000000","2023-01-31","dcid:s2CellId/0x8084962400000000,dcid:s2CellId/0x8084963400000000,dcid:s2CellId/0x8084970000000000,dcid:s2CellId/0x8084990000000000,dcid:s2CellId/0x8084997400000000",3.082,354.76,288.07,"n",7.09 +"fireEvent/2023-01-31_0x8084990000000000","2023-02-01","dcid:s2CellId/0x80849a3c00000000,dcid:s2CellId/0x80849b0000000000",1.026,326.99,269.53,"n",3.74 +"fireEvent/2023-02-08_0x54d4990000000000","2023-02-08","dcid:s2CellId/0x54d498b400000000,dcid:s2CellId/0x54d498bc00000000,dcid:s2CellId/0x54d4990000000000",1.975,344.72,294.21,"n",62.5 +"fireEvent/2023-02-08_0x54d4990000000000","2023-02-10","dcid:s2CellId/0x54d4a2e400000000,dcid:s2CellId/0x54d4a2ec00000000,dcid:s2CellId/0x54d4a2f400000000,dcid:s2CellId/0x54d4a30000000000",2.958,316.49,275.21,"n",2.37 +"fireEvent/2023-02-08_0x54d4990000000000","2023-02-11","dcid:s2CellId/0x54d4a26400000000,dcid:s2CellId/0x54d4a30000000000",0.987,297.05,272.41,"n",2.11 +"fireEvent/2023-02-19_0x80d7650000000000","2023-02-19","dcid:s2CellId/0x80d7650000000000,dcid:s2CellId/0x80d7650400000000,dcid:s2CellId/0x80d765ac00000000",2.6,328.43,279.72,"n",6.57 +"fireEvent/2023-02-19_0x80d7650000000000","2023-02-20","dcid:s2CellId/0x80d7650000000000,dcid:s2CellId/0x80d7658c00000000,dcid:s2CellId/0x80d765f400000000,dcid:s2CellId/0x80d76f0000000000,dcid:s2CellId/0x80d76f6400000000",3.899,352.22,313.34,"n",22.51 +"fireEvent/2023-02-08_0x8083730000000000","2023-02-08","dcid:s2CellId/0x8083737400000000,dcid:s2CellId/0x8083730000000000",1.013,331.45,292.33,"n",2.4 +"fireEvent/2023-02-08_0x8083730000000000","2023-02-09","dcid:s2CellId/0x8083124400000000,dcid:s2CellId/0x8083130000000000",1.011,340.79,289.11,"n",12.31 +"fireEvent/2023-03-09_0x80eb050000000000","2023-03-09","dcid:s2CellId/0x80eb046c00000000,dcid:s2CellId/0x80eb047400000000,dcid:s2CellId/0x80eb050000000000",2.331,310.66,274.9,"n",1.96 +"fireEvent/2023-02-14_0x8094f70000000000","2023-02-14","dcid:s2CellId/0x8094f70000000000,dcid:s2CellId/0x8094f77400000000,dcid:s2CellId/0x8094fb0000000000,dcid:s2CellId/0x8094fb5400000000",2.269,331.0,288.63,"n",2.34 +"fireEvent/2023-01-27_0x80d65f0000000000","2023-01-27","dcid:s2CellId/0x80d65e0c00000000,dcid:s2CellId/0x80d65e3400000000,dcid:s2CellId/0x80d65f0000000000",2.625,367.0,298.2,"n",4.84 +"fireEvent/2023-02-12_0x80921d0000000000","2023-02-12","dcid:s2CellId/0x80921c1c00000000,dcid:s2CellId/0x80921c2400000000,dcid:s2CellId/0x80921d0000000000",2.202,340.59,291.48,"n",9.06 diff --git a/scripts/earthengine/test_data/sample_fires_svobs.tmcf b/scripts/earthengine/test_data/sample_fires_svobs.tmcf new file mode 100644 index 0000000000..c6b6252a49 --- /dev/null +++ b/scripts/earthengine/test_data/sample_fires_svobs.tmcf @@ -0,0 +1,8 @@ +Node: E:SVObs->E0 +typeOf: C:SVObs->dcid:StatVarObservation +dcid: C:SVObs->dcid +observationDate: C:SVObs->observationDate +affectedPlace: C:SVObs->affectedPlace +area: C:SVObs->area +confidence: C:SVObs->confidence +frp: C:SVObs->frp \ No newline at end of file diff --git a/scripts/earthengine/test_data/sample_floods_events.csv b/scripts/earthengine/test_data/sample_floods_events.csv index f947da7e6d..f5200e63bb 100644 --- a/scripts/earthengine/test_data/sample_floods_events.csv +++ b/scripts/earthengine/test_data/sample_floods_events.csv @@ -1,19 +1,10 @@ "dcid","typeOf","name","startDate","endDate","observationPeriod","DurationDays","startLocation","affectedPlace","AffectedPlaceCount","ContainedInPlaceCount","area","AreaSqKm","subEvents","observationDate","geoJsonCoordinatesDP1" -"floodEvent/2022-10_0x39f1a90000000000","FloodEvent","FloodEvent at LatLong(24.82230:86.78190) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 24.82230 86.78190]","dcid:s2CellId/0x39f1a95c00000000,dcid:s2CellId/0x39f1070000000000,dcid:s2CellId/0x39f1072400000000,dcid:s2CellId/0x39f1a90000000000,dcid:Earth",4,5,"[1.806339 SquareKilometer]",1.806339,"","2022-102022-10","{'type': 'Polygon', 'coordinates': (((86.74163739293384, 24.9636595181691), (86.82203408381292, 24.965389147310105), (86.82203408381292, 24.870557703590148), (86.82203408381292, 24.775700454671043), (86.74163739293384, 24.773980497142173), (86.74163739293384, 24.86883290014557), (86.74163739293384, 24.9636595181691)),)}" -"floodEvent/2022-10_0x39fa5b0000000000","FloodEvent","FloodEvent at LatLong(24.74810:87.97270) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 24.74810 87.97270]","dcid:s2CellId/0x39fa5b6400000000,dcid:s2CellId/0x39fa5b0000000000,dcid:s2CellId/0x39fa5b9c00000000,dcid:s2CellId/0x39fa5b5c00000000,dcid:Earth",4,5,"[2.712936 SquareKilometer]",2.712936,"","2022-102022-102022-10","{'type': 'Polygon', 'coordinates': (((87.93348025811581, 24.70013777324746), (88.01184726113603, 24.70119093088496), (88.01184726113603, 24.796131023708277), (87.93348025811581, 24.79507488058305), (87.93348025811581, 24.70013777324746)),)}" -"floodEvent/2022-10_0x398d6b0000000000","FloodEvent","FloodEvent at LatLong(25.12651:84.44352) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 25.12651 84.44352]","dcid:s2CellId/0x398d130000000000,dcid:s2CellId/0x398d12dc00000000,dcid:s2CellId/0x398d6c9400000000,dcid:s2CellId/0x398d6b0000000000,dcid:s2CellId/0x398d6cc400000000,dcid:s2CellId/0x398d127c00000000,dcid:Earth,dcid:s2CellId/0x398d6d0000000000,dcid:s2CellId/0x398d6afc00000000",8,9,"[4.505284 SquareKilometer]",4.505284,"","2022-102022-102022-102022-102022-10","{'type': 'Polygon', 'coordinates': (((84.60604486518308, 25.185699102275812), (84.52221888957693, 25.182627378646327), (84.52221888957693, 25.088061308689923), (84.43827208721021, 25.08494623144014), (84.43827208721021, 25.1795037432513), (84.43827208721021, 25.274033342922905), (84.52221888957693, 25.277165499917018), (84.60604486518308, 25.280245602424383), (84.60604486518308, 25.185699102275812)),)}" -"floodEvent/2022-10_0x39f3cd0000000000","FloodEvent","FloodEvent at LatLong(24.80490:86.05300) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 24.80490 86.05300]","dcid:s2CellId/0x39f3cd0000000000,dcid:s2CellId/0x39f3cdac00000000,dcid:Earth",2,3,"[0.903843 SquareKilometer]",0.903843,"","2022-10","{'type': 'Polygon', 'coordinates': (((86.01215730732058, 24.756410613360817), (86.09373120909008, 24.758551048456575), (86.09373120909008, 24.853359964214558), (86.01215730732058, 24.851213494211738), (86.01215730732058, 24.756410613360817)),)}" -"floodEvent/2022-10_0x39f2cf0000000000","FloodEvent","FloodEvent at LatLong(25.05296:85.03894) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 25.05296 85.03894]","dcid:s2CellId/0x39f2cf0000000000,dcid:s2CellId/0x39f2d10000000000,dcid:s2CellId/0x39f2d01c00000000,dcid:s2CellId/0x39f2ce6400000000,dcid:Earth",4,5,"[1.8044069999999999 SquareKilometer]",1.8044069999999999,"","2022-102022-10","{'type': 'Polygon', 'coordinates': (((85.02334601407406, 25.105671247006093), (85.10643727766721, 25.108427924255686), (85.10643727766721, 25.0137784684534), (85.10643727766721, 24.91910228280929), (85.02334601407406, 24.916360836175645), (85.02334601407406, 25.01102939043017), (85.02334601407406, 25.105671247006093)),)}" -"floodEvent/2022-10_0x39920b0000000000","FloodEvent","FloodEvent at LatLong(25.55443:83.91619) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 25.55443 83.91619]","dcid:s2CellId/0x39920abc00000000,dcid:s2CellId/0x39920b0000000000,dcid:Earth",2,3,"[0.898387 SquareKilometer]",0.898387,"","2022-10","{'type': 'Polygon', 'coordinates': (((83.84730145422645, 25.533859654689113), (83.93208062135697, 25.53738977865098), (83.93208062135697, 25.631747270397884), (83.84730145422645, 25.62820777449197), (83.84730145422645, 25.533859654689113)),)}" -"floodEvent/2022-10_0x39faf10000000000","FloodEvent","FloodEvent at LatLong(24.88412:87.93838) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 24.88412 87.93838]","dcid:s2CellId/0x39fa5ec400000000,dcid:s2CellId/0x39faf72c00000000,dcid:s2CellId/0x39fa5f3c00000000,dcid:s2CellId/0x39fa590000000000,dcid:s2CellId/0x39faf5cc00000000,dcid:Earth,dcid:s2CellId/0x39faf50000000000,dcid:s2CellId/0x39fa5f5c00000000,dcid:s2CellId/0x39fa5ebc00000000,dcid:s2CellId/0x39fa58b400000000,dcid:s2CellId/0x39faf5f400000000,dcid:s2CellId/0x39faf69c00000000,dcid:s2CellId/0x39faf5c400000000,dcid:s2CellId/0x39fa5f4400000000,dcid:s2CellId/0x39faf5d400000000,dcid:s2CellId/0x39faf5e400000000,dcid:s2CellId/0x39faf69400000000,dcid:s2CellId/0x39fa58ac00000000,dcid:s2CellId/0x39faf10000000000,dcid:s2CellId/0x39fa5f5400000000,dcid:s2CellId/0x39fa5f0000000000,dcid:s2CellId/0x39fa5f2400000000,dcid:s2CellId/0x39faf12c00000000,dcid:s2CellId/0x39faf18400000000,dcid:s2CellId/0x39faf17400000000,dcid:s2CellId/0x39faf6c400000000,dcid:s2CellId/0x39faf5fc00000000,dcid:s2CellId/0x39faf70000000000,dcid:s2CellId/0x39fa5f4c00000000,dcid:s2CellId/0x39faf5ec00000000",29,30,"[27.090256 SquareKilometer]",27.090256,"","2022-102022-102022-102022-102022-102022-102022-102022-102022-102022-102022-102022-102022-102022-102022-102022-102022-102022-102022-102022-102022-102022-102022-102022-10","{'type': 'Polygon', 'coordinates': (((88.01184726113603, 24.891045808719575), (88.01184726113603, 24.796131023708277), (87.93348025811581, 24.79507488058305), (87.85497548307694, 24.793975946612758), (87.85497548307694, 24.888884664832755), (87.85497548307694, 24.983767362840133), (87.93348025811581, 24.984872471258544), (87.93348025811581, 25.079731480812), (88.01184726113603, 25.08079650587531), (88.01184726113603, 24.9859345481427), (88.01184726113603, 24.891045808719575)),)}" -"floodEvent/2022-10_0x398dad0000000000","FloodEvent","FloodEvent at LatLong(24.83720:84.14350) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 24.83720 84.14350]","dcid:s2CellId/0x398dad0c00000000,dcid:s2CellId/0x398dad0000000000,dcid:Earth,dcid:s2CellId/0x398dad1400000000",3,4,"[1.807302 SquareKilometer]",1.807302,"","2022-102022-10","{'type': 'Polygon', 'coordinates': (((84.10128611741789, 24.788239718921737), (84.1857114651512, 24.79153608914476), (84.1857114651512, 24.886146090200345), (84.10128611741789, 24.882840466824423), (84.10128611741789, 24.788239718921737)),)}" -"floodEvent/2022-10_0x39ee6d0000000000","FloodEvent","FloodEvent at LatLong(25.85650:86.45920) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 25.85650 86.45920]","dcid:s2CellId/0x39ee11bc00000000,dcid:s2CellId/0x39ee110000000000,dcid:s2CellId/0x39ee6d2c00000000,dcid:s2CellId/0x39ee6d0000000000,dcid:Earth",4,5,"[1.791068 SquareKilometer]",1.791068,"","2022-102022-10","{'type': 'MultiPolygon', 'coordinates': [(((86.41873076460409, 25.997238431745355), (86.49965462380155, 25.99921126692098), (86.49965462380155, 26.093657155868584), (86.41873076460409, 26.091679249420316), (86.41873076460409, 25.997238431745355)),), (((86.41873076460409, 25.808254312591544), (86.49965462380155, 25.81021693539081), (86.49965462380155, 25.904730955127118), (86.41873076460409, 25.90276321452476), (86.41873076460409, 25.808254312591544)),)]}" -"floodEvent/2022-10_0x39ed330000000000","FloodEvent","FloodEvent at LatLong(26.09620:84.98180) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 26.09620 84.98180]","dcid:s2CellId/0x39ed336400000000,dcid:s2CellId/0x39ed330000000000,dcid:s2CellId/0x39ed349c00000000,dcid:Earth,dcid:s2CellId/0x39ed34ec00000000,dcid:s2CellId/0x39ed34fc00000000,dcid:s2CellId/0x39ed350000000000,dcid:s2CellId/0x39ed366400000000,dcid:s2CellId/0x39ed34a400000000,dcid:s2CellId/0x39ed349400000000,dcid:s2CellId/0x39ed370000000000",10,11,"[6.264122 SquareKilometer]",6.264122,"","2022-102022-102022-102022-102022-102022-102022-10","{'type': 'Polygon', 'coordinates': (((85.02334601407406, 26.144762176536553), (85.02334601407406, 26.050461766980458), (85.10643727766721, 26.053292642812583), (85.10643727766721, 25.958950335632913), (85.02334601407406, 25.956126731282584), (84.94013115373588, 25.95325126204064), (84.94013115373588, 26.047578891746294), (84.94013115373588, 26.141871929267474), (85.02334601407406, 26.144762176536553)),)}" -"floodEvent/2022-10_0x39effd0000000000","FloodEvent","FloodEvent at LatLong(25.71732:87.43562) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 25.71732 87.43562]","dcid:s2CellId/0x39f0055c00000000,dcid:s2CellId/0x39f019f400000000,dcid:s2CellId/0x39f0190000000000,dcid:s2CellId/0x39effd0000000000,dcid:Earth,dcid:s2CellId/0x39f0055400000000,dcid:s2CellId/0x39f0054c00000000,dcid:s2CellId/0x39f019e400000000,dcid:s2CellId/0x39f0050000000000,dcid:s2CellId/0x39f019dc00000000,dcid:s2CellId/0x39effc6c00000000,dcid:s2CellId/0x39f01b0000000000,dcid:s2CellId/0x39f01a1c00000000",12,13,"[8.089756000000001 SquareKilometer]",8.089756000000001,"","2022-102022-102022-102022-102022-102022-102022-102022-10","{'type': 'MultiPolygon', 'coordinates': [(((87.46039695308058, 25.735490661888026), (87.46039695308058, 25.640859114305), (87.38107274572258, 25.639465131764638), (87.38107274572258, 25.734092995379868), (87.46039695308058, 25.735490661888026)),), (((87.30161319598756, 25.448683135906013), (87.22201866372775, 25.447206115512454), (87.22201866372775, 25.541888994831428), (87.30161319598756, 25.54336997501217), (87.38107274572258, 25.54480549977361), (87.46039695308058, 25.546195781891544), (87.46039695308058, 25.45150138795216), (87.38107274572258, 25.450114822657753), (87.30161319598756, 25.448683135906013)),)]}" -"floodEvent/2022-10_0x39f2230000000000","FloodEvent","FloodEvent at LatLong(25.18810:86.21580) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 25.18810 86.21580]","dcid:s2CellId/0x39f2230000000000,dcid:s2CellId/0x39f221bc00000000,dcid:s2CellId/0x39f2227c00000000,dcid:s2CellId/0x39f221ec00000000,dcid:s2CellId/0x39f2210000000000,dcid:Earth",5,6,"[2.702495 SquareKilometer]",2.702495,"","2022-102022-102022-10","{'type': 'Polygon', 'coordinates': (((86.09373120909008, 25.13763015295278), (86.09373120909008, 25.23233225373979), (86.1751759122996, 25.234454419095943), (86.2564910087331, 25.236528595275804), (86.2564910087331, 25.141815023056427), (86.1751759122996, 25.139746516746417), (86.09373120909008, 25.13763015295278)),)}" -"floodEvent/2022-10_0x39e5410000000000","FloodEvent","FloodEvent at LatLong(25.97770:87.81570) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 25.97770 87.81570]","dcid:s2CellId/0x39e5490000000000,dcid:s2CellId/0x39e5495400000000,dcid:s2CellId/0x39e5493400000000,dcid:s2CellId/0x39e5410000000000,dcid:s2CellId/0x39e54f0000000000,dcid:s2CellId/0x39e5489400000000,dcid:Earth,dcid:s2CellId/0x39e54ed400000000,dcid:s2CellId/0x39e5413400000000",8,9,"[4.482403 SquareKilometer]",4.482403,"","2022-102022-102022-102022-102022-10","{'type': 'MultiPolygon', 'coordinates': [(((87.77633327357327, 26.024367791331297), (87.85497548307694, 26.025550458330905), (87.85497548307694, 25.931002171995136), (87.77633327357327, 25.92982255544202), (87.77633327357327, 26.024367791331297)),), (((87.85497548307694, 25.836419867259345), (87.85497548307694, 25.741804261933925), (87.77633327357327, 25.740630788088815), (87.69755397032972, 25.73941290701931), (87.69755397032972, 25.834022239067483), (87.77633327357327, 25.83524331510538), (87.85497548307694, 25.836419867259345)),)]}" -"floodEvent/2022-10_0x3992830000000000","FloodEvent","FloodEvent at LatLong(25.60310:84.39630) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 25.60310 84.39630]","dcid:s2CellId/0x3992835400000000,dcid:s2CellId/0x3992830000000000,dcid:Earth",2,3,"[0.897661 SquareKilometer]",0.897661,"","2022-10","{'type': 'Polygon', 'coordinates': (((84.35420493103518, 25.554237253233943), (84.43827208721021, 25.55744742353682), (84.43827208721021, 25.65185813798067), (84.35420493103518, 25.648639452655605), (84.35420493103518, 25.554237253233943)),)}" -"floodEvent/2022-10_0x39fb030000000000","FloodEvent","FloodEvent at LatLong(25.03580:88.20720) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 25.03580 88.20720]","dcid:s2CellId/0x39fb03a400000000,dcid:s2CellId/0x39fb031400000000,dcid:s2CellId/0x39fb074400000000,dcid:s2CellId/0x39fb070000000000,dcid:s2CellId/0x39fb030000000000,dcid:s2CellId/0x39fb030400000000,dcid:Earth",6,7,"[3.609328 SquareKilometer]",3.609328,"","2022-102022-102022-102022-10","{'type': 'MultiPolygon', 'coordinates': [(((88.16816661672841, 24.987930457273897), (88.16816661672841, 25.082797955021128), (88.24611830999973, 25.083734806160862), (88.24611830999973, 24.988864715366525), (88.16816661672841, 24.987930457273897)),), (((88.32393091263926, 24.98975679359349), (88.32393091263926, 24.89485740029704), (88.24611830999973, 24.893967808439232), (88.24611830999973, 24.988864715366525), (88.32393091263926, 24.98975679359349)),)]}" -"floodEvent/2022-10_0x39f2fb0000000000","FloodEvent","FloodEvent at LatLong(25.00855:85.50457) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 25.00855 85.50457]","dcid:s2CellId/0x39f2fb0000000000,dcid:s2CellId/0x39f2fa1400000000,dcid:Earth",2,3,"[0.9023 SquareKilometer]",0.9023,"","2022-10","{'type': 'Polygon', 'coordinates': (((85.4375574061058, 24.929568460361843), (85.52002399545074, 24.932061071646416), (85.52002399545074, 25.026773319001666), (85.4375574061058, 25.024273772791044), (85.4375574061058, 24.929568460361843)),)}" -"floodEvent/2022-10_0x398d590000000000","FloodEvent","FloodEvent at LatLong(25.33200:84.73160) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 25.33200 84.73160]","dcid:s2CellId/0x398d510000000000,dcid:s2CellId/0x398d590000000000,dcid:s2CellId/0x398d50a400000000,dcid:s2CellId/0x398d5a8c00000000,dcid:s2CellId/0x398d5af400000000,dcid:Earth,dcid:s2CellId/0x398d451c00000000,dcid:s2CellId/0x398d5b0000000000,dcid:s2CellId/0x398d583400000000,dcid:s2CellId/0x398d453c00000000,dcid:s2CellId/0x398d5ac400000000,dcid:s2CellId/0x398d450000000000",11,12,"[6.295543 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+"floodEvent/2022-10_0x39ee6d0000000000","FloodEvent","FloodEvent at LatLong(25.85650:86.45921) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 25.85650 86.45921]","dcid:s2CellId/0x39ee6d2c00000000,dcid:Earth,dcid:s2CellId/0x39ee6d0000000000,dcid:s2CellId/0x39ee110000000000,dcid:s2CellId/0x39ee11bc00000000",4,5,"[1.79107 SquareKilometer]",1.791068,"","2022-10","{'type': 'MultiPolygon', 'coordinates': [(((86.41873076460409, 25.997238431745355), (86.49965462380155, 25.99921126692098), (86.49965462380155, 26.093657155868584), (86.41873076460409, 26.091679249420316), (86.41873076460409, 25.997238431745355)),), (((86.41873076460409, 25.808254312591544), (86.49965462380155, 25.81021693539081), (86.49965462380155, 25.904730955127118), (86.41873076460409, 25.90276321452476), (86.41873076460409, 25.808254312591544)),)]}" +"floodEvent/2022-10_0x398dad0000000000","FloodEvent","FloodEvent at LatLong(24.83720:84.14351) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 24.83720 84.14351]","dcid:s2CellId/0x398dad0000000000,dcid:s2CellId/0x398dad1400000000,dcid:Earth,dcid:s2CellId/0x398dad0c00000000",3,4,"[1.8073 SquareKilometer]",1.807302,"","2022-10","{'type': 'Polygon', 'coordinates': (((84.10128611741789, 24.788239718921737), (84.1857114651512, 24.79153608914476), (84.1857114651512, 24.886146090200345), (84.10128611741789, 24.882840466824423), (84.10128611741789, 24.788239718921737)),)}" +"floodEvent/2022-10_0x39f3cd0000000000","FloodEvent","FloodEvent at LatLong(24.80489:86.05296) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 24.80489 86.05296]","dcid:s2CellId/0x39f3cdac00000000,dcid:Earth,dcid:s2CellId/0x39f3cd0000000000",2,3,"[0.90384 SquareKilometer]",0.903843,"","2022-10","{'type': 'Polygon', 'coordinates': (((86.01215730732058, 24.756410613360817), (86.09373120909008, 24.758551048456575), (86.09373120909008, 24.853359964214558), (86.01215730732058, 24.851213494211738), (86.01215730732058, 24.756410613360817)),)}" +"floodEvent/2022-10_0x39e5410000000000","FloodEvent","FloodEvent at LatLong(25.97770:87.81567) on 2022-10","2022-10","2022-10","P1D",1,"[LatLong 25.97770 87.81567]","dcid:s2CellId/0x39e5413400000000,dcid:Earth,dcid:s2CellId/0x39e5410000000000,dcid:s2CellId/0x39e5493400000000,dcid:s2CellId/0x39e5490000000000,dcid:s2CellId/0x39e54ed400000000,dcid:s2CellId/0x39e5489400000000,dcid:s2CellId/0x39e54f0000000000,dcid:s2CellId/0x39e5495400000000",8,9,"[4.4824 SquareKilometer]",4.482403,"","2022-10","{'type': 'MultiPolygon', 'coordinates': [(((87.77633327357327, 26.024367791331297), (87.85497548307694, 26.025550458330905), (87.85497548307694, 25.931002171995136), (87.77633327357327, 25.92982255544202), (87.77633327357327, 26.024367791331297)),), (((87.85497548307694, 25.836419867259345), (87.85497548307694, 25.741804261933925), (87.77633327357327, 25.740630788088815), (87.69755397032972, 25.73941290701931), (87.69755397032972, 25.834022239067483), (87.77633327357327, 25.83524331510538), (87.85497548307694, 25.836419867259345)),)]}" diff --git a/scripts/earthengine/test_data/sample_floods_place_svobs.csv b/scripts/earthengine/test_data/sample_floods_place_svobs.csv new file mode 100644 index 0000000000..fcdb8d3b1e --- /dev/null +++ b/scripts/earthengine/test_data/sample_floods_place_svobs.csv @@ -0,0 +1,333 @@ +"observationAbout","observationDate","observationPeriod","area","count" +"s2CellId/0x39fb030000000000","2022-10","P1M",2.706,1 +"s2CellId/0x39fb070000000000","2022-10","P1M",0.903,1 +"s2CellId/0x39e5410000000000","2022-10","P1M",0.896,1 +"s2CellId/0x39e5490000000000","2022-10","P1M",2.69,1 +"s2CellId/0x39e54f0000000000","2022-10","P1M",0.897,1 +"s2CellId/0x39f3cd0000000000","2022-10","P1M",0.904,1 +"s2CellId/0x39925b0000000000","2022-10","P1M",5.369,1 +"s2CellId/0x3992590000000000","2022-10","P1M",0.895,1 +"s2CellId/0x39925f0000000000","2022-10","P1M",4.476,1 +"s2CellId/0x39928d0000000000","2022-10","P1M",3.583,1 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+"s2CellId/0x39ee6d0000000000","2022","P1Y",0.895,1 +"s2CellId/0x39ee110000000000","2022","P1Y",0.896,1 +"s2CellId/0x39f2cf0000000000","2022","P1Y",0.902,1 +"s2CellId/0x39f2d10000000000","2022","P1Y",0.902,1 +"s2CellId/0x398dad0000000000","2022","P1Y",1.807,1 +"s2CellId/0x39f2fb0000000000","2022","P1Y",0.902,1 +"s2CellId/0x39f1a90000000000","2022","P1Y",0.903,1 +"s2CellId/0x39f1070000000000","2022","P1Y",0.904,1 diff --git a/scripts/earthengine/test_data/sample_floods_place_svobs.tmcf b/scripts/earthengine/test_data/sample_floods_place_svobs.tmcf new file mode 100644 index 0000000000..9f9e301e70 --- /dev/null +++ b/scripts/earthengine/test_data/sample_floods_place_svobs.tmcf @@ -0,0 +1,16 @@ +Node: E:EventPlaces->E0 +typeOf: dcs:StatVarObservation +variableMeasured: dcs:Area_FloodEvent +observationAbout: C:EventPlaces->observationAbout +observationDate: C:EventPlaces->observationDate +observationPeriod: C:EventPlaces->observationPeriod +value: C:EventPlaces->area +unit: SquareKilometer + +Node: E:EventPlaces->E1 +typeOf: dcs:StatVarObservation +variableMeasured: dcs:Count_FloodEvent +observationAbout: C:EventPlaces->observationAbout +observationDate: C:EventPlaces->observationDate +observationPeriod: C:EventPlaces->observationPeriod +value: C:EventPlaces->count \ No newline at end of file diff --git a/scripts/earthengine/test_data/sample_floods_svobs.csv b/scripts/earthengine/test_data/sample_floods_svobs.csv index 16b049ee45..7c363ba8d4 100644 --- a/scripts/earthengine/test_data/sample_floods_svobs.csv +++ b/scripts/earthengine/test_data/sample_floods_svobs.csv @@ -1,19 +1,10 @@ "dcid","observationDate","affectedPlace","area","observationDate" -"floodEvent/2022-10_0x39ed330000000000","2022-10","s2CellId/0x39ed336400000000,s2CellId/0x39ed349400000000,s2CellId/0x39ed349c00000000,s2CellId/0x39ed34a400000000,s2CellId/0x39ed34ec00000000,s2CellId/0x39ed34fc00000000,s2CellId/0x39ed366400000000",6.264122,"2022-10" -"floodEvent/2022-10_0x39ee6d0000000000","2022-10","s2CellId/0x39ee11bc00000000,s2CellId/0x39ee6d2c00000000",1.791068,"2022-10" -"floodEvent/2022-10_0x398d6b0000000000","2022-10","s2CellId/0x398d127c00000000,s2CellId/0x398d12dc00000000,s2CellId/0x398d6afc00000000,s2CellId/0x398d6c9400000000,s2CellId/0x398d6cc400000000",4.505284,"2022-10" -"floodEvent/2022-10_0x39fb030000000000","2022-10","s2CellId/0x39fb030400000000,s2CellId/0x39fb031400000000,s2CellId/0x39fb03a400000000,s2CellId/0x39fb074400000000",3.609328,"2022-10" +"floodEvent/2022-10_0x39e5410000000000","2022-10","s2CellId/0x39e5413400000000,s2CellId/0x39e5489400000000,s2CellId/0x39e5493400000000,s2CellId/0x39e5495400000000,s2CellId/0x39e54ed400000000",4.482403,"2022-10" "floodEvent/2022-10_0x39f1a90000000000","2022-10","s2CellId/0x39f1072400000000,s2CellId/0x39f1a95c00000000",1.806339,"2022-10" +"floodEvent/2022-10_0x39f2fb0000000000","2022-10","s2CellId/0x39f2fa1400000000",0.9023,"2022-10" "floodEvent/2022-10_0x39f3cd0000000000","2022-10","s2CellId/0x39f3cdac00000000",0.903843,"2022-10" +"floodEvent/2022-10_0x39ee6d0000000000","2022-10","s2CellId/0x39ee11bc00000000,s2CellId/0x39ee6d2c00000000",1.791068,"2022-10" 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-"floodEvent/2022-10_0x398d590000000000","2022-10","s2CellId/0x398d451c00000000,s2CellId/0x398d453c00000000,s2CellId/0x398d50a400000000,s2CellId/0x398d583400000000,s2CellId/0x398d5a8c00000000,s2CellId/0x398d5ac400000000,s2CellId/0x398d5af400000000",6.295543,"2022-10" diff --git a/scripts/earthengine/test_data/test_s2_cells_properties.pkl b/scripts/earthengine/test_data/test_s2_cells_properties.pkl new file mode 100644 index 0000000000..384763c507 Binary files /dev/null and b/scripts/earthengine/test_data/test_s2_cells_properties.pkl differ diff --git a/scripts/earthengine/utils.py b/scripts/earthengine/utils.py index e6f7c82c5e..67fa3de8be 100644 --- a/scripts/earthengine/utils.py +++ b/scripts/earthengine/utils.py @@ -15,6 +15,7 @@ import csv import datacommons as dc +import datetime import glob import os import pickle @@ -24,74 +25,25 @@ import tempfile from absl import logging +from datetime import date +from datetime import datetime +from dateutil.relativedelta import relativedelta from geopy import distance from s2sphere import LatLng, Cell, CellId from shapely.geometry import Polygon from typing import Union -_SCRIPTS_DIR = os.path.dirname(os.path.dirname(__file__)) +_SCRIPTS_DIR = os.path.dirname(__file__) sys.path.append(_SCRIPTS_DIR) sys.path.append(os.path.dirname(_SCRIPTS_DIR)) sys.path.append(os.path.dirname(os.path.dirname(_SCRIPTS_DIR))) +sys.path.append( + os.path.join(os.path.dirname(os.path.dirname(_SCRIPTS_DIR)), 'util')) -from util.config_map import ConfigMap, read_py_dict_from_file, write_py_dict_to_file -from util.dc_api_wrapper import dc_api_wrapper - +from config_map import ConfigMap, read_py_dict_from_file, write_py_dict_to_file +from dc_api_wrapper import dc_api_wrapper # Utilities for dicts. -def aggregate_value(value1: str, value2: str, aggregate: str = 'sum') -> str: - '''Return value aggregated from src and dst as per the config.''' - value = None - if aggregate == 'sum': - value = value1 + value2 - elif aggregate == 'min': - value = min(value1, value2) - elif aggregate == 'max': - value = max(value1, value2) - elif aggregate == 'list': - # Create a list of unique values combining lists. - value = set(str(value1).split(',')) - value.update(str(value2).split(',')) - value = ','.join(sorted(value)) - else: - logging.fatal( - f'Unsupported aggregation: {aggregate} for {value1}, {value2}') - return value - - -def dict_aggregate_values(src: dict, dst: dict, config: dict) -> dict: - '''Aggregate values for keys in src dict into dst. - The mode of aggregation (sum, mean, min, max) per property is - defined in the config. - Assumes properties to be aggregated have numeric values. - - Args: - src: dictionary with property:value to be aggregated into dst - dst: dictionary with property:value which is updated. - config: dictionary with aggregation settings per property. - Returns: - dst dictionary with updated property:values. - ''' - if config is None: - config = {} - default_aggr = config.get('aggregate', 'sum') - for prop, new_val in src.items(): - if prop not in dst: - # Add new property to dst without any aggregation. - dst[prop] = new_val - else: - # Combine new value in src with current value in dst by aggregation. - aggr = config.get(prop, {}).get('aggregate', default_aggr) - cur_val = dst[prop] - if aggr == 'mean': - cur_num = dst.get(f'#{prop}:count', 1) - new_num = src.get(f'#{prop}:count', 1) - dst[prop] = ((cur_val * cur_num) + - (new_val * new_num)) / (cur_num + new_num) - dst[f'#{prop}:count'] = cur_num + new_num - else: - dst[prop] = aggregate_value(cur_val, new_val, aggr) - return dst def dict_filter_values(pvs: dict, config: dict = {}) -> bool: @@ -107,6 +59,8 @@ def dict_filter_values(pvs: dict, config: dict = {}) -> bool: 'regex': ', }, } + Returns: + True if the key:values in pvs meet all config criteria. ''' props = list(pvs.keys()) is_allowed = True @@ -142,7 +96,18 @@ def is_s2_cell_id(dcid: str) -> bool: return strip_namespace(dcid).startswith('s2CellId/') -def s2_cell_from_latlng(lat: float, lng: float, level: int) -> s2sphere.CellId: +def s2_cell_from_latlng(lat: float, lng: float, level: int) -> CellId: + '''Returns an S2 CellId object of level for the given location lat/lng. + + Args: + lat: Latitude in degrees + lng: Longitude in degrees + level: desired S2 level for cell id. + Should be <30, the max s2 level supported. + + Returns: + CellId object oof the desired level that contains the lat/lng point. + ''' assert level >= 0 and level <= 30 ll = s2sphere.LatLng.from_degrees(lat, lng) cell = s2sphere.CellId.from_lat_lng(ll) @@ -151,19 +116,22 @@ def s2_cell_from_latlng(lat: float, lng: float, level: int) -> s2sphere.CellId: return cell -def s2_cell_to_hex_str(s2cell_id: int) -> str: +def s2_cell_to_hex_str(s2cell_id: Union[int, CellId]) -> str: + '''Returns the s2 cell id in hex.''' if isinstance(s2cell_id, CellId): s2cell_id = s2cell_id.id() return f'{s2cell_id:#018x}' -def s2_cell_to_dcid(s2cell_id: int) -> str: +def s2_cell_to_dcid(s2cell_id: Union[int, CellId]) -> str: + '''Returns the dcid for the s2 cell of the form s2CellId/0x1234.''' if isinstance(s2cell_id, CellId): s2cell_id = s2cell_id.id() return 'dcid:s2CellId/' + s2_cell_to_hex_str(s2cell_id) -def s2_cell_from_dcid(s2_dcid: str) -> s2sphere.CellId: +def s2_cell_from_dcid(s2_dcid: Union[str, int, CellId]) -> CellId: + '''Returns the s2 CellId object for the s2 cell.''' if isinstance(s2_dcid, str): return s2sphere.CellId(int(s2_dcid[s2_dcid.find('/') + 1:], 16)) if isinstance(s2_dcid, int): @@ -174,11 +142,12 @@ def s2_cell_from_dcid(s2_dcid: str) -> s2sphere.CellId: def s2_cell_latlng_dcid(lat: float, lng: float, level: int) -> str: + '''Returns dcid of the s2 cell of given level containing the point lat/lng.''' return s2_cell_to_dcid(s2_cell_from_latlng(lat, lng, level).id()) def s2_cells_distance(cell_id1: int, cell_id2: int) -> float: - '''Returns the distance between the centroid of the S2 cells.''' + '''Returns the distance between the centroid of two S2 cells in kilometers.''' p1 = CellId(cell_id1).to_lat_lng() p2 = CellId(cell_id2).to_lat_lng() return distance.distance((p1.lat().degrees, p1.lng().degrees), @@ -201,8 +170,11 @@ def s2_cell_area(cell_id: s2sphere.CellId) -> float: return s2sphere.Cell(s2_cell).exact_area() * _EARTH_RADIUS * _EARTH_RADIUS -def s2_cell_get_neighbor_ids(s2_cell_id: str) -> str: - '''Returns the neighbouring cell ids for a given s2 cell dcid.''' +def s2_cell_get_neighbor_ids(s2_cell_id: str) -> list: + '''Returns a list of neighbouring cell dcids for a given s2 cell dcid. + An interior cell will have 8 neighbours: 3 above, 1 left, 1 right and 3 below. + A cell near the edge may have a subset of these. + ''' s2_cell = s2_cell_from_dcid(s2_cell_id) return [ s2_cell_to_dcid(cell) @@ -211,6 +183,7 @@ def s2_cell_get_neighbor_ids(s2_cell_id: str) -> str: def s2_cell_to_polygon(s2_cell_id: str) -> Polygon: + '''Returns the polygon with 4 vertices for an s2 cell.''' s2_cell = Cell(s2_cell_from_dcid(s2_cell_id)) if not s2_cell: return None @@ -227,10 +200,10 @@ def s2_cell_to_polygon(s2_cell_id: str) -> Polygon: def latlng_cell_area(lat: float, lng: float, height: float, width: float) -> float: - '''Returns the area of the rectangular cell in km2. + '''Returns the area of the rectangular region in sqkm. Args: - lat: latitude of a corner. - lng: Longitude of a corner + lat: latitude of a corner in degrees + lng: Longitude of a corner in degrees width: width in degrees height: height in degrees Returns: @@ -384,9 +357,9 @@ def place_distance(place1: str, place2: str) -> float: def place_area(place: str) -> float: - '''Returns the area for the place.''' + '''Returns the area for the place in sqkm.''' if is_s2_cell_id(place): - s2_cell = s2_cell_from_dcid(placeid) + s2_cell = s2_cell_from_dcid(place) return s2_cell_area(s2_cell) if is_grid_id(place) or is_ipcc_id(place): return grid_area(place) @@ -403,189 +376,6 @@ def place_to_polygon(place_id: str) -> Polygon: return None -# Utilities for files. -def file_get_matching(filepat: str) -> list: - '''Return a list of matching file names. - Args: - filepat: string with comma seperated list of file patterns to lookup - Returns: - list of matching filenames. - ''' - # Get a list of input file patterns to lookup - input_files = filepat - if isinstance(filepat, str): - input_files = [filepat] - if isinstance(input_files, list): - for files in input_files: - for file in files.split(','): - if file not in input_files: - input_files.append(file) - # Get all matching files for each file pattern. - files = list() - if input_files: - for file in input_files: - for f in glob.glob(file): - if f not in files: - files.append(f) - return sorted(files) - - -def file_estimate_num_rows(filename: str) -> int: - '''Returns an estimated number of rows based on size of the first few rows. - Args: - filename: string name of the file. - Returns: - An estimated number of rows. - ''' - filesize = os.path.getsize(filename) - with open(filename) as fp: - lines = fp.read(4000) - line_size = max(len(lines) / (lines.count('\n') + 1), 1) - return int(filesize / line_size) - - -def file_get_name(file_path: str, - suffix: str = '', - file_ext: str = '.csv') -> str: - '''Returns the filename with suffix and extension. - Creates the directory path for the file if it doesn't exist. - Args: - file_path: file path with directory and file name prefix - suffix: file name suffix - file_ext: file extension - Returns: - file name combined from path, suffix and extension. - ''' - # Create the file directory if it doesn't exist. - file_dir = os.path.dirname(file_path) - if file_dir: - os.makedirs(file_dir, exist_ok=True) - file_prefix, ext = os.path.splitext(file_path) - if file_prefix.endswith(suffix): - # Suffix already present in name, ignore it. - suffix = '' - # Set the file extension - if file_ext and file_ext[0] != '.': - file_ext = '.' + file_ext - return file_prefix + suffix + file_ext - - -def file_load_csv_dict(filename: str, - key_column: str = None, - value_column: str = None, - delimiter: str = ',', - config: dict = {}) -> dict: - '''Returns a CSV file loaded into a dict. - Each row is added to the dict with value from column 'key_column' as key - and value from 'value_column. - Args: - filename: csv file name to be loaded into the dict. - it can be a comma separated list of file patterns as well. - key_column: column in the csv to be used as the key for the dict - if not set, uses the first column as the key. - value_column: column to be used as value in the dict. - If not set, value is a dict of all remaining columns. - config: dictionary of aggregation settings in case there are - multiple rows with the same key. - refer to dict_aggregate_values() for config settings. - - Returns: - dictionary of {key:value} loaded from the CSV file. - ''' - csv_dict = {} - input_files = file_get_matching(filename) - for filename in input_files: - logging.info(f'Loading csv data file: {filename}') - num_rows = 0 - # Load each CSV file - with open(filename) as csvfile: - reader = csv.DictReader(csvfile, delimiter=delimiter) - if not key_column: - key_column = reader.fieldnames[0] - if not value_column and len(reader.fieldnames) == 2: - value_column = reader.fieldnames[1] - # Process a row from the csv file - for row in reader: - # Get the key for the row. - key = None - if key_column in row: - key = row.pop(key_column) - value = '' - if value_column: - value = row.get(value_column, '') - else: - value = row - if key is None or value is None: - logging.debug(f'Ignoring row without key or value: {row}') - continue - # Add the row to the dict - if key in csv_dict: - # Key already exists. Merge values. - old_value = csv_dict[key] - if isinstance(old_value, dict): - dict_aggregate_values(row, old_value, config) - else: - aggr = config.get(prop, config).get('aggregate', 'sum') - value = aggregate_value(old_value, value, aggr) - csv_dict[key] = value - else: - csv_dict[key] = value - num_rows += 1 - logging.info(f'Loaded {num_rows} rows from {filename} into dict') - return csv_dict - - -def file_load_py_dict(dict_filename: str) -> dict: - '''Returns a py dictionary loaded from the file. - The file can be a pickle file (.pkl) or a .py or JSON dict (.json)''' - input_files = file_get_matching(dict_filename) - py_dict = {} - for filename in input_files: - file_size = os.path.getsize(filename) - if file_size: - if filename.endswith('.pkl'): - logging.info(f'Loading dict from pickle file: {filename}') - with open(filename, 'rb') as file: - py_dict.update(pickle.load(file)) - else: - # Assumes the file is a py or json dict. - logging.info(f'Loading dict from py from file: {filename}') - py_dict.update(read_py_dict_from_file(filename)) - logging.info( - f'Loaded py dict of size: {file_size} from {filename}') - return py_dict - - -def file_write_py_dict(py_dict: dict, filename: str): - '''Save the py dictionary into a file. - First writes the dict into a temp file and moves the tmp file to the required file. - so that any interruption during write will not corrupt the existing file. - ''' - if not py_dict or not filename: - return - output_files = file_get_matching(filename) - if output_files: - # Save into the last file - filename = output_files[-1] - # Save the active events into a tmp file and move it to the required file. - fd, tmp_filename = tempfile.mkstemp() - if filename.endswith('.pkl'): - logging.info( - f'Writing py dict of size {sys.getsizeof(py_dict)} to pickle file: {filename}' - ) - with open(tmp_filename, 'wb') as file: - pickle.dump(py_dict, file) - else: - logging.info( - f'Writing py dict of size {sys.getsizeof(py_dict)} to file: {filename}' - ) - write_py_dict_to_file(py_dict, tmp_filename) - # Rename tmp file into the required file. - os.rename(tmp_filename, filename) - file_size = os.path.getsize(filename) - logging.info(f'Saved py dict into file: {filename} of size: {file_size}') - - # String utilities @@ -649,3 +439,68 @@ def str_format_float(data: float, precision_digits: int = 6): if isinstance(data, float): return f'{data:.{precision_digits}f}' return data + + +# Date utilities + + +def date_today(date_format: str = '%Y-%m-%d') -> str: + '''Returns today's date in the given format.''' + return date.today().strftime(date_format) + + +def date_yesterday(date_format: str = '%Y-%m-%d') -> str: + '''Returns today's date in the given format.''' + return date_advance_by_period(date_today(date_format), '-1d', date_format) + + +def date_parse_time_period(time_period: str) -> (int, str): + '''Parse time period into a tuple of (number, unit), + for eg: for 'P1M' returns (1, month). + Time period is assumed to be of the form: P + where duration is a letter: D: days, M; months, Y: years. + .''' + # Extract the number and duration letter from the time period. + re_pat = r'P?(?P[+-]?[0-9]+)(?P[A-Z])' + m = re.search(re_pat, time_period.upper()) + if m: + m_dict = m.groupdict() + delta = int(m_dict.get('delta', '0')) + unit = m_dict.get('unit', 'M') + # Convert the duration letter to unit: days/months/years + period_dict = {'D': 'days', 'M': 'months', 'Y': 'years'} + period = period_dict.get(unit, 'day') + return (delta, period) + return (0, 'days') + + +def date_advance_by_period(date_str: str, + time_period: str, + date_format: str = '%Y-%m-%d') -> str: + '''Returns the date string advanced by the time period.''' + if not date_str: + return '' + dt = datetime.strptime(date_str, date_format) + (delta, unit) = date_parse_time_period(time_period) + if not delta or not unit: + logging.error( + f'Unable to parse time period: {time_period} for date: {date_str}') + return '' + next_dt = dt + relativedelta(**{unit: delta}) + return next_dt.strftime(date_format) + + +def date_format_by_time_period(date_str: str, time_period: str) -> str: + '''Returns date in the format of the time_period: P + If the last letter in the time_period is Y, returns date in YYYY, + for 'M', returns date as YYYY-MM, for D returns date as YYYY-MM-DD. + ''' + if not time_period: + return date_str + (delta, unit) = date_parse_time_period(time_period) + date_parts = date_str.split('-') + if unit == 'years': + return date_parts[0] + if unit == 'months': + return '-'.join(date_parts[0:2]) + return date_str diff --git a/scripts/earthengine/utils_test.py b/scripts/earthengine/utils_test.py index ab681f97bb..92c6b841b8 100644 --- a/scripts/earthengine/utils_test.py +++ b/scripts/earthengine/utils_test.py @@ -47,63 +47,6 @@ class DictUtilsTest(unittest.TestCase): 'string_key2': 'Value1', } - def setUp(self): - return - - def test_dict_aggregate_values(self): - '''Test aggreation of dictionaries with dict_aggregate_test().''' - dict2 = { - 'int_key1': 11, - 'int_key2': 2, - 'float_key2': 4.56, - 'float_key3': 44.44, - 'string_key1': 'Value2', - 'string_key2': 'Value1,StrValue2', - 'string_key3': 'New String', - } - - config = { - 'aggregate': 'sum', # default aggregate - 'int_key2': { - 'aggregate': 'max' - }, - 'float_key2': { - 'aggregate': 'min' - }, - 'float_key3': { - 'aggregate': 'mean' - }, - 'string_key2': { - 'aggregate': 'list' - }, - } - - merged_dict = dict(dict2) - utils.dict_aggregate_values(self.dict1, merged_dict, config) - expected_dict = { - 'int_key1': self.dict1['int_key1'] + dict2['int_key1'], - 'int_key2': max(self.dict1['int_key2'], dict2['int_key2']), - 'int_key3': self.dict1['int_key3'], - 'float_key1': self.dict1['float_key1'], - 'float_key2': min(self.dict1['float_key2'], dict2['float_key2']), - 'float_key3': (self.dict1['float_key3'] + dict2['float_key3']) / 2, - '#float_key3:count': 2, - 'string_key1': 'Value2String Value', # sum - 'string_key2': 'StrValue2,Value1', # list - 'string_key3': 'New String', - } - self.assertEqual(expected_dict, merged_dict) - - utils.dict_aggregate_values(dict2, merged_dict, config) - expected_dict['int_key1'] += dict2['int_key1'] - expected_dict['float_key3'] = (self.dict1['float_key3'] + - 2 * dict2['float_key3']) / 3 - expected_dict['#float_key3:count'] = 3 - expected_dict['string_key1'] = 'Value2String ValueValue2' - expected_dict['string_key2'] = 'StrValue2,Value1' - expected_dict['string_key3'] = 'New StringNew String' - self.assertEqual(expected_dict, merged_dict) - def test_dict_filter_values(self): filter_config = { 'int_key1': { @@ -296,52 +239,6 @@ def test_grid_to_polygon(self): utils.place_to_polygon('s2CellId/0x1128250000000000'))) -class FileUtilsTest(unittest.TestCase): - - def test_file_get_matching(self): - files = utils.file_get_matching(os.path.join(_TESTDIR, 'sample*.csv')) - self.assertTrue(len(files) > 2) - for file in files: - self.assertTrue(os.path.exists(file)) - - def test_file_get_estimate_num_rows(self): - files = utils.file_get_matching(os.path.join(_TESTDIR, 'sample*.csv')) - for file in files: - estimate_rows = utils.file_estimate_num_rows(file) - with open(file, 'r') as fp: - num_lines = len(fp.readlines()) - self.assertTrue( - math.isclose(num_lines, estimate_rows, rel_tol=1)) - - def test_file_load_csv_dict(self): - csv_dict = utils.file_load_csv_dict( - os.path.join(_TESTDIR, 'sample_output.csv'), 's2CellId') - self.assertTrue(len(csv_dict) > 0) - test_key = 'dcid:s2CellId/0x39925b1c00000000' - self.assertTrue(test_key in csv_dict) - self.assertEqual('1', csv_dict[test_key]['water']) - self.assertEqual('13', csv_dict[test_key]['s2Level']) - - def test_file_write_load_py_dict(self): - test_dict = {'test_key': 'test_value', 'int_key': 10, 'list': [1, 2, 3]} - # read/write dict as a py file - fd, tmp_py_filename = tempfile.mkstemp(suffix='.py') - utils.file_write_py_dict(test_dict, tmp_py_filename) - self.assertTrue(os.path.getsize(tmp_py_filename) > 10) - read_dict = utils.file_load_py_dict(tmp_py_filename) - self.assertEqual(test_dict, read_dict) - # Repeat test with pkl file. - fd, tmp_pkl_filename = tempfile.mkstemp(suffix='.pkl') - utils.file_write_py_dict(test_dict, tmp_pkl_filename) - self.assertTrue(os.path.getsize(tmp_pkl_filename) > 10) - read_pkl_dict = utils.file_load_py_dict(tmp_pkl_filename) - self.assertEqual(test_dict, read_pkl_dict) - # check pkl and py files are different. - self.assertTrue( - os.path.getsize(tmp_pkl_filename) != os.path.getsize( - tmp_py_filename)) - - class StrUtilsTest(unittest.TestCase): def test_strip_namespace(self): @@ -373,3 +270,36 @@ def test_str_get_numeric_vlaue(self): self.assertEqual(2.34, utils.str_get_numeric_value([2.34, 5.67])) self.assertEqual(None, utils.str_get_numeric_value('abc')) self.assertEqual(None, utils.str_get_numeric_value('123abc')) + + +class DateUtilsTest(unittest.TestCase): + + def test_date_parse_time_period(self): + self.assertEqual((1, 'days'), utils.date_parse_time_period('P1D')) + self.assertEqual((10, 'days'), utils.date_parse_time_period('10D')) + self.assertEqual((-7, 'days'), utils.date_parse_time_period('-7D')) + + self.assertEqual((1, 'months'), utils.date_parse_time_period('P1M')) + self.assertEqual((3, 'months'), utils.date_parse_time_period('3M')) + + self.assertEqual((1, 'years'), utils.date_parse_time_period('P1Y')) + self.assertEqual((5, 'years'), utils.date_parse_time_period('5Y')) + + def test_date_advance_by_time_period(self): + self.assertEqual( + utils.date_today(), + utils.date_advance_by_period(utils.date_yesterday(), 'P1D')) + self.assertEqual('2023-04-10', + utils.date_advance_by_period('2023-04-20', 'P-10D')) + self.assertEqual( + '2023-06', utils.date_advance_by_period('2023-04', 'P2M', '%Y-%m')) + self.assertEqual('2033', + utils.date_advance_by_period('2023', '10Y', '%Y')) + + def test_date_format_by_time_period(self): + self.assertEqual('2023-04-10', + utils.date_format_by_time_period('2023-04-10', 'P1D')) + self.assertEqual('2022-04', + utils.date_format_by_time_period('2022-04-10', 'P3M')) + self.assertEqual('2021', + utils.date_format_by_time_period('2021-01-10', '1Y')) diff --git a/scripts/fbi/hate_crime/preprocess_aggregations.py b/scripts/fbi/hate_crime/preprocess_aggregations.py index a9452ebe1c..2719de40f4 100644 --- a/scripts/fbi/hate_crime/preprocess_aggregations.py +++ b/scripts/fbi/hate_crime/preprocess_aggregations.py @@ -1536,8 +1536,8 @@ def _add_offender_category(row): row['OFFENDER_CATEGORY'] = 'UnknownOffender' # If offender's age, race or ethnicity is known, then it is a known offender - if (row['ADULT_OFFENDER_COUNT'] != - np.nan) or (row['JUVENILE_OFFENDER_COUNT'] != np.nan) or ( + if (row['ADULT_OFFENDER_COUNT'] + != np.nan) or (row['JUVENILE_OFFENDER_COUNT'] != np.nan) or ( (row['OFFENDER_RACE'] != np.nan) and (row['OFFENDER_RACE'] != 'Unknown')) or ( (row['OFFENDER_ETHNICITY'] != np.nan) and diff --git a/scripts/fires/wfigs_data.py b/scripts/fires/wfigs_data.py index 530f6dc452..f6d92e591c 100644 --- a/scripts/fires/wfigs_data.py +++ b/scripts/fires/wfigs_data.py @@ -148,8 +148,8 @@ def get_place(row): try: geoIds = [] location = '' - if not (pd.isna(latitude) or pd.isna(longitude) - ) and abs(latitude) <= 90 and abs(longitude) <= 180: + if not (pd.isna(latitude) or pd.isna(longitude)) and abs( + latitude) <= 90 and abs(longitude) <= 180: if latitude_str in _LAT_LNG_CACHE: if longitude_str in _LAT_LNG_CACHE[str(latitude)]: return _LAT_LNG_CACHE[latitude_str][str(longitude)] diff --git a/scripts/india/geo/LocalGovernmentDirectory_Districts.csv b/scripts/india/geo/LocalGovernmentDirectory_Districts.csv index 76ec5828e1..d70a339c49 100644 --- a/scripts/india/geo/LocalGovernmentDirectory_Districts.csv +++ b/scripts/india/geo/LocalGovernmentDirectory_Districts.csv @@ -1,740 +1,758 @@ -LGDDistrictCode,LGDDistrictName,LGDStateCode,LGDStateName,LGDCensus2001Code,LGDCensus2011Code,closestDistrictLabel,district,districtLabel,districtDescription,state,stateLabel,stateDescription,census2011Code,WikiDataId,LGDDistrictNameTitleCase,districtLabelTitleCase -603,nicobars,35,andaman and nicobar islands,35.02,638,nicobar,http://www.wikidata.org/entity/Q797295,nicobar,"district of the Andaman and Nicobar Islands, India",http://www.wikidata.org/entity/Q40888,andaman and nicobar islands,union territory of India,638,Q797295,Nicobars,Nicobar -632,north and middle andaman,35,andaman and nicobar islands,,639,north and middle andaman,http://www.wikidata.org/entity/Q796983,north and middle andaman,"district of the Andaman and Nicobar Islands, India",http://www.wikidata.org/entity/Q40888,andaman and nicobar islands,union territory of India,639,Q796983,North and Middle Andaman,North and Middle Andaman -602,south andamans,35,andaman and nicobar islands,35.01,640,south andaman,http://www.wikidata.org/entity/Q796979,south andaman,district in Andaman and Nicobar Islands,http://www.wikidata.org/entity/Q40888,andaman and nicobar islands,union territory of India,640,Q796979,South Andamans,South Andaman -502,anantapur,28,andhra pradesh,28.22,553,anantapuram,http://www.wikidata.org/entity/Q15212,anantapuram,"district of Andhra Pradesh, India",http://www.wikidata.org/entity/Q1159,andhra pradesh,state in India,553,Q15212,Anantapur,Anantapuram -503,chittoor,28,andhra pradesh,28.23,554,chittoor,http://www.wikidata.org/entity/Q15213,chittoor,"district of Andhra Pradesh, India",http://www.wikidata.org/entity/Q1159,andhra pradesh,state in India,554,Q15213,Chittoor,Chittoor -505,east godavari,28,andhra pradesh,28.14,545,east godavari,http://www.wikidata.org/entity/Q15338,east godavari,"district of Andhra Pradesh, India",http://www.wikidata.org/entity/Q1159,andhra pradesh,state in India,545,Q15338,East Godavari,East Godavari -506,guntur,28,andhra pradesh,28.17,548,guntur,http://www.wikidata.org/entity/Q15341,guntur,"district of Andhra Pradesh, India",http://www.wikidata.org/entity/Q1159,andhra pradesh,state in India,548,Q15341,Guntur,Guntur -510,krishna,28,andhra pradesh,28.16,547,krishna,http://www.wikidata.org/entity/Q15382,krishna,"district of Andhra Pradesh, India",http://www.wikidata.org/entity/Q1159,andhra pradesh,state in India,547,Q15382,Krishna,Krishna -511,kurnool,28,andhra pradesh,28.21,552,kurnool,http://www.wikidata.org/entity/Q15381,kurnool,"district of Andhra Pradesh, India",http://www.wikidata.org/entity/Q1159,andhra pradesh,state in India,552,Q15381,Kurnool,Kurnool -517,prakasam,28,andhra pradesh,28.18,549,prakasam,http://www.wikidata.org/entity/Q15390,prakasam,"district of Andhra Pradesh, India",http://www.wikidata.org/entity/Q1159,andhra pradesh,state in India,549,Q15390,Prakasam,Prakasam -515,spsr nellore,28,andhra pradesh,28.19,550,sri potti sri ramulu nellore,http://www.wikidata.org/entity/Q15383,sri potti sri ramulu nellore,"district of Andhra Pradesh, India",http://www.wikidata.org/entity/Q1159,andhra pradesh,state in India,550,Q15383,Spsr Nellore,Sri Potti Sri Ramulu Nellore -519,srikakulam,28,andhra pradesh,28.11,542,srikakulam,http://www.wikidata.org/entity/Q15395,srikakulam,extreme northeastern district of Andhra Pradesh,http://www.wikidata.org/entity/Q1159,andhra pradesh,state in India,542,Q15395,Srikakulam,Srikakulam -520,visakhapatanam,28,andhra pradesh,28.13,544,visakhapatnam,http://www.wikidata.org/entity/Q15394,visakhapatnam,district of Andhra Pradesh,http://www.wikidata.org/entity/Q1159,andhra pradesh,state in India,544,Q15394,Visakhapatanam,Visakhapatnam -521,vizianagaram,28,andhra pradesh,28.12,543,vizianagaram,http://www.wikidata.org/entity/Q15392,vizianagaram,northern coastal district of Andhra Pradesh,http://www.wikidata.org/entity/Q1159,andhra pradesh,state in India,543,Q15392,Vizianagaram,Vizianagaram -523,west godavari,28,andhra pradesh,28.15,546,west godavari,http://www.wikidata.org/entity/Q15404,west godavari,"district of Andhra Pradesh, India",http://www.wikidata.org/entity/Q1159,andhra pradesh,state in India,546,Q15404,West Godavari,West Godavari -504,y.s.r.,28,andhra pradesh,28.20,551,kadapa,http://www.wikidata.org/entity/Q15342,kadapa,"district of Andhra Pradesh, India",http://www.wikidata.org/entity/Q1159,andhra pradesh,state in India,551,Q15342,Y.s.r.,Kadapa -628,anjaw,12,arunachal pradesh,,260,anjaw,http://www.wikidata.org/entity/Q15413,anjaw,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,260,Q15413,Anjaw,Anjaw -229,changlang,12,arunachal pradesh,12.12,253,changlang,http://www.wikidata.org/entity/Q15427,changlang,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,253,Q15427,Changlang,Changlang -230,dibang valley,12,arunachal pradesh,12.10,257,dibang valley,http://www.wikidata.org/entity/Q15446,dibang valley,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,257,Q15446,Dibang Valley,Dibang Valley -231,east kameng,12,arunachal pradesh,12.03,247,east kameng,http://www.wikidata.org/entity/Q15424,east kameng,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,247,Q15424,East Kameng,East Kameng -232,east siang,12,arunachal pradesh,12.08,251,east siang,http://www.wikidata.org/entity/Q15419,east siang,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,251,Q15419,East Siang,East Siang -718,kamle,12,arunachal pradesh,,,kamle,http://www.wikidata.org/entity/Q48731073,kamle,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q48731073,Kamle,Kamle -677,kra daadi,12,arunachal pradesh,,,kra daadi,http://www.wikidata.org/entity/Q21018627,kra daadi,district of Arunachal Pradesh in India,http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q21018627,Kra Daadi,Kra Daadi -233,kurung kumey,12,arunachal pradesh,12.14,256,kurung kumey,http://www.wikidata.org/entity/Q2449506,kurung kumey,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,256,Q2449506,Kurung Kumey,Kurung Kumey -724,leparada,12,arunachal pradesh,,,lepa rada,http://www.wikidata.org/entity/Q63563632,lepa rada,district of Arunachal Pradesh in India,http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q63563632,Leparada,Lepa Rada -234,lohit,12,arunachal pradesh,12.11,259,lohit,http://www.wikidata.org/entity/Q15438,lohit,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,259,Q15438,Lohit,Lohit -666,longding,12,arunachal pradesh,,,longding,http://www.wikidata.org/entity/Q5627568,longding,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q5627568,Longding,Longding -235,lower dibang valley,12,arunachal pradesh,12.15,258,lower dibang valley,http://www.wikidata.org/entity/Q2373368,lower dibang valley,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,258,Q2373368,Lower Dibang Valley,Lower Dibang Valley -719,lower siang,12,arunachal pradesh,,,lower siang,http://www.wikidata.org/entity/Q13602925,lower siang,district of Arunachal Pradesh,http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q13602925,Lower Siang,Lower Siang -236,lower subansiri,12,arunachal pradesh,12.05,255,lower subansiri,http://www.wikidata.org/entity/Q15436,lower subansiri,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,255,Q15436,Lower Subansiri,Lower Subansiri -678,namsai,12,arunachal pradesh,,,namsai,http://www.wikidata.org/entity/Q21559824,namsai,district of Arunachal Pradesh in India,http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q21559824,Namsai,Namsai -723,pakke kessang,12,arunachal pradesh,,,pakke-kessang,http://www.wikidata.org/entity/Q61439260,pakke-kessang,district of Arunachal Pradesh in India,http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q61439260,Pakke Kessang,Pakke-kessang -237,papum pare,12,arunachal pradesh,12.04,248,papum pare,http://www.wikidata.org/entity/Q15432,papum pare,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,248,Q15432,Papum Pare,Papum Pare -725,shi yomi,12,arunachal pradesh,,,shi yomi,http://www.wikidata.org/entity/Q63563625,shi yomi,district of Arunachal Pradesh in India,http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q63563625,Shi Yomi,Shi Yomi -679,siang,12,arunachal pradesh,,,siang,http://www.wikidata.org/entity/Q18642331,siang,district of Arunachal Pradesh in India,http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q18642331,Siang,Siang -238,tawang,12,arunachal pradesh,12.01,245,tawang,http://www.wikidata.org/entity/Q15449,tawang,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,245,Q15449,Tawang,Tawang -239,tirap,12,arunachal pradesh,12.13,254,tirap,http://www.wikidata.org/entity/Q15448,tirap,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,254,Q15448,Tirap,Tirap -240,upper siang,12,arunachal pradesh,12.09,252,upper siang,http://www.wikidata.org/entity/Q15465,upper siang,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,252,Q15465,Upper Siang,Upper Siang -241,upper subansiri,12,arunachal pradesh,12.06,249,upper subansiri,http://www.wikidata.org/entity/Q15464,upper subansiri,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,249,Q15464,Upper Subansiri,Upper Subansiri -242,west kameng,12,arunachal pradesh,12.02,246,west kameng,http://www.wikidata.org/entity/Q15459,west kameng,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,246,Q15459,West Kameng,West Kameng -243,west siang,12,arunachal pradesh,12.07,250,west siang,http://www.wikidata.org/entity/Q15453,west siang,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,250,Q15453,West Siang,West Siang -739,bajali,18,assam,,,bajali,http://www.wikidata.org/entity/Q101088203,bajali,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,,Q101088203,Bajali,Bajali -616,baksa,18,assam,,324,baksa,http://www.wikidata.org/entity/Q2360266,baksa,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,324,Q2360266,Baksa,Baksa -280,barpeta,18,assam,18.05,303,barpeta,http://www.wikidata.org/entity/Q41249,barpeta,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,303,Q41249,Barpeta,Barpeta -705,biswanath,18,assam,,,biswanath,http://www.wikidata.org/entity/Q28110722,biswanath,"district in Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,,Q28110722,Biswanath,Biswanath -281,bongaigaon,18,assam,18.04,319,bongaigaon,http://www.wikidata.org/entity/Q42197,bongaigaon,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,319,Q42197,Bongaigaon,Bongaigaon -282,cachar,18,assam,18.21,316,cachar,http://www.wikidata.org/entity/Q42209,cachar,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,316,Q42209,Cachar,Cachar -708,charaideo,18,assam,,,charaideo,http://www.wikidata.org/entity/Q24039029,charaideo,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,,Q24039029,Charaideo,Charaideo -612,chirang,18,assam,,320,chirang,http://www.wikidata.org/entity/Q2574898,chirang,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,320,Q2574898,Chirang,Chirang -283,darrang,18,assam,18.08,325,darrang,http://www.wikidata.org/entity/Q42461,darrang,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,325,Q42461,Darrang,Darrang -284,dhemaji,18,assam,18.13,308,dhemaji,http://www.wikidata.org/entity/Q42473,dhemaji,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,308,Q42473,Dhemaji,Dhemaji -285,dhubri,18,assam,18.02,301,dhubri,http://www.wikidata.org/entity/Q42485,dhubri,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,301,Q42485,Dhubri,Dhubri -286,dibrugarh,18,assam,18.15,310,dibrugarh,http://www.wikidata.org/entity/Q42479,dibrugarh,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,310,Q42479,Dibrugarh,Dibrugarh -299,dima hasao,18,assam,18.20,315,dima hasao,http://www.wikidata.org/entity/Q42774,dima hasao,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,315,Q42774,Dima Hasao,Dima Hasao -287,goalpara,18,assam,18.03,302,goalpara,http://www.wikidata.org/entity/Q42522,goalpara,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,302,Q42522,Goalpara,Goalpara -288,golaghat,18,assam,18.18,313,golaghat,http://www.wikidata.org/entity/Q42517,golaghat,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,313,Q42517,Golaghat,Golaghat -289,hailakandi,18,assam,18.23,318,hailakandi,http://www.wikidata.org/entity/Q42505,hailakandi,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,318,Q42505,Hailakandi,Hailakandi -709,hojai,18,assam,,,hojai,http://www.wikidata.org/entity/Q24699407,hojai,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,,Q24699407,Hojai,Hojai -290,jorhat,18,assam,18.17,312,jorhat,http://www.wikidata.org/entity/Q42611,jorhat,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,312,Q42611,Jorhat,Jorhat -291,kamrup,18,assam,18.06,321,kamrup,http://www.wikidata.org/entity/Q2247441,kamrup,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,321,Q2247441,Kamrup,Kamrup -618,kamrup metro,18,assam,,322,kamrup metropolitan,http://www.wikidata.org/entity/Q2464674,kamrup metropolitan,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,322,Q2464674,Kamrup Metro,Kamrup Metropolitan -292,karbi anglong,18,assam,18.19,314,east karbi anglong,http://www.wikidata.org/entity/Q29025081,east karbi anglong,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,,Q29025081,Karbi Anglong,East Karbi Anglong -293,karimganj,18,assam,18.22,317,karimganj,http://www.wikidata.org/entity/Q42542,karimganj,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,317,Q42542,Karimganj,Karimganj -294,kokrajhar,18,assam,18.01,300,kokrajhar,http://www.wikidata.org/entity/Q42618,kokrajhar,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,300,Q42618,Kokrajhar,Kokrajhar -295,lakhimpur,18,assam,18.12,307,lakhimpur,http://www.wikidata.org/entity/Q42743,lakhimpur,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,307,Q42743,Lakhimpur,Lakhimpur -706,majuli,18,assam,,,majuli,http://www.wikidata.org/entity/Q28110729,majuli,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,,Q28110729,Majuli,Majuli -296,marigaon,18,assam,18.09,304,morigaon,http://www.wikidata.org/entity/Q42737,morigaon,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,304,Q42737,Marigaon,Morigaon -297,nagaon,18,assam,18.10,305,nagaon,http://www.wikidata.org/entity/Q42686,nagaon,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,305,Q42686,Nagaon,Nagaon -298,nalbari,18,assam,18.07,323,nalbari,http://www.wikidata.org/entity/Q42779,nalbari,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,323,Q42779,Nalbari,Nalbari -300,sivasagar,18,assam,18.16,311,sivasagar,http://www.wikidata.org/entity/Q42768,sivasagar,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,311,Q42768,Sivasagar,Sivasagar -301,sonitpur,18,assam,18.11,306,sonitpur,http://www.wikidata.org/entity/Q42765,sonitpur,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,306,Q42765,Sonitpur,Sonitpur -707,south salmara mancachar,18,assam,,,south salmara-mankachar,http://www.wikidata.org/entity/Q24907599,south salmara-mankachar,district of Assam in India,http://www.wikidata.org/entity/Q1164,assam,Indian state,,Q24907599,South Salmara Mancachar,South Salmara-mankachar -302,tinsukia,18,assam,18.14,309,tinsukia,http://www.wikidata.org/entity/Q42756,tinsukia,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,309,Q42756,Tinsukia,Tinsukia -617,udalguri,18,assam,,326,udalguri,http://www.wikidata.org/entity/Q321998,udalguri,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,326,Q321998,Udalguri,Udalguri -710,west karbi anglong,18,assam,,,west karbi anglong,http://www.wikidata.org/entity/Q24949218,west karbi anglong,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,,Q24949218,West Karbi Anglong,West Karbi Anglong -188,araria,10,bihar,10.07,209,araria,http://www.wikidata.org/entity/Q42901,araria,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,Indian state,209,Q42901,Araria,Araria -611,arwal,10,bihar,10.33,240,arwal,http://www.wikidata.org/entity/Q42917,arwal,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,Indian state,240,Q42917,Arwal,Arwal -189,aurangabad,10,bihar,10.34,235,aurangabad,http://www.wikidata.org/entity/Q43086,aurangabad,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,Indian state,235,Q43086,Aurangabad,Aurangabad -190,banka,10,bihar,10.23,225,banka,http://www.wikidata.org/entity/Q43097,banka,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,Indian state,225,Q43097,Banka,Banka -191,begusarai,10,bihar,10.20,222,begusarai,http://www.wikidata.org/entity/Q49157,begusarai,"district of 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Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,Indian state,205,Q100095,Sheohar,Sheohar -221,sitamarhi,10,bihar,10.04,206,sitamarhi,http://www.wikidata.org/entity/Q100144,sitamarhi,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,Indian state,206,Q100144,Sitamarhi,Sitamarhi -222,siwan,10,bihar,10.16,218,siwan,http://www.wikidata.org/entity/Q100131,siwan,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,Indian state,218,Q100131,Siwan,Siwan -223,supaul,10,bihar,10.06,208,supaul,http://www.wikidata.org/entity/Q100139,supaul,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,Indian state,208,Q100139,Supaul,Supaul -224,vaishali,10,bihar,10.18,220,vaishali,http://www.wikidata.org/entity/Q100130,vaishali,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,Indian state,220,Q100130,Vaishali,Vaishali 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state,,Q96584972,Gaurella Pendra Marwahi,Gaurela-pendra-marwahi -379,janjgir-champa,22,chhattisgarh,22.06,405,janjgir–champa,http://www.wikidata.org/entity/Q2575633,janjgir–champa,"district of Chhattisgarh, India",http://www.wikidata.org/entity/Q1168,chhattisgarh,Indian state,405,Q2575633,Janjgir-champa,Janjgir–champa -380,jashpur,22,chhattisgarh,22.03,402,jashpur,http://www.wikidata.org/entity/Q2577551,jashpur,"district of Chhattisgarh, India",http://www.wikidata.org/entity/Q1168,chhattisgarh,Indian state,402,Q2577551,Jashpur,Jashpur -382,kabirdham,22,chhattisgarh,22.08,407,kabirdham,http://www.wikidata.org/entity/Q2450255,kabirdham,"district of Chhattisgarh, India",http://www.wikidata.org/entity/Q1168,chhattisgarh,Indian state,407,Q2450255,Kabirdham,Kabirdham -381,kanker,22,chhattisgarh,22.14,413,kanker,http://www.wikidata.org/entity/Q2310530,kanker,"district of Chhattisgarh, India",http://www.wikidata.org/entity/Q1168,chhattisgarh,Indian state,413,Q2310530,Kanker,Kanker 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state,408,Q2341800,Rajnandgaon,Rajnandgaon -642,sukma,22,chhattisgarh,,,sukma,http://www.wikidata.org/entity/Q16933590,sukma,district of Chhattisgarh in India,http://www.wikidata.org/entity/Q1168,chhattisgarh,Indian state,,Q16933590,Sukma,Sukma -648,surajpur,22,chhattisgarh,,,surajpur,http://www.wikidata.org/entity/Q16938031,surajpur,district of Chhattisgarh in India,http://www.wikidata.org/entity/Q1168,chhattisgarh,Indian state,,Q16938031,Surajpur,Surajpur -389,surguja,22,chhattisgarh,22.02,401,surguja,http://www.wikidata.org/entity/Q1805075,surguja,district of Chhattisgarh,http://www.wikidata.org/entity/Q1168,chhattisgarh,Indian state,401,Q1805075,Surguja,Surguja -077,central,07,delhi,07.06,095,central delhi,http://www.wikidata.org/entity/Q107941,central delhi,"district of Delhi, India",http://www.wikidata.org/entity/Q1353,delhi,Indian metropolis and union territory that includes New Delhi,095,Q107941,Central,Central Delhi -078,east,07,delhi,07.04,093,east delhi,http://www.wikidata.org/entity/Q107960,east delhi,"district of Delhi, India",http://www.wikidata.org/entity/Q1353,delhi,Indian metropolis and union territory that includes New Delhi,093,Q107960,East,East Delhi -079,new delhi,07,delhi,07.05,094,new delhi,http://www.wikidata.org/entity/Q110067863,new delhi,"district of Delhi, India",http://www.wikidata.org/entity/Q1353,delhi,Indian metropolis and union territory that includes New Delhi,,Q110067863,New Delhi,New Delhi -080,north,07,delhi,07.02,091,north delhi,http://www.wikidata.org/entity/Q693367,north delhi,"district of Delhi, India",http://www.wikidata.org/entity/Q1353,delhi,Indian metropolis and union territory that includes New Delhi,091,Q693367,North,North Delhi -081,north east,07,delhi,07.03,092,north east delhi,http://www.wikidata.org/entity/Q429329,north east delhi,"district of Delhi, India",http://www.wikidata.org/entity/Q1353,delhi,Indian metropolis and union territory that includes New Delhi,092,Q429329,North East,North East Delhi -082,north west,07,delhi,07.01,090,north west delhi,http://www.wikidata.org/entity/Q766125,north west delhi,"district of Delhi, India",http://www.wikidata.org/entity/Q1353,delhi,Indian metropolis and union territory that includes New Delhi,090,Q766125,North West,North West Delhi -671,shahdara,07,delhi,,,shahdara,http://www.wikidata.org/entity/Q83486,shahdara,"district of East Delhi, India",http://www.wikidata.org/entity/Q1353,delhi,Indian metropolis and union territory that includes New Delhi,,Q83486,Shahdara,Shahdara -083,south,07,delhi,07.09,098,south delhi,http://www.wikidata.org/entity/Q2061938,south delhi,"district of Delhi, India",http://www.wikidata.org/entity/Q1353,delhi,Indian metropolis and union territory that includes New Delhi,098,Q2061938,South,South Delhi -670,south east,07,delhi,,,south east delhi,http://www.wikidata.org/entity/Q25553535,south east delhi,"district in Delhi, India",http://www.wikidata.org/entity/Q1353,delhi,Indian metropolis and union territory that includes New Delhi,,Q25553535,South East,South East Delhi -084,south west,07,delhi,07.08,097,south west delhi,http://www.wikidata.org/entity/Q2379189,south west delhi,"district of Delhi, India",http://www.wikidata.org/entity/Q1353,delhi,Indian metropolis and union territory that includes New Delhi,097,Q2379189,South West,South West Delhi -085,west,07,delhi,07.07,096,west delhi,http://www.wikidata.org/entity/Q549807,west delhi,"district of Delhi, India",http://www.wikidata.org/entity/Q1353,delhi,Indian metropolis and union territory that includes New Delhi,096,Q549807,West,West Delhi -551,north goa,30,goa,30.01,585,north goa,http://www.wikidata.org/entity/Q108234,north goa,"district of Goa, India",http://www.wikidata.org/entity/Q1171,goa,state on the western coast of India,585,Q108234,North Goa,North Goa -552,south goa,30,goa,30.02,586,south goa,http://www.wikidata.org/entity/Q108244,south goa,"district of Goa, India",http://www.wikidata.org/entity/Q1171,goa,state on the western coast of India,586,Q108244,South Goa,South Goa -438,ahmadabad,24,gujarat,24.07,474,ahmedabad,http://www.wikidata.org/entity/Q401686,ahmedabad,district of Gujarat,http://www.wikidata.org/entity/Q1061,gujarat,state of India,474,Q401686,Ahmadabad,Ahmedabad -439,amreli,24,gujarat,24.13,480,amreli,http://www.wikidata.org/entity/Q257946,amreli,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,480,Q257946,Amreli,Amreli -440,anand,24,gujarat,24.15,482,anand,http://www.wikidata.org/entity/Q485683,anand,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,482,Q485683,Anand,Anand -672,arvalli,24,gujarat,,,aravalli,http://www.wikidata.org/entity/Q12175285,aravalli,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,,Q12175285,Arvalli,Aravalli -441,banas kantha,24,gujarat,24.02,469,banaskantha,http://www.wikidata.org/entity/Q806125,banaskantha,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,469,Q806125,Banas Kantha,Banaskantha -442,bharuch,24,gujarat,24.21,488,bharuch,http://www.wikidata.org/entity/Q854900,bharuch,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,488,Q854900,Bharuch,Bharuch -443,bhavnagar,24,gujarat,24.14,481,bhavnagar,http://www.wikidata.org/entity/Q854963,bhavnagar,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,481,Q854963,Bhavnagar,Bhavnagar -676,botad,24,gujarat,,,botad,http://www.wikidata.org/entity/Q14505072,botad,"district in Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,,Q14505072,Botad,Botad -668,chhotaudepur,24,gujarat,,,chhota udaipur,http://www.wikidata.org/entity/Q5979243,chhota udaipur,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,,Q5979243,Chhotaudepur,Chhota Udaipur -444,dang,24,gujarat,24.23,489,dang,http://www.wikidata.org/entity/Q1135616,dang,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,489,Q1135616,Dang,Dang -674,devbhumi dwarka,24,gujarat,,,devbhoomi dwarka,http://www.wikidata.org/entity/Q14594717,devbhoomi dwarka,"district in Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,,Q14594717,Devbhumi Dwarka,Devbhoomi Dwarka -445,dohad,24,gujarat,24.18,485,dahod,http://www.wikidata.org/entity/Q186518,dahod,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,485,Q186518,Dohad,Dahod -446,gandhinagar,24,gujarat,24.06,473,gandhinagar,http://www.wikidata.org/entity/Q1772860,gandhinagar,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,473,Q1772860,Gandhinagar,Gandhinagar -675,gir somnath,24,gujarat,,,gir somnath,http://www.wikidata.org/entity/Q15244465,gir somnath,"district in Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,,Q15244465,Gir Somnath,Gir Somnath -447,jamnagar,24,gujarat,24.10,477,jamnagar,http://www.wikidata.org/entity/Q2982118,jamnagar,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,477,Q2982118,Jamnagar,Jamnagar -448,junagadh,24,gujarat,24.12,479,junagadh,http://www.wikidata.org/entity/Q1797344,junagadh,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,479,Q1797344,Junagadh,Junagadh -449,kachchh,24,gujarat,24.01,468,kutch,http://www.wikidata.org/entity/Q1063417,kutch,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,468,Q1063417,Kachchh,Kutch -450,kheda,24,gujarat,24.16,483,kheda,http://www.wikidata.org/entity/Q1755463,kheda,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,483,Q1755463,Kheda,Kheda -451,mahesana,24,gujarat,24.04,471,mehsana,http://www.wikidata.org/entity/Q2019694,mehsana,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,471,Q2019694,Mahesana,Mehsana -669,mahisagar,24,gujarat,,,mahisagar,http://www.wikidata.org/entity/Q5706885,mahisagar,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,,Q5706885,Mahisagar,Mahisagar -673,morbi,24,gujarat,,,morbi,http://www.wikidata.org/entity/Q5979727,morbi,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,,Q5979727,Morbi,Morbi -452,narmada,24,gujarat,24.20,487,narmada,http://www.wikidata.org/entity/Q1797230,narmada,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,487,Q1797230,Narmada,Narmada -453,navsari,24,gujarat,24.24,490,navsari,http://www.wikidata.org/entity/Q1797349,navsari,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,490,Q1797349,Navsari,Navsari -454,panch mahals,24,gujarat,24.17,484,panchmahal,http://www.wikidata.org/entity/Q1781463,panchmahal,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,484,Q1781463,Panch Mahals,Panchmahal -455,patan,24,gujarat,24.03,470,patan,http://www.wikidata.org/entity/Q1815269,patan,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,470,Q1815269,Patan,Patan -456,porbandar,24,gujarat,24.11,478,porbandar,http://www.wikidata.org/entity/Q1772815,porbandar,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,478,Q1772815,Porbandar,Porbandar -457,rajkot,24,gujarat,24.09,476,rajkot,http://www.wikidata.org/entity/Q1815245,rajkot,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,476,Q1815245,Rajkot,Rajkot -458,sabar kantha,24,gujarat,24.05,472,sabarkantha,http://www.wikidata.org/entity/Q1772856,sabarkantha,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,472,Q1772856,Sabar Kantha,Sabarkantha -459,surat,24,gujarat,24.22,492,surat,http://www.wikidata.org/entity/Q1797317,surat,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,492,Q1797317,Surat,Surat -460,surendranagar,24,gujarat,24.08,475,surendranagar,http://www.wikidata.org/entity/Q237535,surendranagar,"District of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,475,Q237535,Surendranagar,Surendranagar -641,tapi,24,gujarat,,493,tapi,http://www.wikidata.org/entity/Q670165,tapi,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,493,Q670165,Tapi,Tapi -461,vadodara,24,gujarat,24.19,486,vadodara,http://www.wikidata.org/entity/Q578285,vadodara,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,486,Q578285,Vadodara,Vadodara -462,valsad,24,gujarat,24.25,491,valsad,http://www.wikidata.org/entity/Q1946743,valsad,"District of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,491,Q1946743,Valsad,Valsad -058,ambala,06,haryana,06.02,070,ambala,http://www.wikidata.org/entity/Q2086226,ambala,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,070,Q2086226,Ambala,Ambala -059,bhiwani,06,haryana,06.13,081,bhiwani,http://www.wikidata.org/entity/Q1852857,bhiwani,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,081,Q1852857,Bhiwani,Bhiwani -701,charki dadri,06,haryana,,,charkhi dadri,http://www.wikidata.org/entity/Q28172110,charkhi dadri,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,,Q28172110,Charki Dadri,Charkhi Dadri -060,faridabad,06,haryana,06.19,088,faridabad,http://www.wikidata.org/entity/Q2086173,faridabad,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,088,Q2086173,Faridabad,Faridabad -061,fatehabad,06,haryana,06.10,078,fatehabad,http://www.wikidata.org/entity/Q2301753,fatehabad,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,078,Q2301753,Fatehabad,Fatehabad -062,gurugram,06,haryana,06.18,086,gurugram,http://www.wikidata.org/entity/Q1815766,gurugram,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,086,Q1815766,Gurugram,Gurugram -063,hisar,06,haryana,06.12,080,hisar,http://www.wikidata.org/entity/Q1815773,hisar,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,080,Q1815773,Hisar,Hisar -064,jhajjar,06,haryana,06.15,083,jhajjar,http://www.wikidata.org/entity/Q1948260,jhajjar,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,083,Q1948260,Jhajjar,Jhajjar -065,jind,06,haryana,06.09,077,jind,http://www.wikidata.org/entity/Q268605,jind,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,077,Q268605,Jind,Jind -066,kaithal,06,haryana,06.05,073,kaithal,http://www.wikidata.org/entity/Q614037,kaithal,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,073,Q614037,Kaithal,Kaithal -067,karnal,06,haryana,06.06,074,karnal,http://www.wikidata.org/entity/Q607915,karnal,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,074,Q607915,Karnal,Karnal -068,kurukshetra,06,haryana,06.04,072,kurukshetra,http://www.wikidata.org/entity/Q980118,kurukshetra,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,072,Q980118,Kurukshetra,Kurukshetra -069,mahendragarh,06,haryana,06.16,084,mahendragarh,http://www.wikidata.org/entity/Q684019,mahendragarh,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,084,Q684019,Mahendragarh,Mahendragarh -604,nuh,06,haryana,,087,nuh,http://www.wikidata.org/entity/Q2216696,nuh,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,087,Q2216696,Nuh,Nuh -619,palwal,06,haryana,,089,palwal,http://www.wikidata.org/entity/Q2724926,palwal,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,089,Q2724926,Palwal,Palwal -070,panchkula,06,haryana,06.01,069,panchkula,http://www.wikidata.org/entity/Q1898143,panchkula,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,069,Q1898143,Panchkula,Panchkula -071,panipat,06,haryana,06.07,075,panipat,http://www.wikidata.org/entity/Q2086163,panipat,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,075,Q2086163,Panipat,Panipat -072,rewari,06,haryana,06.17,085,rewari,http://www.wikidata.org/entity/Q2301759,rewari,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,085,Q2301759,Rewari,Rewari -073,rohtak,06,haryana,06.14,082,rohtak,http://www.wikidata.org/entity/Q967388,rohtak,"district in Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,082,Q967388,Rohtak,Rohtak -074,sirsa,06,haryana,06.11,079,sirsa,http://www.wikidata.org/entity/Q526101,sirsa,"district in Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,079,Q526101,Sirsa,Sirsa -075,sonipat,06,haryana,06.08,076,sonipat,http://www.wikidata.org/entity/Q2241746,sonipat,"district in Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,076,Q2241746,Sonipat,Sonipat -076,yamunanagar,06,haryana,06.03,071,yamunanagar,http://www.wikidata.org/entity/Q1873644,yamunanagar,"district of Haryana, India",http://www.wikidata.org/entity/Q1174,haryana,state of India,071,Q1873644,Yamunanagar,Yamunanagar -015,bilaspur,02,himachal pradesh,02.08,030,bilaspur,http://www.wikidata.org/entity/Q1478939,bilaspur,"district of Himachal Pradesh, India",http://www.wikidata.org/entity/Q1177,himachal pradesh,Indian state,030,Q1478939,Bilaspur,Bilaspur -016,chamba,02,himachal pradesh,02.01,023,chamba,http://www.wikidata.org/entity/Q1060614,chamba,"district of Himachal Pradesh, India",http://www.wikidata.org/entity/Q1177,himachal pradesh,Indian state,023,Q1060614,Chamba,Chamba -017,hamirpur,02,himachal pradesh,02.06,028,hamirpur,http://www.wikidata.org/entity/Q2086180,hamirpur,"district in Himachal Pradesh, India",http://www.wikidata.org/entity/Q1177,himachal pradesh,Indian state,028,Q2086180,Hamirpur,Hamirpur -018,kangra,02,himachal pradesh,02.02,024,kangra,http://www.wikidata.org/entity/Q727232,kangra,"District in Himachal Pradesh, India",http://www.wikidata.org/entity/Q1177,himachal pradesh,Indian state,024,Q727232,Kangra,Kangra -019,kinnaur,02,himachal pradesh,02.12,034,kinnaur,http://www.wikidata.org/entity/Q1862950,kinnaur,"district of Himachal Pradesh, India",http://www.wikidata.org/entity/Q1177,himachal pradesh,Indian state,034,Q1862950,Kinnaur,Kinnaur -020,kullu,02,himachal pradesh,02.04,026,kullu,http://www.wikidata.org/entity/Q2980880,kullu,"district of Himachal Pradesh, India",http://www.wikidata.org/entity/Q1177,himachal pradesh,Indian state,026,Q2980880,Kullu,Kullu -021,lahul and spiti,02,himachal pradesh,02.03,025,lahaul and spiti,http://www.wikidata.org/entity/Q837595,lahaul and spiti,"district of Himachal Pradesh, India",http://www.wikidata.org/entity/Q1177,himachal pradesh,Indian state,025,Q837595,Lahul and Spiti,Lahaul and Spiti -022,mandi,02,himachal pradesh,02.05,027,mandi,http://www.wikidata.org/entity/Q1892161,mandi,"district of Himachal Pradesh, India",http://www.wikidata.org/entity/Q1177,himachal pradesh,Indian state,027,Q1892161,Mandi,Mandi -023,shimla,02,himachal pradesh,02.11,033,shimla,http://www.wikidata.org/entity/Q1921404,shimla,"district of Himachal Pradesh, India",http://www.wikidata.org/entity/Q1177,himachal pradesh,Indian state,033,Q1921404,Shimla,Shimla -024,sirmaur,02,himachal pradesh,02.10,032,sirmaur,http://www.wikidata.org/entity/Q654331,sirmaur,"district of Himachal Pradesh, India",http://www.wikidata.org/entity/Q1177,himachal pradesh,Indian state,032,Q654331,Sirmaur,Sirmaur -025,solan,02,himachal pradesh,02.09,031,solan,http://www.wikidata.org/entity/Q2980937,solan,"district of Himachal Pradesh, India",http://www.wikidata.org/entity/Q1177,himachal pradesh,Indian state,031,Q2980937,Solan,Solan -026,una,02,himachal pradesh,02.07,029,una,http://www.wikidata.org/entity/Q2301741,una,"district of Himachal Pradesh, India",http://www.wikidata.org/entity/Q1177,himachal pradesh,Indian state,029,Q2301741,Una,Una -001,anantnag,01,jammu and kashmir,01.06,014,anantnag,http://www.wikidata.org/entity/Q2982349,anantnag,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,014,Q2982349,Anantnag,Anantnag -623,bandipora,01,jammu and kashmir,,009,bandipore,http://www.wikidata.org/entity/Q2983553,bandipore,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,009,Q2983553,Bandipora,Bandipore -003,baramulla,01,jammu and kashmir,01.02,008,baramulla,http://www.wikidata.org/entity/Q1912057,baramulla,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,008,Q1912057,Baramulla,Baramulla -002,budgam,01,jammu and kashmir,01.04,002,budgam,http://www.wikidata.org/entity/Q2594218,budgam,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,002,Q2594218,Budgam,Budgam -004,doda,01,jammu and kashmir,01.09,016,doda,http://www.wikidata.org/entity/Q2298979,doda,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,016,Q2298979,Doda,Doda -626,ganderbal,01,jammu and kashmir,,011,ganderbal,http://www.wikidata.org/entity/Q2556028,ganderbal,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,011,Q2556028,Ganderbal,Ganderbal -005,jammu,01,jammu and kashmir,01.13,021,jammu,http://www.wikidata.org/entity/Q1947371,jammu,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,021,Q1947371,Jammu,Jammu -007,kathua,01,jammu and kashmir,01.14,007,kathua,http://www.wikidata.org/entity/Q2375700,kathua,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,007,Q2375700,Kathua,Kathua -620,kishtwar,01,jammu and kashmir,01.09,018,kishtwar,http://www.wikidata.org/entity/Q2321899,kishtwar,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,018,Q2321899,Kishtwar,Kishtwar -622,kulgam,01,jammu and kashmir,,015,kulgam,http://www.wikidata.org/entity/Q2321867,kulgam,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,015,Q2321867,Kulgam,Kulgam -008,kupwara,01,jammu and kashmir,01.01,001,kupwara,http://www.wikidata.org/entity/Q2297306,kupwara,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,001,Q2297306,Kupwara,Kupwara -010,poonch,01,jammu and kashmir,01.11,005,poonch,http://www.wikidata.org/entity/Q2983134,poonch,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,005,Q2983134,Poonch,Poonch -011,pulwama,01,jammu and kashmir,01.05,012,pulwama,http://www.wikidata.org/entity/Q2085364,pulwama,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,012,Q2085364,Pulwama,Pulwama -012,rajouri,01,jammu and kashmir,01.12,006,rajouri,http://www.wikidata.org/entity/Q544279,rajouri,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,006,Q544279,Rajouri,Rajouri -621,ramban,01,jammu and kashmir,01.09,017,ramban,http://www.wikidata.org/entity/Q2321939,ramban,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,017,Q2321939,Ramban,Ramban -627,reasi,01,jammu and 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India,010,Q1506029,Srinagar,Srinagar -014,udhampur,01,jammu and kashmir,01.10,019,udhampur,http://www.wikidata.org/entity/Q1947311,udhampur,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by India,019,Q1947311,Udhampur,Udhampur -322,bokaro,20,jharkhand,20.13,355,bokaro,http://www.wikidata.org/entity/Q2295925,bokaro,"district of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,355,Q2295925,Bokaro,Bokaro -323,chatra,20,jharkhand,20.03,347,chatra,http://www.wikidata.org/entity/Q1979499,chatra,"district of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,347,Q1979499,Chatra,Chatra -324,deoghar,20,jharkhand,20.07,350,deoghar,http://www.wikidata.org/entity/Q2030017,deoghar,"district of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,350,Q2030017,Deoghar,Deoghar -325,dhanbad,20,jharkhand,20.12,354,dhanbad,http://www.wikidata.org/entity/Q2240791,dhanbad,"District of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,354,Q2240791,Dhanbad,Dhanbad -326,dumka,20,jharkhand,20.11,362,dumka,http://www.wikidata.org/entity/Q2577657,dumka,"district of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,362,Q2577657,Dumka,Dumka -327,east singhbum,20,jharkhand,20.18,357,east singhbhum,http://www.wikidata.org/entity/Q2452921,east singhbhum,"district of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,357,Q2452921,East Singhbum,East Singhbhum -328,garhwa,20,jharkhand,20.01,346,garhwa,http://www.wikidata.org/entity/Q2302076,garhwa,"district of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,346,Q2302076,Garhwa,Garhwa -329,giridih,20,jharkhand,20.06,349,giridih,http://www.wikidata.org/entity/Q2302065,giridih,"district of Jharkhand, 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India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,353,Q2295930,Pakur,Pakur -338,palamu,20,jharkhand,20.02,358,palamu,http://www.wikidata.org/entity/Q1797254,palamu,"district of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,358,Q1797254,Palamu,Palamu -607,ramgarh,20,jharkhand,20.04,361,ramgarh,http://www.wikidata.org/entity/Q2663612,ramgarh,"district of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,361,Q2663612,Ramgarh,Ramgarh -339,ranchi,20,jharkhand,20.14,364,ranchi,http://www.wikidata.org/entity/Q1947380,ranchi,"district of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,364,Q1947380,Ranchi,Ranchi -340,sahebganj,20,jharkhand,20.09,352,sahebganj,http://www.wikidata.org/entity/Q767878,sahebganj,"district of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,352,Q767878,Sahebganj,Sahebganj -341,saraikela kharsawan,20,jharkhand,20.17,369,seraikela kharsawan,http://www.wikidata.org/entity/Q2362658,seraikela kharsawan,"district of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,369,Q2362658,Saraikela Kharsawan,Seraikela Kharsawan -342,simdega,20,jharkhand,20.21,367,simdega,http://www.wikidata.org/entity/Q2597889,simdega,"district in Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,367,Q2597889,Simdega,Simdega -343,west singhbhum,20,jharkhand,20.17,368,west singhbhum,http://www.wikidata.org/entity/Q1950527,west singhbhum,"district of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,368,Q1950527,West Singhbhum,West Singhbhum -524,bagalkote,29,karnataka,29.02,556,bagalkot,http://www.wikidata.org/entity/Q1910231,bagalkot,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,556,Q1910231,Bagalkote,Bagalkot -528,ballari,29,karnataka,29.12,565,ballari,http://www.wikidata.org/entity/Q1791926,ballari,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,565,Q1791926,Ballari,Ballari -527,belagavi,29,karnataka,29.01,555,belagavi,http://www.wikidata.org/entity/Q815464,belagavi,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,555,Q815464,Belagavi,Belagavi -526,bengaluru rural,29,karnataka,29.21,583,bengaluru rural,http://www.wikidata.org/entity/Q806464,bengaluru rural,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,583,Q806464,Bengaluru Rural,Bengaluru Rural -525,bengaluru urban,29,karnataka,29.20,572,bengaluru urban,http://www.wikidata.org/entity/Q806463,bengaluru urban,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,572,Q806463,Bengaluru Urban,Bengaluru Urban -529,bidar,29,karnataka,29.05,558,bidar,http://www.wikidata.org/entity/Q1790568,bidar,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,558,Q1790568,Bidar,Bidar -531,chamarajanagara,29,karnataka,29.27,578,chamarajanagar,http://www.wikidata.org/entity/Q862912,chamarajanagar,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,578,Q862912,Chamarajanagara,Chamarajanagar -630,chikkaballapura,29,karnataka,29.19,582,chikkaballapura,http://www.wikidata.org/entity/Q1072629,chikkaballapura,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,582,Q1072629,Chikkaballapura,Chikkaballapura -532,chikkamagaluru,29,karnataka,29.17,570,chikkamagaluru,http://www.wikidata.org/entity/Q743077,chikkamagaluru,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,570,Q743077,Chikkamagaluru,Chikkamagaluru -533,chitradurga,29,karnataka,29.13,566,chitradurga,http://www.wikidata.org/entity/Q165264,chitradurga,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,566,Q165264,Chitradurga,Chitradurga -534,dakshina kannada,29,karnataka,29.24,575,dakshina kannada,http://www.wikidata.org/entity/Q950571,dakshina kannada,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,575,Q950571,Dakshina Kannada,Dakshina Kannada -535,davangere,29,karnataka,29.14,567,davanagere,http://www.wikidata.org/entity/Q1863214,davanagere,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,567,Q1863214,Davangere,Davanagere -536,dharwad,29,karnataka,29.09,562,dharwad,http://www.wikidata.org/entity/Q1790904,dharwad,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,562,Q1790904,Dharwad,Dharwad -537,gadag,29,karnataka,29.08,561,gadag,http://www.wikidata.org/entity/Q2353931,gadag,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,561,Q2353931,Gadag,Gadag -539,hassan,29,karnataka,29.23,574,hassan,http://www.wikidata.org/entity/Q956732,hassan,"district in Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,574,Q956732,Hassan,Hassan -540,haveri,29,karnataka,29.11,564,haveri,http://www.wikidata.org/entity/Q765481,haveri,"district in Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,564,Q765481,Haveri,Haveri -538,kalaburagi,29,karnataka,29.04,579,kalaburgi,http://www.wikidata.org/entity/Q2641873,kalaburgi,"district in Gulbarga division, Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,579,Q2641873,Kalaburagi,Kalaburgi -541,kodagu,29,karnataka,29.25,576,kodagu,http://www.wikidata.org/entity/Q1553185,kodagu,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,576,Q1553185,Kodagu,Kodagu -542,kolar,29,karnataka,29.19,581,kolar,http://www.wikidata.org/entity/Q2509866,kolar,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,581,Q2509866,Kolar,Kolar -543,koppal,29,karnataka,29.07,560,koppal,http://www.wikidata.org/entity/Q956387,koppal,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,560,Q956387,Koppal,Koppal -544,mandya,29,karnataka,29.22,573,mandya,http://www.wikidata.org/entity/Q2768290,mandya,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,573,Q2768290,Mandya,Mandya -545,mysuru,29,karnataka,29.26,577,mysore,http://www.wikidata.org/entity/Q591781,mysore,"district in Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,577,Q591781,Mysuru,Mysore -546,raichur,29,karnataka,29.06,559,raichur,http://www.wikidata.org/entity/Q1430830,raichur,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,559,Q1430830,Raichur,Raichur -631,ramanagara,29,karnataka,29.21,584,ramanagara,http://www.wikidata.org/entity/Q427679,ramanagara,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,584,Q427679,Ramanagara,Ramanagara -547,shivamogga,29,karnataka,29.15,568,shimoga,http://www.wikidata.org/entity/Q2981389,shimoga,"district in Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,568,Q2981389,Shivamogga,Shimoga -548,tumakuru,29,karnataka,29.18,571,tumakuru,http://www.wikidata.org/entity/Q1301635,tumakuru,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,571,Q1301635,Tumakuru,Tumakuru -549,udupi,29,karnataka,29.16,569,udupi,http://www.wikidata.org/entity/Q1483337,udupi,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,569,Q1483337,Udupi,Udupi -550,uttara kannada,29,karnataka,29.10,563,uttara kannada,http://www.wikidata.org/entity/Q579205,uttara kannada,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,563,Q579205,Uttara Kannada,Uttara Kannada -738,vijayanagar,29,karnataka,,,vijayanagara,http://www.wikidata.org/entity/Q104876850,vijayanagara,district of Karnataka in India,http://www.wikidata.org/entity/Q1185,karnataka,Indian state,,Q104876850,Vijayanagar,Vijayanagara -530,vijayapura,29,karnataka,29.03,557,vijaypura,http://www.wikidata.org/entity/Q83108,vijaypura,"district in Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,557,Q83108,Vijayapura,Vijaypura -635,yadgir,29,karnataka,29.04,580,yadgir,http://www.wikidata.org/entity/Q1786949,yadgir,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,580,Q1786949,Yadgir,Yadgir -554,alappuzha,32,kerala,32.11,598,alappuzha,http://www.wikidata.org/entity/Q928959,alappuzha,"district of Kerala, India",http://www.wikidata.org/entity/Q1186,kerala,Indian state,598,Q928959,Alappuzha,Alappuzha -555,ernakulam,32,kerala,32.08,595,ernakulam,http://www.wikidata.org/entity/Q1356097,ernakulam,"district of Kerala, India",http://www.wikidata.org/entity/Q1186,kerala,Indian state,595,Q1356097,Ernakulam,Ernakulam -556,idukki,32,kerala,32.09,596,idukki,http://www.wikidata.org/entity/Q301821,idukki,"district of Kerala, India",http://www.wikidata.org/entity/Q1186,kerala,Indian state,596,Q301821,Idukki,Idukki -557,kannur,32,kerala,32.02,589,kannur,http://www.wikidata.org/entity/Q2980652,kannur,"district of Kerala, India",http://www.wikidata.org/entity/Q1186,kerala,Indian state,589,Q2980652,Kannur,Kannur -558,kasaragod,32,kerala,32.01,588,kasaragod,http://www.wikidata.org/entity/Q1419703,kasaragod,"District of Kerala, India",http://www.wikidata.org/entity/Q1186,kerala,Indian state,588,Q1419703,Kasaragod,Kasaragod -559,kollam,32,kerala,32.13,600,kollam,http://www.wikidata.org/entity/Q1356124,kollam,"district of Kerala, India",http://www.wikidata.org/entity/Q1186,kerala,Indian state,600,Q1356124,Kollam,Kollam -560,kottayam,32,kerala,32.10,597,kottayam,http://www.wikidata.org/entity/Q1353354,kottayam,"district of Kerala, India",http://www.wikidata.org/entity/Q1186,kerala,Indian state,597,Q1353354,Kottayam,Kottayam -561,kozhikode,32,kerala,32.04,591,kozhikode,http://www.wikidata.org/entity/Q1142979,kozhikode,"district of Kerala, India",http://www.wikidata.org/entity/Q1186,kerala,Indian state,591,Q1142979,Kozhikode,Kozhikode -562,malappuram,32,kerala,32.05,592,malappuram,http://www.wikidata.org/entity/Q1030918,malappuram,"district of Kerala, India",http://www.wikidata.org/entity/Q1186,kerala,Indian state,592,Q1030918,Malappuram,Malappuram -563,palakkad,32,kerala,32.06,593,palakkad,http://www.wikidata.org/entity/Q1535742,palakkad,"district of Kerala, India",http://www.wikidata.org/entity/Q1186,kerala,Indian state,593,Q1535742,Palakkad,Palakkad -564,pathanamthitta,32,kerala,32.12,599,pathanamthitta,http://www.wikidata.org/entity/Q634935,pathanamthitta,"district of Kerala, India",http://www.wikidata.org/entity/Q1186,kerala,Indian state,599,Q634935,Pathanamthitta,Pathanamthitta -565,thiruvananthapuram,32,kerala,32.14,601,thiruvananthapuram,http://www.wikidata.org/entity/Q162612,thiruvananthapuram,"district of Kerala, India",http://www.wikidata.org/entity/Q1186,kerala,Indian state,601,Q162612,Thiruvananthapuram,Thiruvananthapuram -566,thrissur,32,kerala,32.07,594,thrissur,http://www.wikidata.org/entity/Q2429655,thrissur,"district of Kerala, India",http://www.wikidata.org/entity/Q1186,kerala,Indian state,594,Q2429655,Thrissur,Thrissur -567,wayanad,32,kerala,32.03,590,wayanad,http://www.wikidata.org/entity/Q1364427,wayanad,"district of Kerala, India",http://www.wikidata.org/entity/Q1186,kerala,Indian state,590,Q1364427,Wayanad,Wayanad -006,kargil,37,ladakh,01.08,004,kargil,http://www.wikidata.org/entity/Q1650798,kargil,"district of Ladakh, India",http://www.wikidata.org/entity/Q200667,ladakh,union territory administered by India,004,Q1650798,Kargil,Kargil -009,leh ladakh,37,ladakh,01.07,003,leh,http://www.wikidata.org/entity/Q1921210,leh,"district in Ladakh, India",http://www.wikidata.org/entity/Q200667,ladakh,union territory administered by India,003,Q1921210,Leh Ladakh,Leh -553,lakshadweep district,31,lakshadweep,31.01,587,lakshadweep,http://www.wikidata.org/entity/Q10784153,lakshadweep,"District in Lakshadweep Union Territory, India",http://www.wikidata.org/entity/Q26927,lakshadweep,Union Territory of India,587,Q10784153,Lakshadweep District,Lakshadweep -667,agar malwa,23,madhya pradesh,,,agar malwa,http://www.wikidata.org/entity/Q15732396,agar malwa,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,,Q15732396,Agar Malwa,Agar Malwa -639,alirajpur,23,madhya pradesh,23.24,465,alirajpur,http://www.wikidata.org/entity/Q2667586,alirajpur,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,465,Q2667586,Alirajpur,Alirajpur -390,anuppur,23,madhya pradesh,23.16,461,anuppur,http://www.wikidata.org/entity/Q2299093,anuppur,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,461,Q2299093,Anuppur,Anuppur -391,ashoknagar,23,madhya pradesh,23.46,459,ashoknagar,http://www.wikidata.org/entity/Q2246416,ashoknagar,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,459,Q2246416,Ashoknagar,Ashoknagar -392,balaghat,23,madhya pradesh,23.45,457,balaghat,http://www.wikidata.org/entity/Q641904,balaghat,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,457,Q641904,Balaghat,Balaghat -393,barwani,23,madhya pradesh,23.28,441,barwani,http://www.wikidata.org/entity/Q2126754,barwani,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,441,Q2126754,Barwani,Barwani -394,betul,23,madhya pradesh,23.35,447,betul,http://www.wikidata.org/entity/Q1815279,betul,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,447,Q1815279,Betul,Betul -395,bhind,23,madhya pradesh,23.03,420,bhind,http://www.wikidata.org/entity/Q2341700,bhind,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,420,Q2341700,Bhind,Bhind -396,bhopal,23,madhya pradesh,23.32,444,bhopal,http://www.wikidata.org/entity/Q1797245,bhopal,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,444,Q1797245,Bhopal,Bhopal -397,burhanpur,23,madhya pradesh,23.29,467,burhanpur,http://www.wikidata.org/entity/Q2125592,burhanpur,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,467,Q2125592,Burhanpur,Burhanpur -398,chhatarpur,23,madhya pradesh,23.09,425,chhatarpur,http://www.wikidata.org/entity/Q2449785,chhatarpur,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,425,Q2449785,Chhatarpur,Chhatarpur -399,chhindwara,23,madhya pradesh,23.43,455,chhindwara,http://www.wikidata.org/entity/Q1986096,chhindwara,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,455,Q1986096,Chhindwara,Chhindwara -400,damoh,23,madhya pradesh,23.12,428,damoh,http://www.wikidata.org/entity/Q2479331,damoh,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,428,Q2479331,Damoh,Damoh -401,datia,23,madhya pradesh,23.05,422,datia,http://www.wikidata.org/entity/Q2206266,datia,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,422,Q2206266,Datia,Datia -402,dewas,23,madhya pradesh,23.23,437,dewas,http://www.wikidata.org/entity/Q2025998,dewas,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,437,Q2025998,Dewas,Dewas -403,dhar,23,madhya pradesh,23.25,438,dhar,http://www.wikidata.org/entity/Q2299069,dhar,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,438,Q2299069,Dhar,Dhar -404,dindori,23,madhya pradesh,23.41,453,dindori,http://www.wikidata.org/entity/Q2398551,dindori,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,453,Q2398551,Dindori,Dindori -405,east nimar,23,madhya pradesh,23.29,466,khandwa,http://www.wikidata.org/entity/Q2085436,khandwa,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,466,Q2085436,East Nimar,Khandwa -406,guna,23,madhya pradesh,23.07,458,guna,http://www.wikidata.org/entity/Q930027,guna,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,458,Q930027,Guna,Guna -407,gwalior,23,madhya pradesh,23.04,421,gwalior,http://www.wikidata.org/entity/Q2085310,gwalior,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,421,Q2085310,Gwalior,Gwalior -408,harda,23,madhya pradesh,23.36,448,harda,http://www.wikidata.org/entity/Q2173003,harda,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,448,Q2173003,Harda,Harda -409,hoshangabad,23,madhya pradesh,23.37,449,narmadapuram,http://www.wikidata.org/entity/Q620801,narmadapuram,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,449,Q620801,Hoshangabad,Narmadapuram -410,indore,23,madhya pradesh,23.26,439,indore,http://www.wikidata.org/entity/Q742938,indore,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,439,Q742938,Indore,Indore -411,jabalpur,23,madhya pradesh,23.39,451,jabalpur,http://www.wikidata.org/entity/Q632093,jabalpur,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,451,Q632093,Jabalpur,Jabalpur -412,jhabua,23,madhya pradesh,23.24,464,jhabua,http://www.wikidata.org/entity/Q2085336,jhabua,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,464,Q2085336,Jhabua,Jhabua -413,katni,23,madhya pradesh,23.38,450,katni,http://www.wikidata.org/entity/Q746441,katni,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,450,Q746441,Katni,Katni -414,khargone,23,madhya pradesh,23.27,440,khargone,http://www.wikidata.org/entity/Q2273900,khargone,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,440,Q2273900,Khargone,Khargone -415,mandla,23,madhya pradesh,23.42,454,mandla,http://www.wikidata.org/entity/Q2341670,mandla,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,454,Q2341670,Mandla,Mandla -416,mandsaur,23,madhya pradesh,23.19,433,mandsaur,http://www.wikidata.org/entity/Q1870014,mandsaur,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,433,Q1870014,Mandsaur,Mandsaur -417,morena,23,madhya pradesh,23.02,419,morena,http://www.wikidata.org/entity/Q2341467,morena,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,419,Q2341467,Morena,Morena -418,narsinghpur,23,madhya pradesh,23.40,452,narsinghpur,http://www.wikidata.org/entity/Q2341616,narsinghpur,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,452,Q2341616,Narsinghpur,Narsinghpur -419,neemuch,23,madhya pradesh,23.18,432,neemuch,http://www.wikidata.org/entity/Q2341713,neemuch,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,432,Q2341713,Neemuch,Neemuch -722,niwari,23,madhya pradesh,,,niwari,http://www.wikidata.org/entity/Q63563797,niwari,district of Madhya Pradesh in India,http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,,Q63563797,Niwari,Niwari -420,panna,23,madhya pradesh,23.10,426,panna,http://www.wikidata.org/entity/Q2341630,panna,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,426,Q2341630,Panna,Panna -421,raisen,23,madhya pradesh,23.34,446,raisen,http://www.wikidata.org/entity/Q1815223,raisen,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,446,Q1815223,Raisen,Raisen -422,rajgarh,23,madhya pradesh,23.30,442,rajgarh,http://www.wikidata.org/entity/Q1833306,rajgarh,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,442,Q1833306,Rajgarh,Rajgarh -423,ratlam,23,madhya pradesh,23.20,434,ratlam,http://www.wikidata.org/entity/Q2299164,ratlam,"district of Madhya Pradesh, 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pradesh,23.44,456,seoni,http://www.wikidata.org/entity/Q2221184,seoni,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,456,Q2221184,Seoni,Seoni -429,shahdol,23,madhya pradesh,23.16,460,shahdol,http://www.wikidata.org/entity/Q2085464,shahdol,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,460,Q2085464,Shahdol,Shahdol -430,shajapur,23,madhya pradesh,23.22,436,shajapur,http://www.wikidata.org/entity/Q2449803,shajapur,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,436,Q2449803,Shajapur,Shajapur -431,sheopur,23,madhya pradesh,23.01,418,sheopur,http://www.wikidata.org/entity/Q620105,sheopur,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,418,Q620105,Sheopur,Sheopur -432,shivpuri,23,madhya pradesh,23.06,423,shivpuri,http://www.wikidata.org/entity/Q2299042,shivpuri,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,423,Q2299042,Shivpuri,Shivpuri -433,sidhi,23,madhya pradesh,23.17,462,sidhi,http://www.wikidata.org/entity/Q2449793,sidhi,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,462,Q2449793,Sidhi,Sidhi -638,singrauli,23,madhya pradesh,,463,singrauli,http://www.wikidata.org/entity/Q2668638,singrauli,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,463,Q2668638,Singrauli,Singrauli -434,tikamgarh,23,madhya pradesh,23.08,424,tikamgarh,http://www.wikidata.org/entity/Q2449760,tikamgarh,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,424,Q2449760,Tikamgarh,Tikamgarh -435,ujjain,23,madhya pradesh,23.21,435,ujjain,http://www.wikidata.org/entity/Q892641,ujjain,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,435,Q892641,Ujjain,Ujjain -436,umaria,23,madhya pradesh,23.15,431,umaria,http://www.wikidata.org/entity/Q620297,umaria,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,431,Q620297,Umaria,Umaria -437,vidisha,23,madhya pradesh,23.31,443,vidisha,http://www.wikidata.org/entity/Q1815253,vidisha,"district of Madhya Pradesh, India",http://www.wikidata.org/entity/Q1188,madhya pradesh,Indian state,443,Q1815253,Vidisha,Vidisha -466,ahmednagar,27,maharashtra,27.26,522,ahmednagar,http://www.wikidata.org/entity/Q401744,ahmednagar,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,522,Q401744,Ahmednagar,Ahmednagar -467,akola,27,maharashtra,27.05,501,akola,http://www.wikidata.org/entity/Q520510,akola,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,501,Q520510,Akola,Akola -468,amravati,27,maharashtra,27.07,503,amravati,http://www.wikidata.org/entity/Q1771774,amravati,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,503,Q1771774,Amravati,Amravati -469,aurangabad,27,maharashtra,27.19,515,aurangabad,http://www.wikidata.org/entity/Q592942,aurangabad,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,515,Q592942,Aurangabad,Aurangabad -470,beed,27,maharashtra,27.27,523,beed,http://www.wikidata.org/entity/Q814037,beed,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,523,Q814037,Beed,Beed -471,bhandara,27,maharashtra,27.10,506,bhandara,http://www.wikidata.org/entity/Q1813857,bhandara,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,506,Q1813857,Bhandara,Bhandara -472,buldhana,27,maharashtra,27.04,500,buldhana,http://www.wikidata.org/entity/Q47929,buldhana,"district of Maharashtra, 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-477,hingoli,27,maharashtra,27.16,512,hingoli,http://www.wikidata.org/entity/Q2087615,hingoli,"district in Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,512,Q2087615,Hingoli,Hingoli -478,jalgaon,27,maharashtra,27.03,499,jalgaon,http://www.wikidata.org/entity/Q1797291,jalgaon,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,499,Q1797291,Jalgaon,Jalgaon -479,jalna,27,maharashtra,27.18,514,jalna,http://www.wikidata.org/entity/Q1804863,jalna,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,514,Q1804863,Jalna,Jalna -480,kolhapur,27,maharashtra,27.34,530,kolhapur,http://www.wikidata.org/entity/Q1797312,kolhapur,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,530,Q1797312,Kolhapur,Kolhapur -481,latur,27,maharashtra,27.28,524,latur,http://www.wikidata.org/entity/Q1948713,latur,"district of Maharashtra, 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state,511,Q692389,Nanded,Nanded -486,nandurbar,27,maharashtra,27.01,497,nandurbar,http://www.wikidata.org/entity/Q1623525,nandurbar,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,497,Q1623525,Nandurbar,Nandurbar -487,nashik,27,maharashtra,27.20,516,nashik,http://www.wikidata.org/entity/Q1797269,nashik,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,516,Q1797269,Nashik,Nashik -488,osmanabad,27,maharashtra,27.29,525,osmanabad,http://www.wikidata.org/entity/Q1647186,osmanabad,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,525,Q1647186,Osmanabad,Osmanabad -665,palghar,27,maharashtra,,,palghar,http://www.wikidata.org/entity/Q18003119,palghar,"District in Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,,Q18003119,Palghar,Palghar -489,parbhani,27,maharashtra,27.17,513,parbhani,http://www.wikidata.org/entity/Q1797389,parbhani,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,513,Q1797389,Parbhani,Parbhani -490,pune,27,maharashtra,27.25,521,pune,http://www.wikidata.org/entity/Q1797336,pune,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,521,Q1797336,Pune,Pune -491,raigad,27,maharashtra,27.24,520,raigad,http://www.wikidata.org/entity/Q2019683,raigad,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,520,Q2019683,Raigad,Raigad -492,ratnagiri,27,maharashtra,27.32,528,ratnagiri,http://www.wikidata.org/entity/Q1771768,ratnagiri,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,528,Q1771768,Ratnagiri,Ratnagiri -493,sangli,27,maharashtra,27.35,531,sangli,http://www.wikidata.org/entity/Q1425060,sangli,district of Maharashtra state in west-central India,http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,531,Q1425060,Sangli,Sangli -494,satara,27,maharashtra,27.31,527,satara,http://www.wikidata.org/entity/Q1135612,satara,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,527,Q1135612,Satara,Satara -495,sindhudurg,27,maharashtra,27.33,529,sindhudurg,http://www.wikidata.org/entity/Q768332,sindhudurg,"district in Maharashtra , India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,529,Q768332,Sindhudurg,Sindhudurg -496,solapur,27,maharashtra,27.30,526,solapur,http://www.wikidata.org/entity/Q1797263,solapur,district in Maharashtra state of India,http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,526,Q1797263,Solapur,Solapur -497,thane,27,maharashtra,27.21,517,thane,http://www.wikidata.org/entity/Q943099,thane,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,517,Q943099,Thane,Thane -498,wardha,27,maharashtra,27.08,504,wardha,http://www.wikidata.org/entity/Q980608,wardha,"district in Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,504,Q980608,Wardha,Wardha -499,washim,27,maharashtra,27.06,502,washim,http://www.wikidata.org/entity/Q1804858,washim,"district in Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,502,Q1804858,Washim,Washim -500,yavatmal,27,maharashtra,27.14,510,yavatmal,http://www.wikidata.org/entity/Q1804852,yavatmal,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,Indian state,510,Q1804852,Yavatmal,Yavatmal -252,bishnupur,14,manipur,14.04,275,bishnupur,http://www.wikidata.org/entity/Q938190,bishnupur,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,275,Q938190,Bishnupur,Bishnupur -253,chandel,14,manipur,14.09,280,chandel,http://www.wikidata.org/entity/Q2301769,chandel,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,280,Q2301769,Chandel,Chandel -254,churachandpur,14,manipur,14.03,274,churachandpur,http://www.wikidata.org/entity/Q2577281,churachandpur,"District of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,274,Q2577281,Churachandpur,Churachandpur -255,imphal east,14,manipur,14.07,278,imphal east,http://www.wikidata.org/entity/Q1916666,imphal east,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,278,Q1916666,Imphal East,Imphal East -256,imphal west,14,manipur,14.06,277,imphal west,http://www.wikidata.org/entity/Q1822188,imphal west,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,277,Q1822188,Imphal West,Imphal West -713,jiribam,14,manipur,,,jiribam,http://www.wikidata.org/entity/Q28419387,jiribam,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,,Q28419387,Jiribam,Jiribam 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-257,senapati,14,manipur,14.01,272,senapati,http://www.wikidata.org/entity/Q2301706,senapati,district of Manipur,http://www.wikidata.org/entity/Q1193,manipur,Indian state,272,Q2301706,Senapati,Senapati -258,tamenglong,14,manipur,14.02,273,tamenglong,http://www.wikidata.org/entity/Q2301717,tamenglong,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,273,Q2301717,Tamenglong,Tamenglong -716,tengnoupal,14,manipur,,,tengnoupal,http://www.wikidata.org/entity/Q28419388,tengnoupal,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,,Q28419388,Tengnoupal,Tengnoupal -259,thoubal,14,manipur,14.05,276,thoubal,http://www.wikidata.org/entity/Q2086198,thoubal,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,276,Q2086198,Thoubal,Thoubal -260,ukhrul,14,manipur,14.08,279,ukhrul,http://www.wikidata.org/entity/Q735101,ukhrul,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,279,Q735101,Ukhrul,Ukhrul -273,east garo hills,17,meghalaya,17.02,294,east garo hills,http://www.wikidata.org/entity/Q2085455,east garo hills,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,294,Q2085455,East Garo Hills,East Garo Hills -657,east jaintia hills,17,meghalaya,,,east jaintia hills,http://www.wikidata.org/entity/Q15923776,east jaintia hills,district of Meghalaya in India,http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,,Q15923776,East Jaintia Hills,East Jaintia Hills -274,east khasi hills,17,meghalaya,17.06,298,east khasi hills,http://www.wikidata.org/entity/Q1945304,east khasi hills,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,298,Q1945304,East Khasi Hills,East Khasi Hills -656,north garo hills,17,meghalaya,,,north garo hills,http://www.wikidata.org/entity/Q7055466,north garo hills,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,,Q7055466,North Garo Hills,North Garo Hills -276,ri bhoi,17,meghalaya,17.05,297,ri-bhoi,http://www.wikidata.org/entity/Q1884672,ri-bhoi,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,297,Q1884672,Ri Bhoi,Ri-bhoi -277,south garo hills,17,meghalaya,17.03,295,south garo hills,http://www.wikidata.org/entity/Q2329228,south garo hills,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,295,Q2329228,South Garo Hills,South Garo Hills -663,south west garo hills,17,meghalaya,,,south west garo hills,http://www.wikidata.org/entity/Q15961576,south west garo hills,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,,Q15961576,South West Garo Hills,South West Garo Hills -658,south west khasi hills,17,meghalaya,,,south west khasi hills,http://www.wikidata.org/entity/Q15923741,south west khasi hills,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,,Q15923741,South West Khasi Hills,South West Khasi Hills -278,west garo hills,17,meghalaya,17.01,293,west garo hills,http://www.wikidata.org/entity/Q2329181,west garo hills,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,293,Q2329181,West Garo Hills,West Garo Hills -275,west jaintia hills,17,meghalaya,17.07,299,west jaintia hills,http://www.wikidata.org/entity/Q13181190,west jaintia hills,district of Meghalaya,http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,,Q13181190,West Jaintia Hills,West Jaintia Hills -279,west khasi hills,17,meghalaya,17.04,296,west khasi hills,http://www.wikidata.org/entity/Q2064752,west khasi hills,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,296,Q2064752,West Khasi Hills,West Khasi Hills -261,aizawl,15,mizoram,15.03,283,aizawl,http://www.wikidata.org/entity/Q1947322,aizawl,"district of Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,283,Q1947322,Aizawl,Aizawl -262,champhai,15,mizoram,15.04,284,champhai,http://www.wikidata.org/entity/Q1965256,champhai,"district of Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,284,Q1965256,Champhai,Champhai -726,hnahthial,15,mizoram,,,hnahthial,http://www.wikidata.org/entity/Q86882590,hnahthial,district in Mizoram,http://www.wikidata.org/entity/Q1502,mizoram,State in India,,Q86882590,Hnahthial,Hnahthial -728,khawzawl,15,mizoram,,,khawzawl,http://www.wikidata.org/entity/Q86882591,khawzawl,district in Mizoram,http://www.wikidata.org/entity/Q1502,mizoram,State in India,,Q86882591,Khawzawl,Khawzawl -263,kolasib,15,mizoram,15.02,282,kolasib,http://www.wikidata.org/entity/Q1947343,kolasib,"district of Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,282,Q1947343,Kolasib,Kolasib -264,lawngtlai,15,mizoram,15.07,287,lawngtlai,http://www.wikidata.org/entity/Q2086209,lawngtlai,district of Mizoram,http://www.wikidata.org/entity/Q1502,mizoram,State in India,287,Q2086209,Lawngtlai,Lawngtlai -265,lunglei,15,mizoram,15.06,286,lunglei,http://www.wikidata.org/entity/Q1947352,lunglei,"district of Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,286,Q1947352,Lunglei,Lunglei -266,mamit,15,mizoram,15.01,281,mamit,http://www.wikidata.org/entity/Q751531,mamit,"district of Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,281,Q751531,Mamit,Mamit -267,saiha,15,mizoram,15.08,288,saiha,http://www.wikidata.org/entity/Q1821714,saiha,"district of Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,288,Q1821714,Saiha,Saiha -727,saitual,15,mizoram,,,saitual,http://www.wikidata.org/entity/Q86882593,saitual,"district in Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,,Q86882593,Saitual,Saitual -268,serchhip,15,mizoram,15.05,285,serchhip,http://www.wikidata.org/entity/Q2086190,serchhip,"district of Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,285,Q2086190,Serchhip,Serchhip -244,dimapur,13,nagaland,13.06,265,dimapur,http://www.wikidata.org/entity/Q634262,dimapur,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,State in northeastern India,265,Q634262,Dimapur,Dimapur -614,kiphire,13,nagaland,13.02,269,kiphire,http://www.wikidata.org/entity/Q2597908,kiphire,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,State in northeastern India,269,Q2597908,Kiphire,Kiphire -245,kohima,13,nagaland,13.07,270,kohima,http://www.wikidata.org/entity/Q953530,kohima,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,State in northeastern India,270,Q953530,Kohima,Kohima -615,longleng,13,nagaland,13.02,268,longleng,http://www.wikidata.org/entity/Q1426783,longleng,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,State in northeastern India,268,Q1426783,Longleng,Longleng -246,mokokchung,13,nagaland,13.03,262,mokokchung,http://www.wikidata.org/entity/Q2175311,mokokchung,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,State in northeastern India,262,Q2175311,Mokokchung,Mokokchung -247,mon,13,nagaland,13.01,261,mon,http://www.wikidata.org/entity/Q2339648,mon,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,State in northeastern India,261,Q2339648,Mon,Mon -736,noklak,13,nagaland,,,noklak,http://www.wikidata.org/entity/Q48731903,noklak,"district in India, Nagaland",http://www.wikidata.org/entity/Q1599,nagaland,State in northeastern India,,Q48731903,Noklak,Noklak -613,peren,13,nagaland,13.07,271,peren,http://www.wikidata.org/entity/Q516294,peren,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,State in northeastern India,271,Q516294,Peren,Peren -248,phek,13,nagaland,13.08,266,phek,http://www.wikidata.org/entity/Q590882,phek,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,State in northeastern India,266,Q590882,Phek,Phek -249,tuensang,13,nagaland,13.02,267,tuensang,http://www.wikidata.org/entity/Q2571393,tuensang,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,State in northeastern India,267,Q2571393,Tuensang,Tuensang -250,wokha,13,nagaland,13.05,264,wokha,http://www.wikidata.org/entity/Q681821,wokha,district of Nagaland,http://www.wikidata.org/entity/Q1599,nagaland,State in northeastern India,264,Q681821,Wokha,Wokha -251,zunheboto,13,nagaland,13.04,263,zunheboto,http://www.wikidata.org/entity/Q2091461,zunheboto,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,State in northeastern India,263,Q2091461,Zunheboto,Zunheboto -344,anugul,21,odisha,21.15,384,angul,http://www.wikidata.org/entity/Q1772807,angul,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,384,Q1772807,Anugul,Angul -345,balangir,21,odisha,21.24,393,balangir,http://www.wikidata.org/entity/Q804642,balangir,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,393,Q804642,Balangir,Balangir -346,baleshwar,21,odisha,21.08,377,balasore,http://www.wikidata.org/entity/Q2022279,balasore,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,377,Q2022279,Baleshwar,Balasore -347,bargarh,21,odisha,21.01,370,bargarh,http://www.wikidata.org/entity/Q808140,bargarh,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,370,Q808140,Bargarh,Bargarh -348,bhadrak,21,odisha,21.09,378,bhadrak,http://www.wikidata.org/entity/Q685638,bhadrak,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,378,Q685638,Bhadrak,Bhadrak -349,boudh,21,odisha,21.22,391,boudh,http://www.wikidata.org/entity/Q2363639,boudh,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,391,Q2363639,Boudh,Boudh -350,cuttack,21,odisha,21.12,381,cuttack,http://www.wikidata.org/entity/Q2022256,cuttack,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,381,Q2022256,Cuttack,Cuttack -351,deogarh,21,odisha,21.04,373,debagarh,http://www.wikidata.org/entity/Q2269639,debagarh,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,373,Q2269639,Deogarh,Debagarh -352,dhenkanal,21,odisha,21.14,383,dhenkanal,http://www.wikidata.org/entity/Q1948389,dhenkanal,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,383,Q1948389,Dhenkanal,Dhenkanal -353,gajapati,21,odisha,21.20,389,gajapati,http://www.wikidata.org/entity/Q1947292,gajapati,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,389,Q1947292,Gajapati,Gajapati -354,ganjam,21,odisha,21.19,388,ganjam,http://www.wikidata.org/entity/Q776213,ganjam,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,388,Q776213,Ganjam,Ganjam -355,jagatsinghapur,21,odisha,21.11,380,jagatsinghpur,http://www.wikidata.org/entity/Q971581,jagatsinghpur,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,380,Q971581,Jagatsinghapur,Jagatsinghpur -356,jajapur,21,odisha,21.13,382,jajpur,http://www.wikidata.org/entity/Q2087771,jajpur,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,382,Q2087771,Jajapur,Jajpur -357,jharsuguda,21,odisha,21.02,371,jharsuguda,http://www.wikidata.org/entity/Q569181,jharsuguda,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,371,Q569181,Jharsuguda,Jharsuguda -358,kalahandi,21,odisha,21.26,395,kalahandi,http://www.wikidata.org/entity/Q1876588,kalahandi,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,395,Q1876588,Kalahandi,Kalahandi -359,kandhamal,21,odisha,21.21,390,kandhamal,http://www.wikidata.org/entity/Q2085500,kandhamal,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,390,Q2085500,Kandhamal,Kandhamal -360,kendrapara,21,odisha,21.10,379,kendrapara,http://www.wikidata.org/entity/Q2299172,kendrapara,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,379,Q2299172,Kendrapara,Kendrapara -361,kendujhar,21,odisha,21.06,375,kendujhar,http://www.wikidata.org/entity/Q2085428,kendujhar,"district of Odisha, India",http://www.wikidata.org/entity/Q22048,odisha,state of India,375,Q2085428,Kendujhar,Kendujhar -362,khordha,21,odisha,21.17,386,khordha,http://www.wikidata.org/entity/Q662818,khordha,"district of Odisha, 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Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in northern India,125,Q806969,Banswara,Banswara -089,baran,08,rajasthan,08.31,128,baran,http://www.wikidata.org/entity/Q2329717,baran,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in northern India,128,Q2329717,Baran,Baran -090,barmer,08,rajasthan,08.17,115,barmer,http://www.wikidata.org/entity/Q42016,barmer,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in northern India,115,Q42016,Barmer,Barmer -091,bharatpur,08,rajasthan,08.07,105,bharatpur,http://www.wikidata.org/entity/Q854861,bharatpur,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in northern India,105,Q854861,Bharatpur,Bharatpur -092,bhilwara,08,rajasthan,08.24,122,bhilwara,http://www.wikidata.org/entity/Q41991,bhilwara,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in northern India,122,Q41991,Bhilwara,Bhilwara 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northern India,100,Q1356112,Hanumangarh,Hanumangarh -102,jaipur,08,rajasthan,08.12,110,jaipur,http://www.wikidata.org/entity/Q1134781,jaipur,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in northern India,110,Q1134781,Jaipur,Jaipur -103,jaisalmer,08,rajasthan,08.16,114,jaisalmer,http://www.wikidata.org/entity/Q1419708,jaisalmer,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in northern India,114,Q1419708,Jaisalmer,Jaisalmer -104,jalore,08,rajasthan,08.18,116,jalore,http://www.wikidata.org/entity/Q1460832,jalore,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in northern India,116,Q1460832,Jalore,Jalore -105,jhalawar,08,rajasthan,08.32,129,jhalawar,http://www.wikidata.org/entity/Q1471417,jhalawar,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in northern India,129,Q1471417,Jhalawar,Jhalawar 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sikkim,"district of Sikkim, India",http://www.wikidata.org/entity/Q1505,sikkim,Indian state,244,Q1772832,East District,East Sikkim -226,north district,11,sikkim,11.01,241,north sikkim,http://www.wikidata.org/entity/Q1784149,north sikkim,"district of Sikkim, India",http://www.wikidata.org/entity/Q1505,sikkim,Indian state,241,Q1784149,North District,North Sikkim -227,south district,11,sikkim,11.03,243,south sikkim,http://www.wikidata.org/entity/Q1805051,south sikkim,"district of Sikkim, India",http://www.wikidata.org/entity/Q1505,sikkim,Indian state,243,Q1805051,South District,South Sikkim -228,west district,11,sikkim,11.02,242,west sikkim,http://www.wikidata.org/entity/Q611357,west sikkim,"district of Sikkim, India",http://www.wikidata.org/entity/Q1505,sikkim,Indian state,242,Q611357,West District,West Sikkim -610,ariyalur,33,tamil nadu,33.17,616,ariyalur,http://www.wikidata.org/entity/Q15112,ariyalur,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,616,Q15112,Ariyalur,Ariyalur -730,chengalpattu,33,tamil nadu,,,chengalpattu,http://www.wikidata.org/entity/Q65976177,chengalpattu,"district in Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,,Q65976177,Chengalpattu,Chengalpattu -568,chennai,33,tamil nadu,33.02,603,chennai,http://www.wikidata.org/entity/Q15116,chennai,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,603,Q15116,Chennai,Chennai -569,coimbatore,33,tamil nadu,33.12,632,coimbatore,http://www.wikidata.org/entity/Q15136,coimbatore,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,632,Q15136,Coimbatore,Coimbatore -570,cuddalore,33,tamil nadu,33.18,617,cuddalore,http://www.wikidata.org/entity/Q15150,cuddalore,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,617,Q15150,Cuddalore,Cuddalore -571,dharmapuri,33,tamil nadu,33.05,630,dharmapuri,http://www.wikidata.org/entity/Q15152,dharmapuri,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,630,Q15152,Dharmapuri,Dharmapuri -572,dindigul,33,tamil nadu,33.13,612,dindigul,http://www.wikidata.org/entity/Q15154,dindigul,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,612,Q15154,Dindigul,Dindigul -573,erode,33,tamil nadu,33.10,610,erode,http://www.wikidata.org/entity/Q15155,erode,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,610,Q15155,Erode,Erode -729,kallakurichi,33,tamil nadu,,,kallakurichi,http://www.wikidata.org/entity/Q60493360,kallakurichi,"district in Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,,Q60493360,Kallakurichi,Kallakurichi -574,kanchipuram,33,tamil nadu,33.03,604,kanchipuram,http://www.wikidata.org/entity/Q15157,kanchipuram,"district of Tamil Nadu, 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nadu,33.22,621,pudukkottai,http://www.wikidata.org/entity/Q15190,pudukkottai,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,621,Q15190,Pudukkottai,Pudukkottai -583,ramanathapuram,33,tamil nadu,33.27,626,ramanathapuram,http://www.wikidata.org/entity/Q15191,ramanathapuram,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,626,Q15191,Ramanathapuram,Ramanathapuram -731,ranipet,33,tamil nadu,,,ranipet,http://www.wikidata.org/entity/Q66659623,ranipet,district of Tamil Nadu in India,http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,,Q66659623,Ranipet,Ranipet -584,salem,33,tamil nadu,33.08,608,salem,http://www.wikidata.org/entity/Q15192,salem,district of Tamil Nadu state in southern India,http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,608,Q15192,Salem,Salem -585,sivaganga,33,tamil nadu,33.23,622,sivaganga,http://www.wikidata.org/entity/Q15195,sivaganga,"district of Tamil Nadu, 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nadu,33.01,602,tiruvallur,http://www.wikidata.org/entity/Q15204,tiruvallur,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,602,Q15204,Thiruvallur,Tiruvallur -590,thiruvarur,33,tamil nadu,33.20,619,tiruvarur,http://www.wikidata.org/entity/Q15197,tiruvarur,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,619,Q15197,Thiruvarur,Tiruvarur -591,tiruchirappalli,33,tamil nadu,33.15,614,tiruchirappalli,http://www.wikidata.org/entity/Q15201,tiruchirappalli,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,614,Q15201,Tiruchirappalli,Tiruchirappalli -592,tirunelveli,33,tamil nadu,33.29,628,tirunelveli,http://www.wikidata.org/entity/Q15200,tirunelveli,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,628,Q15200,Tirunelveli,Tirunelveli -732,tirupathur,33,tamil nadu,,,tirupattur,http://www.wikidata.org/entity/Q66659621,tirupattur,district of Tamil Nadu in India,http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,,Q66659621,Tirupathur,Tirupattur -634,tiruppur,33,tamil nadu,,633,tiruppur,http://www.wikidata.org/entity/Q15202,tiruppur,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,633,Q15202,Tiruppur,Tiruppur -593,tiruvannamalai,33,tamil nadu,33.06,606,tiruvannamalai,http://www.wikidata.org/entity/Q15207,tiruvannamalai,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,606,Q15207,Tiruvannamalai,Tiruvannamalai -594,tuticorin,33,tamil nadu,33.28,627,thoothukudi,http://www.wikidata.org/entity/Q15198,thoothukudi,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,627,Q15198,Tuticorin,Thoothukudi -595,vellore,33,tamil nadu,33.04,605,vellore,http://www.wikidata.org/entity/Q15206,vellore,"district in Tamil Nadu, 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-687,jayashankar bhupalapally,36,telangana,,,jayashankar bhupalpally,http://www.wikidata.org/entity/Q28169775,jayashankar bhupalpally,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169775,Jayashankar Bhupalapally,Jayashankar Bhupalpally -695,jogulamba gadwal,36,telangana,,,jogulamba gadwal,http://www.wikidata.org/entity/Q27897618,jogulamba gadwal,district of Telangana in India,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q27897618,Jogulamba Gadwal,Jogulamba Gadwal -685,kamareddy,36,telangana,,,kamareddy,http://www.wikidata.org/entity/Q27956125,kamareddy,district of Telangana in India,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q27956125,Kamareddy,Kamareddy -508,karimnagar,36,telangana,28.03,534,karimnagar,http://www.wikidata.org/entity/Q15373,karimnagar,district of Telangana,http://www.wikidata.org/entity/Q677037,telangana,state in India,534,Q15373,Karimnagar,Karimnagar -509,khammam,36,telangana,28.10,541,khammam,http://www.wikidata.org/entity/Q15371,khammam,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,541,Q15371,Khammam,Khammam -699,kumuram bheem asifabad,36,telangana,,,kumaram bheem asifabad,http://www.wikidata.org/entity/Q28170184,kumaram bheem asifabad,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28170184,Kumuram Bheem Asifabad,Kumaram Bheem Asifabad -688,mahabubabad,36,telangana,,,mahabubabad,http://www.wikidata.org/entity/Q28169761,mahabubabad,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169761,Mahabubabad,Mahabubabad -512,mahabubnagar,36,telangana,28.07,538,mahbubnagar,http://www.wikidata.org/entity/Q15380,mahbubnagar,district of Telangana,http://www.wikidata.org/entity/Q677037,telangana,state in India,538,Q15380,Mahabubnagar,Mahbubnagar -684,mancherial,36,telangana,,,mancherial,http://www.wikidata.org/entity/Q28169747,mancherial,district of Telangana,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169747,Mancherial,Mancherial -513,medak,36,telangana,28.04,535,medak,http://www.wikidata.org/entity/Q15386,medak,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,535,Q15386,Medak,Medak -700,medchal malkajgiri,36,telangana,,,medchal–malkajgiri,http://www.wikidata.org/entity/Q27614841,medchal–malkajgiri,district of Telangana in India,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q27614841,Medchal Malkajgiri,Medchal–malkajgiri -720,mulugu,36,telangana,,,mulugu,http://www.wikidata.org/entity/Q61746006,mulugu,"district in Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q61746006,Mulugu,Mulugu -694,nagarkurnool,36,telangana,,,nagarkurnool,http://www.wikidata.org/entity/Q28169773,nagarkurnool,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169773,Nagarkurnool,Nagarkurnool -514,nalgonda,36,telangana,28.08,539,nalgonda,http://www.wikidata.org/entity/Q15384,nalgonda,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,539,Q15384,Nalgonda,Nalgonda -721,narayanpet,36,telangana,,,narayanpet,http://www.wikidata.org/entity/Q61746013,narayanpet,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q61746013,Narayanpet,Narayanpet -680,nirmal,36,telangana,,,nirmal,http://www.wikidata.org/entity/Q28169750,nirmal,district of Telangana,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169750,Nirmal,Nirmal -516,nizamabad,36,telangana,28.02,533,nizamabad,http://www.wikidata.org/entity/Q15391,nizamabad,district of Telangana,http://www.wikidata.org/entity/Q677037,telangana,state in India,533,Q15391,Nizamabad,Nizamabad -682,peddapalli,36,telangana,,,peddapalli,http://www.wikidata.org/entity/Q27614797,peddapalli,district of Telangana,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q27614797,Peddapalli,Peddapalli -683,rajanna sircilla,36,telangana,,,rajanna sircilla,http://www.wikidata.org/entity/Q28172781,rajanna sircilla,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28172781,Rajanna Sircilla,Rajanna Sircilla -518,ranga reddy,36,telangana,28.06,537,ranga reddy,http://www.wikidata.org/entity/Q15388,ranga reddy,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,537,Q15388,Ranga Reddy,Ranga Reddy -691,sangareddy,36,telangana,,,sangareddy,http://www.wikidata.org/entity/Q28169753,sangareddy,district in Telangana,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169753,Sangareddy,Sangareddy -692,siddipet,36,telangana,,,siddipet,http://www.wikidata.org/entity/Q28169756,siddipet,district in Telangana,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169756,Siddipet,Siddipet -696,suryapet,36,telangana,,,suryapet,http://www.wikidata.org/entity/Q28169770,suryapet,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169770,Suryapet,Suryapet -698,vikarabad,36,telangana,,,vikarabad,http://www.wikidata.org/entity/Q28170173,vikarabad,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28170173,Vikarabad,Vikarabad -693,wanaparthy,36,telangana,,,wanaparthy,http://www.wikidata.org/entity/Q28172504,wanaparthy,"District of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28172504,Wanaparthy,Wanaparthy -522,warangal,36,telangana,28.09,540,warangal,http://www.wikidata.org/entity/Q28169759,warangal,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169759,Warangal,Warangal -697,yadadri bhuvanagiri,36,telangana,,,yadadri bhuvanagiri,http://www.wikidata.org/entity/Q28169764,yadadri bhuvanagiri,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169764,Yadadri Bhuvanagiri,Yadadri Bhuvanagiri -465,dadra and nagar haveli,38,dadra and nagar haveli and daman and diu,26.01,496,dadra and nagar haveli,http://www.wikidata.org/entity/Q46107,dadra and nagar haveli,"district of Dadra and Nagar Haveli and Daman and Diu, India",http://www.wikidata.org/entity/Q77997266,dadra and nagar haveli and daman and diu,Union territory in India,496,Q46107,Dadra and Nagar Haveli,Dadra and Nagar Haveli -463,daman,38,dadra and nagar haveli and daman and diu,25.02,495,daman,http://www.wikidata.org/entity/Q1158197,daman,district of Dadra and Nagar Haveli and Daman and Diu,http://www.wikidata.org/entity/Q77997266,dadra and nagar haveli and daman and diu,Union territory in India,495,Q1158197,Daman,Daman -464,diu,38,dadra and nagar haveli and daman and diu,25.01,494,diu,http://www.wikidata.org/entity/Q2552347,diu,"district in Dadra and Nagar Haveli and Daman and Diu, India",http://www.wikidata.org/entity/Q77997266,dadra and nagar haveli and daman and diu,Union territory in India,494,Q2552347,Diu,Diu -269,dhalai,16,tripura,16.03,291,dhalai,http://www.wikidata.org/entity/Q2086546,dhalai,"district in Tripura, India",http://www.wikidata.org/entity/Q1363,tripura,Indian state,291,Q2086546,Dhalai,Dhalai -654,gomati,16,tripura,,,gomati,http://www.wikidata.org/entity/Q16086497,gomati,district of Tripura in India,http://www.wikidata.org/entity/Q1363,tripura,Indian state,,Q16086497,Gomati,Gomati -652,khowai,16,tripura,,,khowai,http://www.wikidata.org/entity/Q16086680,khowai,district of Tripura in India,http://www.wikidata.org/entity/Q1363,tripura,Indian state,,Q16086680,Khowai,Khowai -270,north tripura,16,tripura,16.04,292,north 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pradesh,,,shamli,http://www.wikidata.org/entity/Q2999938,shamli,district of Uttar Pradesh in India,http://www.wikidata.org/entity/Q1498,uttar pradesh,Indian state,,Q2999938,Shamli,Shamli -181,shravasti,09,uttar pradesh,09.51,181,shravasti,http://www.wikidata.org/entity/Q1945458,shravasti,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,Indian state,181,Q1945458,Shravasti,Shravasti -182,siddharth nagar,09,uttar pradesh,09.54,184,siddharthnagar,http://www.wikidata.org/entity/Q1815339,siddharthnagar,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,Indian state,184,Q1815339,Siddharth Nagar,Siddharthnagar -183,sitapur,09,uttar pradesh,09.24,154,sitapur,http://www.wikidata.org/entity/Q1812539,sitapur,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,Indian state,154,Q1812539,Sitapur,Sitapur -184,sonbhadra,09,uttar pradesh,09.70,200,sonbhadra,http://www.wikidata.org/entity/Q607798,sonbhadra,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,Indian state,200,Q607798,Sonbhadra,Sonbhadra -185,sultanpur,09,uttar pradesh,09.49,179,sultanpur,http://www.wikidata.org/entity/Q1356154,sultanpur,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,Indian state,179,Q1356154,Sultanpur,Sultanpur -186,unnao,09,uttar pradesh,09.26,156,unnao,http://www.wikidata.org/entity/Q1937875,unnao,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,Indian state,156,Q1937875,Unnao,Unnao -187,varanasi,09,uttar pradesh,09.67,197,varanasi,http://www.wikidata.org/entity/Q1321140,varanasi,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,Indian state,197,Q1321140,Varanasi,Varanasi -303,24 paraganas north,19,west bengal,19.11,337,north 24 parganas,http://www.wikidata.org/entity/Q338425,north 24 parganas,"district in West Bengal, India",http://www.wikidata.org/entity/Q1356,west bengal,Indian state,337,Q338425,24 Paraganas North,North 24 Parganas -304,24 paraganas south,19,west bengal,19.18,343,south 24 parganas,http://www.wikidata.org/entity/Q2308319,south 24 parganas,"district in West Bengal, India",http://www.wikidata.org/entity/Q1356,west bengal,Indian state,343,Q2308319,24 Paraganas South,South 24 Parganas -664,alipurduar,19,west bengal,,,alipurduar,http://www.wikidata.org/entity/Q4726845,alipurduar,district of West Bengal,http://www.wikidata.org/entity/Q1356,west bengal,Indian state,,Q4726845,Alipurduar,Alipurduar -305,bankura,19,west bengal,19.13,339,bankura,http://www.wikidata.org/entity/Q2088458,bankura,"district of West Bengal, India",http://www.wikidata.org/entity/Q1356,west bengal,Indian state,339,Q2088458,Bankura,Bankura -307,birbhum,19,west bengal,19.08,334,birbhum,http://www.wikidata.org/entity/Q2088440,birbhum,"district of West Bengal, 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bardhaman,http://www.wikidata.org/entity/Q29257278,purba bardhaman,district in West Bengal,http://www.wikidata.org/entity/Q1356,west bengal,Indian state,,Q29257278,Purba Bardhaman,Purba Bardhaman -321,purulia,19,west bengal,19.14,340,purulia,http://www.wikidata.org/entity/Q307474,purulia,"District of West Bengal, India",http://www.wikidata.org/entity/Q1356,west bengal,Indian state,340,Q307474,Purulia,Purulia +LGDDistrictCode,LGDDistrictName,LGDStateCode,LGDStateName,LGDCensus2001Code,LGDCensus2011Code,closestDistrictLabel,district,districtLabel,districtDescription,state,stateLabel,stateDescription,census2011Code,WikiDataId,LGDDistrictNameTitleCase,districtLabelTitleCase,StateDCID,DistrictDCID +001,anantnag,01,jammu and kashmir,01.06,014,anantnag,http://www.wikidata.org/entity/Q2982349,anantnag,"district of Jammu and Kashmir, India",http://www.wikidata.org/entity/Q66278313,jammu and kashmir,union territory administered by 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state,024,Q727232,Kangra,Kangra,wikidataId/Q1177,wikidataId/Q727232 +019,kinnaur,02,himachal pradesh,02.12,034,kinnaur,http://www.wikidata.org/entity/Q1862950,kinnaur,"district of Himachal Pradesh, India",http://www.wikidata.org/entity/Q1177,himachal pradesh,Indian state,034,Q1862950,Kinnaur,Kinnaur,wikidataId/Q1177,wikidataId/Q1862950 +020,kullu,02,himachal pradesh,02.04,026,kullu,http://www.wikidata.org/entity/Q2980880,kullu,"district of Himachal Pradesh, India",http://www.wikidata.org/entity/Q1177,himachal pradesh,Indian state,026,Q2980880,Kullu,Kullu,wikidataId/Q1177,wikidataId/Q2980880 +021,lahul and spiti,02,himachal pradesh,02.03,025,lahaul and spiti,http://www.wikidata.org/entity/Q837595,lahaul and spiti,"district of Himachal Pradesh, India",http://www.wikidata.org/entity/Q1177,himachal pradesh,Indian state,025,Q837595,Lahul and Spiti,Lahaul and Spiti,wikidataId/Q1177,wikidataId/Q837595 +022,mandi,02,himachal 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includes New Delhi,,Q25553535,South East,South East Delhi,wikidataId/Q1353,wikidataId/Q25553535 +671,shahdara,07,delhi,,,shahdara,http://www.wikidata.org/entity/Q83486,shahdara,"district of Delhi, India",http://www.wikidata.org/entity/Q1353,delhi,Indian metropolis and union territory that includes New Delhi,,Q83486,Shahdara,Shahdara,wikidataId/Q1353,wikidataId/Q83486 +086,ajmer,08,rajasthan,08.21,119,ajmer,http://www.wikidata.org/entity/Q413037,ajmer,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,119,Q413037,Ajmer,Ajmer,wikidataId/Q1437,wikidataId/Q413037 +087,alwar,08,rajasthan,08.06,104,alwar,http://www.wikidata.org/entity/Q449690,alwar,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,104,Q449690,Alwar,Alwar,wikidataId/Q1437,wikidataId/Q449690 +088,banswara,08,rajasthan,08.28,125,banswara,http://www.wikidata.org/entity/Q806969,banswara,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,125,Q806969,Banswara,Banswara,wikidataId/Q1437,wikidataId/Q806969 +089,baran,08,rajasthan,08.31,128,baran,http://www.wikidata.org/entity/Q2329717,baran,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,128,Q2329717,Baran,Baran,wikidataId/Q1437,wikidataId/Q2329717 +090,barmer,08,rajasthan,08.17,115,barmer,http://www.wikidata.org/entity/Q42016,barmer,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,115,Q42016,Barmer,Barmer,wikidataId/Q1437,wikidataId/Q42016 +091,bharatpur,08,rajasthan,08.07,105,bharatpur,http://www.wikidata.org/entity/Q854861,bharatpur,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,105,Q854861,Bharatpur,Bharatpur,wikidataId/Q1437,wikidataId/Q854861 +092,bhilwara,08,rajasthan,08.24,122,bhilwara,http://www.wikidata.org/entity/Q41991,bhilwara,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,122,Q41991,Bhilwara,Bhilwara,wikidataId/Q1437,wikidataId/Q41991 +093,bikaner,08,rajasthan,08.03,101,bikaner,http://www.wikidata.org/entity/Q778996,bikaner,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,101,Q778996,Bikaner,Bikaner,wikidataId/Q1437,wikidataId/Q778996 +094,bundi,08,rajasthan,08.23,121,bundi,http://www.wikidata.org/entity/Q670405,bundi,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,121,Q670405,Bundi,Bundi,wikidataId/Q1437,wikidataId/Q670405 +095,chittorgarh,08,rajasthan,08.29,126,chittorgarh,http://www.wikidata.org/entity/Q1075011,chittorgarh,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,126,Q1075011,Chittorgarh,Chittorgarh,wikidataId/Q1437,wikidataId/Q1075011 +096,churu,08,rajasthan,08.04,102,churu,http://www.wikidata.org/entity/Q1090006,churu,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,102,Q1090006,Churu,Churu,wikidataId/Q1437,wikidataId/Q1090006 +097,dausa,08,rajasthan,08.11,109,dausa,http://www.wikidata.org/entity/Q1173042,dausa,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,109,Q1173042,Dausa,Dausa,wikidataId/Q1437,wikidataId/Q1173042 +098,dholpur,08,rajasthan,08.08,106,dholpur,http://www.wikidata.org/entity/Q1207709,dholpur,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,106,Q1207709,Dholpur,Dholpur,wikidataId/Q1437,wikidataId/Q1207709 +099,dungarpur,08,rajasthan,08.27,124,dungarpur,http://www.wikidata.org/entity/Q1265687,dungarpur,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,124,Q1265687,Dungarpur,Dungarpur,wikidataId/Q1437,wikidataId/Q1265687 +100,ganganagar,08,rajasthan,08.01,099,sri ganganagar,http://www.wikidata.org/entity/Q1419696,sri ganganagar,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,099,Q1419696,Ganganagar,Sri Ganganagar,wikidataId/Q1437,wikidataId/Q1419696 +101,hanumangarh,08,rajasthan,08.02,100,hanumangarh,http://www.wikidata.org/entity/Q1356112,hanumangarh,"district in Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,100,Q1356112,Hanumangarh,Hanumangarh,wikidataId/Q1437,wikidataId/Q1356112 +102,jaipur,08,rajasthan,08.12,110,jaipur,http://www.wikidata.org/entity/Q1134781,jaipur,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,110,Q1134781,Jaipur,Jaipur,wikidataId/Q1437,wikidataId/Q1134781 +103,jaisalmer,08,rajasthan,08.16,114,jaisalmer,http://www.wikidata.org/entity/Q1419708,jaisalmer,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,114,Q1419708,Jaisalmer,Jaisalmer,wikidataId/Q1437,wikidataId/Q1419708 +104,jalore,08,rajasthan,08.18,116,jalore,http://www.wikidata.org/entity/Q1460832,jalore,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,116,Q1460832,Jalore,Jalore,wikidataId/Q1437,wikidataId/Q1460832 +105,jhalawar,08,rajasthan,08.32,129,jhalawar,http://www.wikidata.org/entity/Q1471417,jhalawar,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,129,Q1471417,Jhalawar,Jhalawar,wikidataId/Q1437,wikidataId/Q1471417 +106,jhunjhunu,08,rajasthan,08.05,103,jhunjhunu,http://www.wikidata.org/entity/Q1471427,jhunjhunu,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,103,Q1471427,Jhunjhunu,Jhunjhunu,wikidataId/Q1437,wikidataId/Q1471427 +107,jodhpur,08,rajasthan,08.15,113,jodhpur,http://www.wikidata.org/entity/Q1434965,jodhpur,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,113,Q1434965,Jodhpur,Jodhpur,wikidataId/Q1437,wikidataId/Q1434965 +108,karauli,08,rajasthan,08.09,107,karauli,http://www.wikidata.org/entity/Q1419668,karauli,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,107,Q1419668,Karauli,Karauli,wikidataId/Q1437,wikidataId/Q1419668 +109,kota,08,rajasthan,08.30,127,kota,http://www.wikidata.org/entity/Q999432,kota,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,127,Q999432,Kota,Kota,wikidataId/Q1437,wikidataId/Q999432 +110,nagaur,08,rajasthan,08.14,112,nagaur,http://www.wikidata.org/entity/Q1507174,nagaur,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,112,Q1507174,Nagaur,Nagaur,wikidataId/Q1437,wikidataId/Q1507174 +111,pali,08,rajasthan,08.20,118,pali,http://www.wikidata.org/entity/Q46925,pali,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,118,Q46925,Pali,Pali,wikidataId/Q1437,wikidataId/Q46925 +112,rajsamand,08,rajasthan,08.25,123,rajsamand,http://www.wikidata.org/entity/Q596693,rajsamand,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,123,Q596693,Rajsamand,Rajsamand,wikidataId/Q1437,wikidataId/Q596693 +113,sawai madhopur,08,rajasthan,08.10,108,sawai madhopur,http://www.wikidata.org/entity/Q1507166,sawai madhopur,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,108,Q1507166,Sawai Madhopur,Sawai Madhopur,wikidataId/Q1437,wikidataId/Q1507166 +114,sikar,08,rajasthan,08.13,111,sikar,http://www.wikidata.org/entity/Q12945777,sikar,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,111,Q12945777,Sikar,Sikar,wikidataId/Q1437,wikidataId/Q12945777 +115,sirohi,08,rajasthan,08.19,117,sirohi,http://www.wikidata.org/entity/Q205719,sirohi,district in Rajasthan,http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,117,Q205719,Sirohi,Sirohi,wikidataId/Q1437,wikidataId/Q205719 +116,tonk,08,rajasthan,08.22,120,tonk,http://www.wikidata.org/entity/Q915880,tonk,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,120,Q915880,Tonk,Tonk,wikidataId/Q1437,wikidataId/Q915880 +117,udaipur,08,rajasthan,08.26,130,udaipur,http://www.wikidata.org/entity/Q1321577,udaipur,"district of Rajasthan, India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,130,Q1321577,Udaipur,Udaipur,wikidataId/Q1437,wikidataId/Q1321577 +629,pratapgarh,08,rajasthan,,131,pratapgarh,http://www.wikidata.org/entity/Q1585433,pratapgarh,"district of state Rajasthan,India",http://www.wikidata.org/entity/Q1437,rajasthan,state in north-western India,131,Q1585433,Pratapgarh,Pratapgarh,wikidataId/Q1437,wikidataId/Q1585433 +118,agra,09,uttar pradesh,09.15,146,agra,http://www.wikidata.org/entity/Q606343,agra,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,146,Q606343,Agra,Agra,wikidataId/Q1498,wikidataId/Q606343 +119,aligarh,09,uttar pradesh,09.12,143,aligarh,http://www.wikidata.org/entity/Q766918,aligarh,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,143,Q766918,Aligarh,Aligarh,wikidataId/Q1498,wikidataId/Q766918 +120,prayagraj,09,uttar pradesh,09.45,175,allahabad,http://www.wikidata.org/entity/Q1773426,allahabad,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,175,Q1773426,Prayagraj,Allahabad,wikidataId/Q1498,wikidataId/Q1773426 +121,ambedkar nagar,09,uttar pradesh,09.48,178,ambedkar nagar,http://www.wikidata.org/entity/Q456764,ambedkar nagar,"district in Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,178,Q456764,Ambedkar Nagar,Ambedkar Nagar,wikidataId/Q1498,wikidataId/Q456764 +122,auraiya,09,uttar pradesh,09.32,162,auraiya,http://www.wikidata.org/entity/Q1812533,auraiya,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,162,Q1812533,Auraiya,Auraiya,wikidataId/Q1498,wikidataId/Q1812533 +123,azamgarh,09,uttar pradesh,09.61,191,azamgarh,http://www.wikidata.org/entity/Q793553,azamgarh,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,191,Q793553,Azamgarh,Azamgarh,wikidataId/Q1498,wikidataId/Q793553 +124,baghpat,09,uttar pradesh,09.08,139,bagpat,http://www.wikidata.org/entity/Q1797363,bagpat,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,139,Q1797363,Baghpat,Bagpat,wikidataId/Q1498,wikidataId/Q1797363 +125,bahraich,09,uttar pradesh,09.50,180,bahraich,http://www.wikidata.org/entity/Q1812548,bahraich,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,180,Q1812548,Bahraich,Bahraich,wikidataId/Q1498,wikidataId/Q1812548 +126,ballia,09,uttar pradesh,09.63,193,ballia,http://www.wikidata.org/entity/Q584644,ballia,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,193,Q584644,Ballia,Ballia,wikidataId/Q1498,wikidataId/Q584644 +127,balrampur,09,uttar pradesh,09.52,182,balrampur,http://www.wikidata.org/entity/Q1948380,balrampur,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,182,Q1948380,Balrampur,Balrampur,wikidataId/Q1498,wikidataId/Q1948380 +128,banda,09,uttar pradesh,09.40,170,banda,http://www.wikidata.org/entity/Q2131759,banda,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,170,Q2131759,Banda,Banda,wikidataId/Q1498,wikidataId/Q2131759 +129,barabanki,09,uttar pradesh,09.46,176,barabanki,http://www.wikidata.org/entity/Q633114,barabanki,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,176,Q633114,Barabanki,Barabanki,wikidataId/Q1498,wikidataId/Q633114 +130,bareilly,09,uttar pradesh,09.20,150,bareilly,http://www.wikidata.org/entity/Q1797378,bareilly,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,150,Q1797378,Bareilly,Bareilly,wikidataId/Q1498,wikidataId/Q1797378 +131,basti,09,uttar pradesh,09.55,185,basti,http://www.wikidata.org/entity/Q715267,basti,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,185,Q715267,Basti,Basti,wikidataId/Q1498,wikidataId/Q715267 +132,bijnor,09,uttar pradesh,09.03,134,bijnor,http://www.wikidata.org/entity/Q1937865,bijnor,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,134,Q1937865,Bijnor,Bijnor,wikidataId/Q1498,wikidataId/Q1937865 +133,budaun,09,uttar pradesh,09.19,149,budaun,http://www.wikidata.org/entity/Q1815262,budaun,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,149,Q1815262,Budaun,Budaun,wikidataId/Q1498,wikidataId/Q1815262 +134,bulandshahr,09,uttar pradesh,09.11,142,bulandshahr,http://www.wikidata.org/entity/Q1752328,bulandshahr,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,142,Q1752328,Bulandshahr,Bulandshahr,wikidataId/Q1498,wikidataId/Q1752328 +135,chandauli,09,uttar pradesh,09.66,196,chandauli,http://www.wikidata.org/entity/Q2733369,chandauli,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,196,Q2733369,Chandauli,Chandauli,wikidataId/Q1498,wikidataId/Q2733369 +136,chitrakoot,09,uttar pradesh,09.41,171,chitrakoot,http://www.wikidata.org/entity/Q2089141,chitrakoot,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,171,Q2089141,Chitrakoot,Chitrakoot,wikidataId/Q1498,wikidataId/Q2089141 +137,deoria,09,uttar pradesh,09.60,190,deoria,http://www.wikidata.org/entity/Q731746,deoria,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,190,Q731746,Deoria,Deoria,wikidataId/Q1498,wikidataId/Q731746 +138,etah,09,uttar pradesh,09.17,201,etah,http://www.wikidata.org/entity/Q1773429,etah,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,201,Q1773429,Etah,Etah,wikidataId/Q1498,wikidataId/Q1773429 +139,etawah,09,uttar pradesh,09.31,161,etawah,http://www.wikidata.org/entity/Q1815288,etawah,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,161,Q1815288,Etawah,Etawah,wikidataId/Q1498,wikidataId/Q1815288 +140,ayodhya,09,uttar pradesh,09.47,177,ayodhya,http://www.wikidata.org/entity/Q1814132,ayodhya,"District of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern India,177,Q1814132,Ayodhya,Ayodhya,wikidataId/Q1498,wikidataId/Q1814132 +141,farrukhabad,09,uttar pradesh,09.29,159,farrukhabad,http://www.wikidata.org/entity/Q1897251,farrukhabad,"district of Uttar Pradesh, India",http://www.wikidata.org/entity/Q1498,uttar pradesh,state in northern 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eastern India,213,Q77746,Madhepura,Madhepura,wikidataId/Q1165,wikidataId/Q77746 +206,madhubani,10,bihar,10.05,207,madhubani,http://www.wikidata.org/entity/Q77474,madhubani,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,207,Q77474,Madhubani,Madhubani,wikidataId/Q1165,wikidataId/Q77474 +207,munger,10,bihar,10.24,226,munger,http://www.wikidata.org/entity/Q77452,munger,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,226,Q77452,Munger,Munger,wikidataId/Q1165,wikidataId/Q77452 +208,muzaffarpur,10,bihar,10.14,216,muzaffarpur,http://www.wikidata.org/entity/Q77731,muzaffarpur,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,216,Q77731,Muzaffarpur,Muzaffarpur,wikidataId/Q1165,wikidataId/Q77731 +209,nalanda,10,bihar,10.27,229,nalanda,http://www.wikidata.org/entity/Q77633,nalanda,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,229,Q77633,Nalanda,Nalanda,wikidataId/Q1165,wikidataId/Q77633 +210,nawada,10,bihar,10.36,237,nawada,http://www.wikidata.org/entity/Q100067,nawada,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,237,Q100067,Nawada,Nawada,wikidataId/Q1165,wikidataId/Q100067 +211,pashchim champaran,10,bihar,10.01,203,west champaran,http://www.wikidata.org/entity/Q100124,west champaran,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,203,Q100124,Pashchim Champaran,West Champaran,wikidataId/Q1165,wikidataId/Q100124 +212,patna,10,bihar,10.28,230,patna,http://www.wikidata.org/entity/Q100077,patna,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,230,Q100077,Patna,Patna,wikidataId/Q1165,wikidataId/Q100077 +213,purbi champaran,10,bihar,10.02,204,east champaran,http://www.wikidata.org/entity/Q49159,east champaran,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,204,Q49159,Purbi Champaran,East Champaran,wikidataId/Q1165,wikidataId/Q49159 +214,purnia,10,bihar,10.09,211,purnia,http://www.wikidata.org/entity/Q100082,purnia,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,211,Q100082,Purnia,Purnia,wikidataId/Q1165,wikidataId/Q100082 +215,rohtas,10,bihar,10.32,234,rohtas,http://www.wikidata.org/entity/Q100085,rohtas,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,234,Q100085,Rohtas,Rohtas,wikidataId/Q1165,wikidataId/Q100085 +216,saharsa,10,bihar,10.12,214,saharsa,http://www.wikidata.org/entity/Q100120,saharsa,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,214,Q100120,Saharsa,Saharsa,wikidataId/Q1165,wikidataId/Q100120 +217,samastipur,10,bihar,10.19,221,samastipur,http://www.wikidata.org/entity/Q100117,samastipur,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,221,Q100117,Samastipur,Samastipur,wikidataId/Q1165,wikidataId/Q100117 +218,saran,10,bihar,10.17,219,saran,http://www.wikidata.org/entity/Q100146,saran,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,219,Q100146,Saran,Saran,wikidataId/Q1165,wikidataId/Q100146 +219,sheikhpura,10,bihar,10.26,228,sheikhpura,http://www.wikidata.org/entity/Q100093,sheikhpura,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,228,Q100093,Sheikhpura,Sheikhpura,wikidataId/Q1165,wikidataId/Q100093 +220,sheohar,10,bihar,10.03,205,sheohar,http://www.wikidata.org/entity/Q100095,sheohar,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,205,Q100095,Sheohar,Sheohar,wikidataId/Q1165,wikidataId/Q100095 +221,sitamarhi,10,bihar,10.04,206,sitamarhi,http://www.wikidata.org/entity/Q100144,sitamarhi,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,206,Q100144,Sitamarhi,Sitamarhi,wikidataId/Q1165,wikidataId/Q100144 +222,siwan,10,bihar,10.16,218,siwan,http://www.wikidata.org/entity/Q100131,siwan,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,218,Q100131,Siwan,Siwan,wikidataId/Q1165,wikidataId/Q100131 +223,supaul,10,bihar,10.06,208,supaul,http://www.wikidata.org/entity/Q100139,supaul,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,208,Q100139,Supaul,Supaul,wikidataId/Q1165,wikidataId/Q100139 +224,vaishali,10,bihar,10.18,220,vaishali,http://www.wikidata.org/entity/Q100130,vaishali,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,220,Q100130,Vaishali,Vaishali,wikidataId/Q1165,wikidataId/Q100130 +611,arwal,10,bihar,10.33,240,arwal,http://www.wikidata.org/entity/Q42917,arwal,"district of Bihar, India",http://www.wikidata.org/entity/Q1165,bihar,state in eastern India,240,Q42917,Arwal,Arwal,wikidataId/Q1165,wikidataId/Q42917 +225,gangtok,11,sikkim,11.04,244,east sikkim,http://www.wikidata.org/entity/Q1772832,east sikkim,"district of Sikkim, India",http://www.wikidata.org/entity/Q1505,sikkim,Indian state,244,Q1772832,Gangtok,East Sikkim,wikidataId/Q1505,wikidataId/Q1772832 +226,mangan,11,sikkim,11.01,241,north sikkim,http://www.wikidata.org/entity/Q1784149,north sikkim,"district of Sikkim, India",http://www.wikidata.org/entity/Q1505,sikkim,Indian state,241,Q1784149,Mangan,North Sikkim,wikidataId/Q1505,wikidataId/Q1784149 +227,namchi,11,sikkim,11.03,243,south sikkim,http://www.wikidata.org/entity/Q1805051,south sikkim,"district of Sikkim, India",http://www.wikidata.org/entity/Q1505,sikkim,Indian state,243,Q1805051,Namchi,South Sikkim,wikidataId/Q1505,wikidataId/Q1805051 +228,gyalshing,11,sikkim,11.02,242,west sikkim,http://www.wikidata.org/entity/Q611357,west sikkim,"district of Sikkim, India",http://www.wikidata.org/entity/Q1505,sikkim,Indian state,242,Q611357,Gyalshing,West Sikkim,wikidataId/Q1505,wikidataId/Q611357 +741,pakyong,11,sikkim,,,pakyong,http://www.wikidata.org/entity/Q108803704,pakyong,"district in Sikkim, India",http://www.wikidata.org/entity/Q1505,sikkim,Indian state,,Q108803704,Pakyong,Pakyong,wikidataId/Q1505,wikidataId/Q108803704 +742,soreng,11,sikkim,,,soreng,http://www.wikidata.org/entity/Q111203982,soreng,"district in Sikkim, India",http://www.wikidata.org/entity/Q1505,sikkim,Indian state,,Q111203982,Soreng,Soreng,wikidataId/Q1505,wikidataId/Q111203982 +229,changlang,12,arunachal pradesh,12.12,253,changlang,http://www.wikidata.org/entity/Q15427,changlang,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,253,Q15427,Changlang,Changlang,wikidataId/Q1162,wikidataId/Q15427 +230,dibang valley,12,arunachal pradesh,12.10,257,dibang valley,http://www.wikidata.org/entity/Q15446,dibang valley,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,257,Q15446,Dibang Valley,Dibang Valley,wikidataId/Q1162,wikidataId/Q15446 +231,east kameng,12,arunachal pradesh,12.03,247,east kameng,http://www.wikidata.org/entity/Q15424,east kameng,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,247,Q15424,East Kameng,East Kameng,wikidataId/Q1162,wikidataId/Q15424 +232,east siang,12,arunachal pradesh,12.08,251,east siang,http://www.wikidata.org/entity/Q15419,east siang,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,251,Q15419,East Siang,East Siang,wikidataId/Q1162,wikidataId/Q15419 +233,kurung kumey,12,arunachal pradesh,12.14,256,kurung kumey,http://www.wikidata.org/entity/Q2449506,kurung kumey,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,256,Q2449506,Kurung Kumey,Kurung Kumey,wikidataId/Q1162,wikidataId/Q2449506 +234,lohit,12,arunachal pradesh,12.11,259,lohit,http://www.wikidata.org/entity/Q15438,lohit,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,259,Q15438,Lohit,Lohit,wikidataId/Q1162,wikidataId/Q15438 +235,lower dibang valley,12,arunachal pradesh,12.15,258,lower dibang valley,http://www.wikidata.org/entity/Q2373368,lower dibang valley,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,258,Q2373368,Lower Dibang Valley,Lower Dibang Valley,wikidataId/Q1162,wikidataId/Q2373368 +236,lower subansiri,12,arunachal pradesh,12.05,255,lower subansiri,http://www.wikidata.org/entity/Q15436,lower subansiri,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,255,Q15436,Lower Subansiri,Lower Subansiri,wikidataId/Q1162,wikidataId/Q15436 +237,papum pare,12,arunachal pradesh,12.04,248,papum pare,http://www.wikidata.org/entity/Q15432,papum pare,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,248,Q15432,Papum Pare,Papum Pare,wikidataId/Q1162,wikidataId/Q15432 +238,tawang,12,arunachal pradesh,12.01,245,tawang,http://www.wikidata.org/entity/Q15449,tawang,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,245,Q15449,Tawang,Tawang,wikidataId/Q1162,wikidataId/Q15449 +239,tirap,12,arunachal pradesh,12.13,254,tirap,http://www.wikidata.org/entity/Q15448,tirap,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,254,Q15448,Tirap,Tirap,wikidataId/Q1162,wikidataId/Q15448 +240,upper siang,12,arunachal pradesh,12.09,252,upper siang,http://www.wikidata.org/entity/Q15465,upper siang,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,252,Q15465,Upper Siang,Upper Siang,wikidataId/Q1162,wikidataId/Q15465 +241,upper subansiri,12,arunachal pradesh,12.06,249,upper subansiri,http://www.wikidata.org/entity/Q15464,upper subansiri,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,249,Q15464,Upper Subansiri,Upper Subansiri,wikidataId/Q1162,wikidataId/Q15464 +242,west kameng,12,arunachal pradesh,12.02,246,west kameng,http://www.wikidata.org/entity/Q15459,west kameng,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,246,Q15459,West Kameng,West Kameng,wikidataId/Q1162,wikidataId/Q15459 +243,west siang,12,arunachal pradesh,12.07,250,west siang,http://www.wikidata.org/entity/Q15453,west siang,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,250,Q15453,West Siang,West Siang,wikidataId/Q1162,wikidataId/Q15453 +628,anjaw,12,arunachal pradesh,,260,anjaw,http://www.wikidata.org/entity/Q15413,anjaw,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,260,Q15413,Anjaw,Anjaw,wikidataId/Q1162,wikidataId/Q15413 +666,longding,12,arunachal pradesh,,,longding,http://www.wikidata.org/entity/Q5627568,longding,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q5627568,Longding,Longding,wikidataId/Q1162,wikidataId/Q5627568 +677,kra daadi,12,arunachal pradesh,,,kra daadi,http://www.wikidata.org/entity/Q21018627,kra daadi,district of Arunachal Pradesh in India,http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q21018627,Kra Daadi,Kra Daadi,wikidataId/Q1162,wikidataId/Q21018627 +678,namsai,12,arunachal pradesh,,,namsai,http://www.wikidata.org/entity/Q21559824,namsai,district of Arunachal Pradesh in India,http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q21559824,Namsai,Namsai,wikidataId/Q1162,wikidataId/Q21559824 +679,siang,12,arunachal pradesh,,,siang,http://www.wikidata.org/entity/Q18642331,siang,district of Arunachal Pradesh in India,http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q18642331,Siang,Siang,wikidataId/Q1162,wikidataId/Q18642331 +718,kamle,12,arunachal pradesh,,,kamle,http://www.wikidata.org/entity/Q48731073,kamle,"district of Arunachal Pradesh, India",http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q48731073,Kamle,Kamle,wikidataId/Q1162,wikidataId/Q48731073 +719,lower siang,12,arunachal pradesh,,,lower siang,http://www.wikidata.org/entity/Q13602925,lower siang,district of Arunachal Pradesh,http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q13602925,Lower Siang,Lower Siang,wikidataId/Q1162,wikidataId/Q13602925 +723,pakke kessang,12,arunachal pradesh,,,pakke-kessang,http://www.wikidata.org/entity/Q61439260,pakke-kessang,district of Arunachal Pradesh in India,http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q61439260,Pakke Kessang,Pakke-kessang,wikidataId/Q1162,wikidataId/Q61439260 +724,leparada,12,arunachal pradesh,,,lepa rada,http://www.wikidata.org/entity/Q63563632,lepa rada,district of Arunachal Pradesh in India,http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q63563632,Leparada,Lepa Rada,wikidataId/Q1162,wikidataId/Q63563632 +725,shi yomi,12,arunachal pradesh,,,shi yomi,http://www.wikidata.org/entity/Q63563625,shi yomi,district of Arunachal Pradesh in India,http://www.wikidata.org/entity/Q1162,arunachal pradesh,State in North East India,,Q63563625,Shi Yomi,Shi Yomi,wikidataId/Q1162,wikidataId/Q63563625 +244,dimapur,13,nagaland,13.06,265,dimapur,http://www.wikidata.org/entity/Q634262,dimapur,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,state in northeastern India,265,Q634262,Dimapur,Dimapur,wikidataId/Q1599,wikidataId/Q634262 +245,kohima,13,nagaland,13.07,270,kohima,http://www.wikidata.org/entity/Q953530,kohima,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,state in northeastern India,270,Q953530,Kohima,Kohima,wikidataId/Q1599,wikidataId/Q953530 +246,mokokchung,13,nagaland,13.03,262,mokokchung,http://www.wikidata.org/entity/Q2175311,mokokchung,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,state in northeastern India,262,Q2175311,Mokokchung,Mokokchung,wikidataId/Q1599,wikidataId/Q2175311 +247,mon,13,nagaland,13.01,261,mon,http://www.wikidata.org/entity/Q2339648,mon,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,state in northeastern India,261,Q2339648,Mon,Mon,wikidataId/Q1599,wikidataId/Q2339648 +248,phek,13,nagaland,13.08,266,phek,http://www.wikidata.org/entity/Q590882,phek,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,state in northeastern India,266,Q590882,Phek,Phek,wikidataId/Q1599,wikidataId/Q590882 +249,tuensang,13,nagaland,13.02,267,tuensang,http://www.wikidata.org/entity/Q2571393,tuensang,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,state in northeastern India,267,Q2571393,Tuensang,Tuensang,wikidataId/Q1599,wikidataId/Q2571393 +250,wokha,13,nagaland,13.05,264,wokha,http://www.wikidata.org/entity/Q681821,wokha,district of Nagaland,http://www.wikidata.org/entity/Q1599,nagaland,state in northeastern India,264,Q681821,Wokha,Wokha,wikidataId/Q1599,wikidataId/Q681821 +251,zunheboto,13,nagaland,13.04,263,zunheboto,http://www.wikidata.org/entity/Q2091461,zunheboto,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,state in northeastern India,263,Q2091461,Zunheboto,Zunheboto,wikidataId/Q1599,wikidataId/Q2091461 +613,peren,13,nagaland,13.07,271,peren,http://www.wikidata.org/entity/Q516294,peren,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,state in northeastern India,271,Q516294,Peren,Peren,wikidataId/Q1599,wikidataId/Q516294 +614,kiphire,13,nagaland,13.02,269,kiphire,http://www.wikidata.org/entity/Q2597908,kiphire,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,state in northeastern India,269,Q2597908,Kiphire,Kiphire,wikidataId/Q1599,wikidataId/Q2597908 +615,longleng,13,nagaland,13.02,268,longleng,http://www.wikidata.org/entity/Q1426783,longleng,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,state in northeastern India,268,Q1426783,Longleng,Longleng,wikidataId/Q1599,wikidataId/Q1426783 +736,noklak,13,nagaland,,,noklak,http://www.wikidata.org/entity/Q48731903,noklak,"district in India, Nagaland",http://www.wikidata.org/entity/Q1599,nagaland,state in northeastern India,,Q48731903,Noklak,Noklak,wikidataId/Q1599,wikidataId/Q48731903 +757,tseminyu,13,nagaland,,,tseminyu,http://www.wikidata.org/entity/Q110223836,tseminyu,"district of Nagaland, India",http://www.wikidata.org/entity/Q1599,nagaland,Indian state,,Q110223836,Tseminyu,Tseminyu,wikidataId/Q1599,wikidataId/Q110223836 +252,bishnupur,14,manipur,14.04,275,bishnupur,http://www.wikidata.org/entity/Q938190,bishnupur,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,275,Q938190,Bishnupur,Bishnupur,wikidataId/Q1193,wikidataId/Q938190 +253,chandel,14,manipur,14.09,280,chandel,http://www.wikidata.org/entity/Q2301769,chandel,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,280,Q2301769,Chandel,Chandel,wikidataId/Q1193,wikidataId/Q2301769 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state,272,Q2301706,Senapati,Senapati,wikidataId/Q1193,wikidataId/Q2301706 +258,tamenglong,14,manipur,14.02,273,tamenglong,http://www.wikidata.org/entity/Q2301717,tamenglong,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,273,Q2301717,Tamenglong,Tamenglong,wikidataId/Q1193,wikidataId/Q2301717 +259,thoubal,14,manipur,14.05,276,thoubal,http://www.wikidata.org/entity/Q2086198,thoubal,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,276,Q2086198,Thoubal,Thoubal,wikidataId/Q1193,wikidataId/Q2086198 +260,ukhrul,14,manipur,14.08,279,ukhrul,http://www.wikidata.org/entity/Q735101,ukhrul,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,279,Q735101,Ukhrul,Ukhrul,wikidataId/Q1193,wikidataId/Q735101 +711,kakching,14,manipur,,,kakching,http://www.wikidata.org/entity/Q28173825,kakching,"district in Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,,Q28173825,Kakching,Kakching,wikidataId/Q1193,wikidataId/Q28173825 +712,kangpokpi,14,manipur,,,kangpokpi,http://www.wikidata.org/entity/Q28419386,kangpokpi,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,,Q28419386,Kangpokpi,Kangpokpi,wikidataId/Q1193,wikidataId/Q28419386 +713,jiribam,14,manipur,,,jiribam,http://www.wikidata.org/entity/Q28419387,jiribam,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,,Q28419387,Jiribam,Jiribam,wikidataId/Q1193,wikidataId/Q28419387 +714,noney,14,manipur,,,noney,http://www.wikidata.org/entity/Q28419389,noney,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,,Q28419389,Noney,Noney,wikidataId/Q1193,wikidataId/Q28419389 +715,pherzawl,14,manipur,,,pherzawl,http://www.wikidata.org/entity/Q28173809,pherzawl,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,,Q28173809,Pherzawl,Pherzawl,wikidataId/Q1193,wikidataId/Q28173809 +716,tengnoupal,14,manipur,,,tengnoupal,http://www.wikidata.org/entity/Q28419388,tengnoupal,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,,Q28419388,Tengnoupal,Tengnoupal,wikidataId/Q1193,wikidataId/Q28419388 +717,kamjong,14,manipur,,,kamjong,http://www.wikidata.org/entity/Q28419390,kamjong,"district of Manipur, India",http://www.wikidata.org/entity/Q1193,manipur,Indian state,,Q28419390,Kamjong,Kamjong,wikidataId/Q1193,wikidataId/Q28419390 +261,aizawl,15,mizoram,15.03,283,aizawl,http://www.wikidata.org/entity/Q1947322,aizawl,"district of Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,283,Q1947322,Aizawl,Aizawl,wikidataId/Q1502,wikidataId/Q1947322 +262,champhai,15,mizoram,15.04,284,champhai,http://www.wikidata.org/entity/Q1965256,champhai,"district of Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,284,Q1965256,Champhai,Champhai,wikidataId/Q1502,wikidataId/Q1965256 +263,kolasib,15,mizoram,15.02,282,kolasib,http://www.wikidata.org/entity/Q1947343,kolasib,"district of Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,282,Q1947343,Kolasib,Kolasib,wikidataId/Q1502,wikidataId/Q1947343 +264,lawngtlai,15,mizoram,15.07,287,lawngtlai,http://www.wikidata.org/entity/Q2086209,lawngtlai,district of Mizoram,http://www.wikidata.org/entity/Q1502,mizoram,State in India,287,Q2086209,Lawngtlai,Lawngtlai,wikidataId/Q1502,wikidataId/Q2086209 +265,lunglei,15,mizoram,15.06,286,lunglei,http://www.wikidata.org/entity/Q1947352,lunglei,"district of Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,286,Q1947352,Lunglei,Lunglei,wikidataId/Q1502,wikidataId/Q1947352 +266,mamit,15,mizoram,15.01,281,mamit,http://www.wikidata.org/entity/Q751531,mamit,"district of Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,281,Q751531,Mamit,Mamit,wikidataId/Q1502,wikidataId/Q751531 +267,saiha,15,mizoram,15.08,288,saiha,http://www.wikidata.org/entity/Q1821714,saiha,"district of Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,288,Q1821714,Saiha,Saiha,wikidataId/Q1502,wikidataId/Q1821714 +268,serchhip,15,mizoram,15.05,285,serchhip,http://www.wikidata.org/entity/Q2086190,serchhip,"district of Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,285,Q2086190,Serchhip,Serchhip,wikidataId/Q1502,wikidataId/Q2086190 +726,hnahthial,15,mizoram,,,hnahthial,http://www.wikidata.org/entity/Q86882590,hnahthial,district in Mizoram,http://www.wikidata.org/entity/Q1502,mizoram,State in India,,Q86882590,Hnahthial,Hnahthial,wikidataId/Q1502,wikidataId/Q86882590 +727,saitual,15,mizoram,,,saitual,http://www.wikidata.org/entity/Q86882593,saitual,"district in Mizoram, India",http://www.wikidata.org/entity/Q1502,mizoram,State in India,,Q86882593,Saitual,Saitual,wikidataId/Q1502,wikidataId/Q86882593 +728,khawzawl,15,mizoram,,,khawzawl,http://www.wikidata.org/entity/Q86882591,khawzawl,district in Mizoram,http://www.wikidata.org/entity/Q1502,mizoram,State in India,,Q86882591,Khawzawl,Khawzawl,wikidataId/Q1502,wikidataId/Q86882591 +269,dhalai,16,tripura,16.03,291,dhalai,http://www.wikidata.org/entity/Q2086546,dhalai,"district in Tripura, India",http://www.wikidata.org/entity/Q1363,tripura,Indian state,291,Q2086546,Dhalai,Dhalai,wikidataId/Q1363,wikidataId/Q2086546 +270,north tripura,16,tripura,16.04,292,north tripura,http://www.wikidata.org/entity/Q1920978,north tripura,"District in Tripura, India",http://www.wikidata.org/entity/Q1363,tripura,Indian state,292,Q1920978,North Tripura,North Tripura,wikidataId/Q1363,wikidataId/Q1920978 +271,south tripura,16,tripura,16.02,290,south tripura,http://www.wikidata.org/entity/Q1822159,south tripura,"District in India, 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Khasi Hills,wikidataId/Q1195,wikidataId/Q1945304 +275,west jaintia hills,17,meghalaya,17.07,299,west jaintia hills,http://www.wikidata.org/entity/Q13181190,west jaintia hills,district of Meghalaya,http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,,Q13181190,West Jaintia Hills,West Jaintia Hills,wikidataId/Q1195,wikidataId/Q13181190 +276,ri bhoi,17,meghalaya,17.05,297,ri-bhoi,http://www.wikidata.org/entity/Q1884672,ri-bhoi,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,297,Q1884672,Ri Bhoi,Ri-bhoi,wikidataId/Q1195,wikidataId/Q1884672 +277,south garo hills,17,meghalaya,17.03,295,south garo hills,http://www.wikidata.org/entity/Q2329228,south garo hills,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,295,Q2329228,South Garo Hills,South Garo Hills,wikidataId/Q1195,wikidataId/Q2329228 +278,west garo hills,17,meghalaya,17.01,293,west garo hills,http://www.wikidata.org/entity/Q2329181,west garo hills,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,293,Q2329181,West Garo Hills,West Garo Hills,wikidataId/Q1195,wikidataId/Q2329181 +279,west khasi hills,17,meghalaya,17.04,296,west khasi hills,http://www.wikidata.org/entity/Q2064752,west khasi hills,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,296,Q2064752,West Khasi Hills,West Khasi Hills,wikidataId/Q1195,wikidataId/Q2064752 +656,north garo hills,17,meghalaya,,,north garo hills,http://www.wikidata.org/entity/Q7055466,north garo hills,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,,Q7055466,North Garo Hills,North Garo Hills,wikidataId/Q1195,wikidataId/Q7055466 +657,east jaintia hills,17,meghalaya,,,east jaintia hills,http://www.wikidata.org/entity/Q15923776,east jaintia hills,district of Meghalaya in India,http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,,Q15923776,East Jaintia Hills,East Jaintia Hills,wikidataId/Q1195,wikidataId/Q15923776 +658,south west khasi hills,17,meghalaya,,,south west khasi hills,http://www.wikidata.org/entity/Q15923741,south west khasi hills,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,,Q15923741,South West Khasi Hills,South West Khasi Hills,wikidataId/Q1195,wikidataId/Q15923741 +663,south west garo hills,17,meghalaya,,,south west garo hills,http://www.wikidata.org/entity/Q15961576,south west garo hills,"district of Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,,Q15961576,South West Garo Hills,South West Garo Hills,wikidataId/Q1195,wikidataId/Q15961576 +740,eastern west khasi hills,17,meghalaya,,,eastern west khasi hills,http://www.wikidata.org/entity/Q110442602,eastern west khasi hills,"district in Meghalaya, India",http://www.wikidata.org/entity/Q1195,meghalaya,Indian state,,Q110442602,Eastern West Khasi Hills,Eastern West Khasi Hills,wikidataId/Q1195,wikidataId/Q110442602 +280,barpeta,18,assam,18.05,303,barpeta,http://www.wikidata.org/entity/Q41249,barpeta,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,303,Q41249,Barpeta,Barpeta,wikidataId/Q1164,wikidataId/Q41249 +281,bongaigaon,18,assam,18.04,319,bongaigaon,http://www.wikidata.org/entity/Q42197,bongaigaon,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,319,Q42197,Bongaigaon,Bongaigaon,wikidataId/Q1164,wikidataId/Q42197 +282,cachar,18,assam,18.21,316,cachar,http://www.wikidata.org/entity/Q42209,cachar,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,316,Q42209,Cachar,Cachar,wikidataId/Q1164,wikidataId/Q42209 +283,darrang,18,assam,18.08,325,darrang,http://www.wikidata.org/entity/Q42461,darrang,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,325,Q42461,Darrang,Darrang,wikidataId/Q1164,wikidataId/Q42461 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anglong,http://www.wikidata.org/entity/Q29025081,east karbi anglong,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,,Q29025081,Karbi Anglong,East Karbi Anglong,wikidataId/Q1164,wikidataId/Q29025081 +293,karimganj,18,assam,18.22,317,karimganj,http://www.wikidata.org/entity/Q42542,karimganj,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,317,Q42542,Karimganj,Karimganj,wikidataId/Q1164,wikidataId/Q42542 +294,kokrajhar,18,assam,18.01,300,kokrajhar,http://www.wikidata.org/entity/Q42618,kokrajhar,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,300,Q42618,Kokrajhar,Kokrajhar,wikidataId/Q1164,wikidataId/Q42618 +295,lakhimpur,18,assam,18.12,307,lakhimpur,http://www.wikidata.org/entity/Q42743,lakhimpur,"district of Assam, India",http://www.wikidata.org/entity/Q1164,assam,Indian state,307,Q42743,Lakhimpur,Lakhimpur,wikidataId/Q1164,wikidataId/Q42743 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state,354,Q2240791,Dhanbad,Dhanbad,wikidataId/Q1184,wikidataId/Q2240791 +326,dumka,20,jharkhand,20.11,362,dumka,http://www.wikidata.org/entity/Q2577657,dumka,"district of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,362,Q2577657,Dumka,Dumka,wikidataId/Q1184,wikidataId/Q2577657 +327,east singhbum,20,jharkhand,20.18,357,east singhbhum,http://www.wikidata.org/entity/Q2452921,east singhbhum,"district of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,357,Q2452921,East Singhbum,East Singhbhum,wikidataId/Q1184,wikidataId/Q2452921 +328,garhwa,20,jharkhand,20.01,346,garhwa,http://www.wikidata.org/entity/Q2302076,garhwa,"district of Jharkhand, India",http://www.wikidata.org/entity/Q1184,jharkhand,Indian state,346,Q2302076,Garhwa,Garhwa,wikidataId/Q1184,wikidataId/Q2302076 +329,giridih,20,jharkhand,20.06,349,giridih,http://www.wikidata.org/entity/Q2302065,giridih,"district of Jharkhand, 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India,490,Q1797349,Navsari,Navsari,wikidataId/Q1061,wikidataId/Q1797349 +454,panch mahals,24,gujarat,24.17,484,panchmahal,http://www.wikidata.org/entity/Q1781463,panchmahal,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,484,Q1781463,Panch Mahals,Panchmahal,wikidataId/Q1061,wikidataId/Q1781463 +455,patan,24,gujarat,24.03,470,patan,http://www.wikidata.org/entity/Q1815269,patan,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,470,Q1815269,Patan,Patan,wikidataId/Q1061,wikidataId/Q1815269 +456,porbandar,24,gujarat,24.11,478,porbandar,http://www.wikidata.org/entity/Q1772815,porbandar,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,478,Q1772815,Porbandar,Porbandar,wikidataId/Q1061,wikidataId/Q1772815 +457,rajkot,24,gujarat,24.09,476,rajkot,http://www.wikidata.org/entity/Q1815245,rajkot,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,476,Q1815245,Rajkot,Rajkot,wikidataId/Q1061,wikidataId/Q1815245 +458,sabar kantha,24,gujarat,24.05,472,sabarkantha,http://www.wikidata.org/entity/Q1772856,sabarkantha,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,472,Q1772856,Sabar Kantha,Sabarkantha,wikidataId/Q1061,wikidataId/Q1772856 +459,surat,24,gujarat,24.22,492,surat,http://www.wikidata.org/entity/Q1797317,surat,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,492,Q1797317,Surat,Surat,wikidataId/Q1061,wikidataId/Q1797317 +460,surendranagar,24,gujarat,24.08,475,surendranagar,http://www.wikidata.org/entity/Q237535,surendranagar,"District of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,475,Q237535,Surendranagar,Surendranagar,wikidataId/Q1061,wikidataId/Q237535 +461,vadodara,24,gujarat,24.19,486,vadodara,http://www.wikidata.org/entity/Q578285,vadodara,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,486,Q578285,Vadodara,Vadodara,wikidataId/Q1061,wikidataId/Q578285 +462,valsad,24,gujarat,24.25,491,valsad,http://www.wikidata.org/entity/Q1946743,valsad,"District of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,491,Q1946743,Valsad,Valsad,wikidataId/Q1061,wikidataId/Q1946743 +641,tapi,24,gujarat,,493,tapi,http://www.wikidata.org/entity/Q670165,tapi,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,493,Q670165,Tapi,Tapi,wikidataId/Q1061,wikidataId/Q670165 +668,chhotaudepur,24,gujarat,,,chhota udaipur,http://www.wikidata.org/entity/Q5979243,chhota udaipur,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,,Q5979243,Chhotaudepur,Chhota Udaipur,wikidataId/Q1061,wikidataId/Q5979243 +669,mahisagar,24,gujarat,,,mahisagar,http://www.wikidata.org/entity/Q5706885,mahisagar,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,,Q5706885,Mahisagar,Mahisagar,wikidataId/Q1061,wikidataId/Q5706885 +672,arvalli,24,gujarat,,,aravalli,http://www.wikidata.org/entity/Q12175285,aravalli,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,,Q12175285,Arvalli,Aravalli,wikidataId/Q1061,wikidataId/Q12175285 +673,morbi,24,gujarat,,,morbi,http://www.wikidata.org/entity/Q5979727,morbi,"district of Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,,Q5979727,Morbi,Morbi,wikidataId/Q1061,wikidataId/Q5979727 +674,devbhumi dwarka,24,gujarat,,,devbhoomi dwarka,http://www.wikidata.org/entity/Q14594717,devbhoomi dwarka,"district in Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,,Q14594717,Devbhumi Dwarka,Devbhoomi Dwarka,wikidataId/Q1061,wikidataId/Q14594717 +675,gir somnath,24,gujarat,,,gir somnath,http://www.wikidata.org/entity/Q15244465,gir somnath,"district in Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,,Q15244465,Gir Somnath,Gir Somnath,wikidataId/Q1061,wikidataId/Q15244465 +676,botad,24,gujarat,,,botad,http://www.wikidata.org/entity/Q14505072,botad,"district in Gujarat, India",http://www.wikidata.org/entity/Q1061,gujarat,state of India,,Q14505072,Botad,Botad,wikidataId/Q1061,wikidataId/Q14505072 +466,ahmednagar,27,maharashtra,27.26,522,ahmednagar,http://www.wikidata.org/entity/Q401744,ahmednagar,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,522,Q401744,Ahmednagar,Ahmednagar,wikidataId/Q1191,wikidataId/Q401744 +467,akola,27,maharashtra,27.05,501,akola,http://www.wikidata.org/entity/Q520510,akola,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,501,Q520510,Akola,Akola,wikidataId/Q1191,wikidataId/Q520510 +468,amravati,27,maharashtra,27.07,503,amravati,http://www.wikidata.org/entity/Q1771774,amravati,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,503,Q1771774,Amravati,Amravati,wikidataId/Q1191,wikidataId/Q1771774 +469,aurangabad,27,maharashtra,27.19,515,aurangabad,http://www.wikidata.org/entity/Q592942,aurangabad,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,515,Q592942,Aurangabad,Aurangabad,wikidataId/Q1191,wikidataId/Q592942 +470,beed,27,maharashtra,27.27,523,beed,http://www.wikidata.org/entity/Q814037,beed,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,523,Q814037,Beed,Beed,wikidataId/Q1191,wikidataId/Q814037 +471,bhandara,27,maharashtra,27.10,506,bhandara,http://www.wikidata.org/entity/Q1813857,bhandara,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,506,Q1813857,Bhandara,Bhandara,wikidataId/Q1191,wikidataId/Q1813857 +472,buldhana,27,maharashtra,27.04,500,buldhana,http://www.wikidata.org/entity/Q47929,buldhana,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,500,Q47929,Buldhana,Buldhana,wikidataId/Q1191,wikidataId/Q47929 +473,chandrapur,27,maharashtra,27.13,509,chandrapur,http://www.wikidata.org/entity/Q1797274,chandrapur,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,509,Q1797274,Chandrapur,Chandrapur,wikidataId/Q1191,wikidataId/Q1797274 +474,dhule,27,maharashtra,27.02,498,dhule,http://www.wikidata.org/entity/Q1797383,dhule,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,498,Q1797383,Dhule,Dhule,wikidataId/Q1191,wikidataId/Q1797383 +475,gadchiroli,27,maharashtra,27.12,508,gadchiroli,http://www.wikidata.org/entity/Q1804847,gadchiroli,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,508,Q1804847,Gadchiroli,Gadchiroli,wikidataId/Q1191,wikidataId/Q1804847 +476,gondia,27,maharashtra,27.11,507,gondia,http://www.wikidata.org/entity/Q1917227,gondia,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,507,Q1917227,Gondia,Gondia,wikidataId/Q1191,wikidataId/Q1917227 +477,hingoli,27,maharashtra,27.16,512,hingoli,http://www.wikidata.org/entity/Q2087615,hingoli,"district in Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,512,Q2087615,Hingoli,Hingoli,wikidataId/Q1191,wikidataId/Q2087615 +478,jalgaon,27,maharashtra,27.03,499,jalgaon,http://www.wikidata.org/entity/Q1797291,jalgaon,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,499,Q1797291,Jalgaon,Jalgaon,wikidataId/Q1191,wikidataId/Q1797291 +479,jalna,27,maharashtra,27.18,514,jalna,http://www.wikidata.org/entity/Q1804863,jalna,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,514,Q1804863,Jalna,Jalna,wikidataId/Q1191,wikidataId/Q1804863 +480,kolhapur,27,maharashtra,27.34,530,kolhapur,http://www.wikidata.org/entity/Q1797312,kolhapur,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,530,Q1797312,Kolhapur,Kolhapur,wikidataId/Q1191,wikidataId/Q1797312 +481,latur,27,maharashtra,27.28,524,latur,http://www.wikidata.org/entity/Q1948713,latur,district of Maharashtra in India,http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,524,Q1948713,Latur,Latur,wikidataId/Q1191,wikidataId/Q1948713 +482,mumbai,27,maharashtra,27.23,519,mumbai city,http://www.wikidata.org/entity/Q2341660,mumbai city,district of Maharashtra in Konkan Division,http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,519,Q2341660,Mumbai,Mumbai City,wikidataId/Q1191,wikidataId/Q2341660 +483,mumbai suburban,27,maharashtra,27.22,518,mumbai suburban,http://www.wikidata.org/entity/Q2085374,mumbai suburban,district of Maharashtra in India,http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,518,Q2085374,Mumbai Suburban,Mumbai Suburban,wikidataId/Q1191,wikidataId/Q2085374 +484,nagpur,27,maharashtra,27.09,505,nagpur,http://www.wikidata.org/entity/Q1797367,nagpur,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,505,Q1797367,Nagpur,Nagpur,wikidataId/Q1191,wikidataId/Q1797367 +485,nanded,27,maharashtra,27.15,511,nanded,http://www.wikidata.org/entity/Q692389,nanded,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,511,Q692389,Nanded,Nanded,wikidataId/Q1191,wikidataId/Q692389 +486,nandurbar,27,maharashtra,27.01,497,nandurbar,http://www.wikidata.org/entity/Q1623525,nandurbar,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,497,Q1623525,Nandurbar,Nandurbar,wikidataId/Q1191,wikidataId/Q1623525 +487,nashik,27,maharashtra,27.20,516,nashik,http://www.wikidata.org/entity/Q1797269,nashik,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,516,Q1797269,Nashik,Nashik,wikidataId/Q1191,wikidataId/Q1797269 +488,osmanabad,27,maharashtra,27.29,525,osmanabad,http://www.wikidata.org/entity/Q1647186,osmanabad,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,525,Q1647186,Osmanabad,Osmanabad,wikidataId/Q1191,wikidataId/Q1647186 +489,parbhani,27,maharashtra,27.17,513,parbhani,http://www.wikidata.org/entity/Q1797389,parbhani,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,513,Q1797389,Parbhani,Parbhani,wikidataId/Q1191,wikidataId/Q1797389 +490,pune,27,maharashtra,27.25,521,pune,http://www.wikidata.org/entity/Q1797336,pune,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,521,Q1797336,Pune,Pune,wikidataId/Q1191,wikidataId/Q1797336 +491,raigad,27,maharashtra,27.24,520,raigad,http://www.wikidata.org/entity/Q2019683,raigad,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,520,Q2019683,Raigad,Raigad,wikidataId/Q1191,wikidataId/Q2019683 +492,ratnagiri,27,maharashtra,27.32,528,ratnagiri,http://www.wikidata.org/entity/Q1771768,ratnagiri,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,528,Q1771768,Ratnagiri,Ratnagiri,wikidataId/Q1191,wikidataId/Q1771768 +493,sangli,27,maharashtra,27.35,531,sangli,http://www.wikidata.org/entity/Q1425060,sangli,district of Maharashtra state in west-central India,http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,531,Q1425060,Sangli,Sangli,wikidataId/Q1191,wikidataId/Q1425060 +494,satara,27,maharashtra,27.31,527,satara,http://www.wikidata.org/entity/Q1135612,satara,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,527,Q1135612,Satara,Satara,wikidataId/Q1191,wikidataId/Q1135612 +495,sindhudurg,27,maharashtra,27.33,529,sindhudurg,http://www.wikidata.org/entity/Q768332,sindhudurg,"district in Maharashtra , India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,529,Q768332,Sindhudurg,Sindhudurg,wikidataId/Q1191,wikidataId/Q768332 +496,solapur,27,maharashtra,27.30,526,solapur,http://www.wikidata.org/entity/Q1797263,solapur,district in Maharashtra state of India,http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,526,Q1797263,Solapur,Solapur,wikidataId/Q1191,wikidataId/Q1797263 +497,thane,27,maharashtra,27.21,517,thane,http://www.wikidata.org/entity/Q943099,thane,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,517,Q943099,Thane,Thane,wikidataId/Q1191,wikidataId/Q943099 +498,wardha,27,maharashtra,27.08,504,wardha,http://www.wikidata.org/entity/Q980608,wardha,"district in Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,504,Q980608,Wardha,Wardha,wikidataId/Q1191,wikidataId/Q980608 +499,washim,27,maharashtra,27.06,502,washim,http://www.wikidata.org/entity/Q1804858,washim,"district in Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,502,Q1804858,Washim,Washim,wikidataId/Q1191,wikidataId/Q1804858 +500,yavatmal,27,maharashtra,27.14,510,yavatmal,http://www.wikidata.org/entity/Q1804852,yavatmal,"district of Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,510,Q1804852,Yavatmal,Yavatmal,wikidataId/Q1191,wikidataId/Q1804852 +665,palghar,27,maharashtra,,,palghar,http://www.wikidata.org/entity/Q18003119,palghar,"District in Maharashtra, India",http://www.wikidata.org/entity/Q1191,maharashtra,state in the western and central peninsular region of India,,Q18003119,Palghar,Palghar,wikidataId/Q1191,wikidataId/Q18003119 +502,anantapur,28,andhra 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Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,557,Q83108,Vijayapura,Vijaypura,wikidataId/Q1185,wikidataId/Q83108 +531,chamarajanagara,29,karnataka,29.27,578,chamarajanagar,http://www.wikidata.org/entity/Q862912,chamarajanagar,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,578,Q862912,Chamarajanagara,Chamarajanagar,wikidataId/Q1185,wikidataId/Q862912 +532,chikkamagaluru,29,karnataka,29.17,570,chikkamagaluru,http://www.wikidata.org/entity/Q743077,chikkamagaluru,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,570,Q743077,Chikkamagaluru,Chikkamagaluru,wikidataId/Q1185,wikidataId/Q743077 +533,chitradurga,29,karnataka,29.13,566,chitradurga,http://www.wikidata.org/entity/Q165264,chitradurga,"district of Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,566,Q165264,Chitradurga,Chitradurga,wikidataId/Q1185,wikidataId/Q165264 +534,dakshina 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state,561,Q2353931,Gadag,Gadag,wikidataId/Q1185,wikidataId/Q2353931 +538,kalaburagi,29,karnataka,29.04,579,kalaburgi,http://www.wikidata.org/entity/Q2641873,kalaburgi,"district in Gulbarga division, Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,579,Q2641873,Kalaburagi,Kalaburgi,wikidataId/Q1185,wikidataId/Q2641873 +539,hassan,29,karnataka,29.23,574,hassan,http://www.wikidata.org/entity/Q956732,hassan,"district in Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,574,Q956732,Hassan,Hassan,wikidataId/Q1185,wikidataId/Q956732 +540,haveri,29,karnataka,29.11,564,haveri,http://www.wikidata.org/entity/Q765481,haveri,"district in Karnataka, India",http://www.wikidata.org/entity/Q1185,karnataka,Indian state,564,Q765481,Haveri,Haveri,wikidataId/Q1185,wikidataId/Q765481 +541,kodagu,29,karnataka,29.25,576,kodagu,http://www.wikidata.org/entity/Q1553185,kodagu,"district of Karnataka, 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state,621,Q15190,Pudukkottai,Pudukkottai,wikidataId/Q1445,wikidataId/Q15190 +583,ramanathapuram,33,tamil nadu,33.27,626,ramanathapuram,http://www.wikidata.org/entity/Q15191,ramanathapuram,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,626,Q15191,Ramanathapuram,Ramanathapuram,wikidataId/Q1445,wikidataId/Q15191 +584,salem,33,tamil nadu,33.08,608,salem,http://www.wikidata.org/entity/Q15192,salem,district of Tamil Nadu state in southern India,http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,608,Q15192,Salem,Salem,wikidataId/Q1445,wikidataId/Q15192 +585,sivaganga,33,tamil nadu,33.23,622,sivaganga,http://www.wikidata.org/entity/Q15195,sivaganga,"district of Tamil Nadu, India",http://www.wikidata.org/entity/Q1445,tamil nadu,Indian state,622,Q15195,Sivaganga,Sivaganga,wikidataId/Q1445,wikidataId/Q15195 +586,thanjavur,33,tamil nadu,33.21,620,thanjavur,http://www.wikidata.org/entity/Q15194,thanjavur,"district of Tamil Nadu, 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Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,539,Q15384,Nalgonda,Nalgonda,wikidataId/Q677037,wikidataId/Q15384 +516,nizamabad,36,telangana,28.02,533,nizamabad,http://www.wikidata.org/entity/Q15391,nizamabad,district of Telangana,http://www.wikidata.org/entity/Q677037,telangana,state in India,533,Q15391,Nizamabad,Nizamabad,wikidataId/Q677037,wikidataId/Q15391 +518,ranga reddy,36,telangana,28.06,537,ranga reddy,http://www.wikidata.org/entity/Q15388,ranga reddy,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,537,Q15388,Ranga Reddy,Ranga Reddy,wikidataId/Q677037,wikidataId/Q15388 +522,warangal,36,telangana,28.09,540,warangal,http://www.wikidata.org/entity/Q15399,warangal,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,540,Q15399,Warangal,Warangal,wikidataId/Q677037,wikidataId/Q28169759 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Sircilla,wikidataId/Q677037,wikidataId/Q28172781 +684,mancherial,36,telangana,,,mancherial,http://www.wikidata.org/entity/Q28169747,mancherial,district of Telangana,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169747,Mancherial,Mancherial,wikidataId/Q677037,wikidataId/Q28169747 +685,kamareddy,36,telangana,,,kamareddy,http://www.wikidata.org/entity/Q27956125,kamareddy,district of Telangana in India,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q27956125,Kamareddy,Kamareddy,wikidataId/Q677037,wikidataId/Q27956125 +686,hanumakonda,36,telangana,,,hanamkonda,http://www.wikidata.org/entity/Q213077,hanamkonda,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q213077,Hanumakonda,Hanamkonda,wikidataId/Q677037,wikidataId/Q213077 +687,jayashankar bhupalapally,36,telangana,,,jayashankar bhupalpally,http://www.wikidata.org/entity/Q28169775,jayashankar bhupalpally,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169775,Jayashankar Bhupalapally,Jayashankar Bhupalpally,wikidataId/Q677037,wikidataId/Q28169775 +688,mahabubabad,36,telangana,,,mahabubabad,http://www.wikidata.org/entity/Q28169761,mahabubabad,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169761,Mahabubabad,Mahabubabad,wikidataId/Q677037,wikidataId/Q28169761 +689,jangoan,36,telangana,,,jangaon,http://www.wikidata.org/entity/Q28170170,jangaon,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28170170,Jangoan,Jangaon,wikidataId/Q677037,wikidataId/Q28170170 +690,bhadradri kothagudem,36,telangana,,,bhadradri kothagudem,http://www.wikidata.org/entity/Q28169767,bhadradri kothagudem,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169767,Bhadradri Kothagudem,Bhadradri Kothagudem,wikidataId/Q677037,wikidataId/Q28169767 +691,sangareddy,36,telangana,,,sangareddy,http://www.wikidata.org/entity/Q28169753,sangareddy,district in Telangana,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169753,Sangareddy,Sangareddy,wikidataId/Q677037,wikidataId/Q28169753 +692,siddipet,36,telangana,,,siddipet,http://www.wikidata.org/entity/Q28169756,siddipet,district in Telangana,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169756,Siddipet,Siddipet,wikidataId/Q677037,wikidataId/Q28169756 +693,wanaparthy,36,telangana,,,wanaparthy,http://www.wikidata.org/entity/Q28172504,wanaparthy,"District of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28172504,Wanaparthy,Wanaparthy,wikidataId/Q677037,wikidataId/Q28172504 +694,nagarkurnool,36,telangana,,,nagarkurnool,http://www.wikidata.org/entity/Q28169773,nagarkurnool,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169773,Nagarkurnool,Nagarkurnool,wikidataId/Q677037,wikidataId/Q28169773 +695,jogulamba gadwal,36,telangana,,,jogulamba gadwal,http://www.wikidata.org/entity/Q27897618,jogulamba gadwal,district of Telangana in India,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q27897618,Jogulamba Gadwal,Jogulamba Gadwal,wikidataId/Q677037,wikidataId/Q27897618 +696,suryapet,36,telangana,,,suryapet,http://www.wikidata.org/entity/Q28169770,suryapet,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169770,Suryapet,Suryapet,wikidataId/Q677037,wikidataId/Q28169770 +697,yadadri bhuvanagiri,36,telangana,,,yadadri bhuvanagiri,http://www.wikidata.org/entity/Q28169764,yadadri bhuvanagiri,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169764,Yadadri Bhuvanagiri,Yadadri Bhuvanagiri,wikidataId/Q677037,wikidataId/Q28169764 +698,vikarabad,36,telangana,,,vikarabad,http://www.wikidata.org/entity/Q28170173,vikarabad,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28170173,Vikarabad,Vikarabad,wikidataId/Q677037,wikidataId/Q28170173 +699,kumuram bheem asifabad,36,telangana,,,kumaram bheem asifabad,http://www.wikidata.org/entity/Q28170184,kumaram bheem asifabad,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28170184,Kumuram Bheem Asifabad,Kumaram Bheem Asifabad,wikidataId/Q677037,wikidataId/Q28170184 +700,medchal malkajgiri,36,telangana,,,medchal–malkajgiri,http://www.wikidata.org/entity/Q27614841,medchal–malkajgiri,district of Telangana in India,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q27614841,Medchal Malkajgiri,Medchal–malkajgiri,wikidataId/Q677037,wikidataId/Q27614841 +720,mulugu,36,telangana,,,mulugu,http://www.wikidata.org/entity/Q61746006,mulugu,"district in Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q61746006,Mulugu,Mulugu,wikidataId/Q677037,wikidataId/Q61746006 +721,narayanpet,36,telangana,,,narayanpet,http://www.wikidata.org/entity/Q61746013,narayanpet,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q61746013,Narayanpet,Narayanpet,wikidataId/Q677037,wikidataId/Q61746013 +006,kargil,37,ladakh,01.08,004,kargil,http://www.wikidata.org/entity/Q1650798,kargil,1st District of Ladakh in India,http://www.wikidata.org/entity/Q200667,ladakh,union territory administered by India,004,Q1650798,Kargil,Kargil,wikidataId/Q200667,wikidataId/Q1650798 +009,leh ladakh,37,ladakh,01.07,003,leh,http://www.wikidata.org/entity/Q1921210,leh,"district in Ladakh, India",http://www.wikidata.org/entity/Q200667,ladakh,union territory administered by India,003,Q1921210,Leh Ladakh,Leh,wikidataId/Q200667,wikidataId/Q1921210 +463,daman,38,dadra and nagar haveli and daman and diu,25.02,495,daman,http://www.wikidata.org/entity/Q1158197,daman,district of Dadra and Nagar Haveli and Daman and Diu,http://www.wikidata.org/entity/Q77997266,dadra and nagar haveli and daman and diu,union territory in India,495,Q1158197,Daman,Daman,wikidataId/Q77997266,wikidataId/Q1158197 +464,diu,38,dadra and nagar haveli and daman and diu,25.01,494,diu,http://www.wikidata.org/entity/Q2552347,diu,"district in Dadra and Nagar Haveli and Daman and Diu, India",http://www.wikidata.org/entity/Q77997266,dadra and nagar haveli and daman and diu,union territory in India,494,Q2552347,Diu,Diu,wikidataId/Q77997266,wikidataId/Q2552347 +465,dadra and nagar haveli,38,dadra and nagar haveli and daman and diu,26.01,496,dadra and nagar haveli,http://www.wikidata.org/entity/Q46107,dadra and nagar haveli,district of Dadra and Nagar Haveli and Daman and Diu and former union territory,http://www.wikidata.org/entity/Q77997266,dadra and nagar haveli and daman and diu,union territory in India,496,Q46107,Dadra and Nagar Haveli,Dadra and Nagar Haveli,wikidataId/Q77997266,wikidataId/Q46107 diff --git a/scripts/india/geo/districts.py b/scripts/india/geo/districts.py index d42800ec54..536d679484 100644 --- a/scripts/india/geo/districts.py +++ b/scripts/india/geo/districts.py @@ -21,6 +21,35 @@ DISTRICTS_MAPPING_CSV = os.path.join(os.path.dirname(__file__), "LocalGovernmentDirectory_Districts.csv") +# Some districts have entirely different names over time or in some datasets. +# Even the closestDistrictLabel can't be used for mapping these districts. +# We will use this to map them to resolve it when all other options fail. +# +# This is used for mapping them. Format of the dictionary +# is defined below +# ALTERNATIVE_NAMES_MAPPING = { +# "state_lgd_code": { +# "district_lgd_code" : ["alt name1","alt name2"], +# } +# } +# + +ALTERNATIVE_NAMES_MAPPING = { + "11": { + "225": ["east sikkim", "east district", "gangtok"], + "226": ["north sikkim", "north district", "mangan"], + "227": ["south sikkim", "south district", "namchi"], + "228": ["west sikkim", "west district", "gyalshing"] + }, + "03": { + "031": ["firozpur", "ferozepore", "firozepur"] + }, + "36": { + "686": ["warangal urban", "hanumakonda"], + "522": ["warangal rural", "warangal"] + } +} + class IndiaDistrictsMapper: """Class for resolving various mappings for Indian districts """ @@ -66,6 +95,15 @@ def get_district_name_to_lgd_code_mapping(self, state_name, district_name): if len(df_districts.index) == 1: return list(df_districts["LGDDistrictCode"])[0] + # May be name is completely different now + if state_lgd_code in ALTERNATIVE_NAMES_MAPPING: + district_name_alternatives = ALTERNATIVE_NAMES_MAPPING[ + state_lgd_code] + for key, values in district_name_alternatives.items(): + if district_name in values: + return key + # This shouldn't happen - raise Exception("District name - {district_name} is not found".format( - district_name=district_name)) + raise Exception( + "{state_name} - District name - {district_name} is not found". + format(district_name=district_name, state_name=state_name)) diff --git a/scripts/india/geo/districts_test.py b/scripts/india/geo/districts_test.py index 38a68cf7ac..e39a4f57c5 100644 --- a/scripts/india/geo/districts_test.py +++ b/scripts/india/geo/districts_test.py @@ -58,3 +58,43 @@ def test_get_district_name_to_lgd_code_mapping(self): district_lgd_code = mapper.get_district_name_to_lgd_code_mapping( "telangana", "warangal") self.assertEqual(district_lgd_code, "522") + + district_lgd_code = mapper.get_district_name_to_lgd_code_mapping( + "andhra pradesh", "nandyal") + self.assertEqual(district_lgd_code, "755") + + district_lgd_code = mapper.get_district_name_to_lgd_code_mapping( + "andhra pradesh", "ntr") + self.assertEqual(district_lgd_code, "749") + + district_lgd_code = mapper.get_district_name_to_lgd_code_mapping( + "Meghalaya", "eastern west khasi hills") + self.assertEqual(district_lgd_code, "740") + + district_lgd_code = mapper.get_district_name_to_lgd_code_mapping( + "nagaland", "tseminyu") + self.assertEqual(district_lgd_code, "757") + + district_lgd_code = mapper.get_district_name_to_lgd_code_mapping( + "assam", "tamulpur") + self.assertEqual(district_lgd_code, "756") + + district_lgd_code = mapper.get_district_name_to_lgd_code_mapping( + "sikkim", "Soreng") + self.assertEqual(district_lgd_code, "742") + + district_lgd_code = mapper.get_district_name_to_lgd_code_mapping( + "sikkim", "Pakyong") + self.assertEqual(district_lgd_code, "741") + + district_lgd_code = mapper.get_district_name_to_lgd_code_mapping( + "sikkim", "north district") + self.assertEqual(district_lgd_code, "226") + + district_lgd_code = mapper.get_district_name_to_lgd_code_mapping( + "telangana", "warangal urban") + self.assertEqual(district_lgd_code, "686") + + district_lgd_code = mapper.get_district_name_to_lgd_code_mapping( + "telangana", "warangal rural") + self.assertEqual(district_lgd_code, "522") diff --git a/scripts/india_census/primary_religion_data/preprocess.py b/scripts/india_census/primary_religion_data/preprocess.py index 67fb90b92d..a8783579e5 100644 --- a/scripts/india_census/primary_religion_data/preprocess.py +++ b/scripts/india_census/primary_religion_data/preprocess.py @@ -183,8 +183,8 @@ def stat_var_index_key(row, data_category_column=None): # When data_category i.e religion is "Total" remove those rows # As they are not required - self.raw_df = self.raw_df[ - self.raw_df[self.data_category_column] != "Total"] + self.raw_df = self.raw_df[self.raw_df[self.data_category_column] != + "Total"] # Converting rows in to columns. So the final structure will be # Name,TRU,columnName,value diff --git a/scripts/india_geosadak/India_GeoSadak.mcf b/scripts/india_geosadak/India_GeoSadak.mcf index 3894786999..9a821b8a59 100644 --- a/scripts/india_geosadak/India_GeoSadak.mcf +++ b/scripts/india_geosadak/India_GeoSadak.mcf @@ -1,27 +1,27 @@ Node: dcid:Count_CivicStructure_AgriculturalFacility typeOf: dcs:StatisticalVariable populationType: dcs:CivicStructure -civicStructureType: dcs:AgriculturalFacility +placeCategory: dcs:AgriculturalFacility measuredProperty: dcs:count statType: dcs:measuredValue Node: dcid:Count_CivicStructure_TransportOrAdminFacility typeOf: dcs:StatisticalVariable populationType: dcs:CivicStructure -civicStructureType: dcs:TransportOrAdminFacility +placeCategory: dcs:TransportOrAdminFacility measuredProperty: dcs:count statType: dcs:measuredValue Node: dcid:Count_CivicStructure_EducationFacility typeOf: dcs:StatisticalVariable populationType: dcs:CivicStructure -civicStructureType: dcs:EducationFacility +placeCategory: dcs:EducationFacility measuredProperty: dcs:count statType: dcs:measuredValue Node: dcid:Count_CivicStructure_MedicalFacility typeOf: dcs:StatisticalVariable populationType: dcs:CivicStructure -civicStructureType: dcs:MedicalFacility +placeCategory: dcs:MedicalFacility measuredProperty: dcs:count statType: dcs:measuredValue diff --git a/scripts/india_lgd/local_government_directory_districts/LocalGovernmentDirectory_Districts.csv b/scripts/india_lgd/local_government_directory_districts/LocalGovernmentDirectory_Districts.csv index 83b012b6fc..d70a339c49 100644 --- a/scripts/india_lgd/local_government_directory_districts/LocalGovernmentDirectory_Districts.csv +++ b/scripts/india_lgd/local_government_directory_districts/LocalGovernmentDirectory_Districts.csv @@ -53,7 +53,7 @@ LGDDistrictCode,LGDDistrictName,LGDStateCode,LGDStateName,LGDCensus2001Code,LGDC 609,tarn taran,03,punjab,,050,tarn taran,http://www.wikidata.org/entity/Q2298993,tarn taran,"district in Punjab, India",http://www.wikidata.org/entity/Q22424,punjab,Indian state,050,Q2298993,Tarn Taran,Tarn Taran,wikidataId/Q22424,wikidataId/Q2298993 651,fazilka,03,punjab,,,fazilka,http://www.wikidata.org/entity/Q188702,fazilka,"district of Punjab, India",http://www.wikidata.org/entity/Q22424,punjab,Indian state,,Q188702,Fazilka,Fazilka,wikidataId/Q22424,wikidataId/Q188702 662,pathankot,03,punjab,,,pathankot,http://www.wikidata.org/entity/Q172269,pathankot,"district in Punjab, India",http://www.wikidata.org/entity/Q22424,punjab,Indian state,,Q172269,Pathankot,Pathankot,wikidataId/Q22424,wikidataId/Q172269 -737,malerkotla,03,punjab,,,malerkotla,http://www.wikidata.org/entity/Q107016021,malerkotla,"district in Punjab, India",http://www.wikidata.org/entity/Q22424,punjab,Indian state,,Q107016021,Malerkotla,Malerkotla,wikidataId/Q22424,wikidataId/Q107016021 +737,malerkotla,03,punjab,,,malerkotla,http://www.wikidata.org/entity/Q107016021,malerkotla,"district in Punjab, India",http://www.wikidata.org/entity/Q22424,punjab,Indian state,,Q107016021,Malerkotla,Malerkotla,wikidataId/Q22424,wikidataId/Q1470987 044,chandigarh,04,chandigarh,04.01,055,chandigarh,http://www.wikidata.org/entity/Q5071071,chandigarh,"district of Chandigarh, India",http://www.wikidata.org/entity/Q43433,chandigarh,"capital of Punjab and Haryana states, Union Territory of India",055,Q5071071,Chandigarh,Chandigarh,wikidataId/Q43433,wikidataId/Q5071071 045,almora,05,uttarakhand,05.09,064,almora,http://www.wikidata.org/entity/Q1805066,almora,"district of Uttarakhand, India",http://www.wikidata.org/entity/Q1499,uttarakhand,Indian state,064,Q1805066,Almora,Almora,wikidataId/Q1499,wikidataId/Q1805066 046,bageshwar,05,uttarakhand,05.08,063,bageshwar,http://www.wikidata.org/entity/Q1815313,bageshwar,"district of Uttarakhand, India",http://www.wikidata.org/entity/Q1499,uttarakhand,Indian state,063,Q1815313,Bageshwar,Bageshwar,wikidataId/Q1499,wikidataId/Q1815313 @@ -727,7 +727,7 @@ LGDDistrictCode,LGDDistrictName,LGDStateCode,LGDStateName,LGDCensus2001Code,LGDC 514,nalgonda,36,telangana,28.08,539,nalgonda,http://www.wikidata.org/entity/Q15384,nalgonda,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,539,Q15384,Nalgonda,Nalgonda,wikidataId/Q677037,wikidataId/Q15384 516,nizamabad,36,telangana,28.02,533,nizamabad,http://www.wikidata.org/entity/Q15391,nizamabad,district of Telangana,http://www.wikidata.org/entity/Q677037,telangana,state in India,533,Q15391,Nizamabad,Nizamabad,wikidataId/Q677037,wikidataId/Q15391 518,ranga reddy,36,telangana,28.06,537,ranga reddy,http://www.wikidata.org/entity/Q15388,ranga reddy,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,537,Q15388,Ranga Reddy,Ranga Reddy,wikidataId/Q677037,wikidataId/Q15388 -522,warangal,36,telangana,28.09,540,warangal,http://www.wikidata.org/entity/Q15399,warangal,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,540,Q15399,Warangal,Warangal,wikidataId/Q677037,wikidataId/Q15399 +522,warangal,36,telangana,28.09,540,warangal,http://www.wikidata.org/entity/Q15399,warangal,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,540,Q15399,Warangal,Warangal,wikidataId/Q677037,wikidataId/Q28169759 680,nirmal,36,telangana,,,nirmal,http://www.wikidata.org/entity/Q28169750,nirmal,district of Telangana,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169750,Nirmal,Nirmal,wikidataId/Q677037,wikidataId/Q28169750 681,jagitial,36,telangana,,,jagtial,http://www.wikidata.org/entity/Q28169780,jagtial,"district of Telangana, India",http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q28169780,Jagitial,Jagtial,wikidataId/Q677037,wikidataId/Q28169780 682,peddapalli,36,telangana,,,peddapalli,http://www.wikidata.org/entity/Q27614797,peddapalli,district of Telangana,http://www.wikidata.org/entity/Q677037,telangana,state in India,,Q27614797,Peddapalli,Peddapalli,wikidataId/Q677037,wikidataId/Q27614797 diff --git a/scripts/india_lgd/local_government_directory_districts/preprocess.py b/scripts/india_lgd/local_government_directory_districts/preprocess.py index 09dad35461..aac4b4505a 100644 --- a/scripts/india_lgd/local_government_directory_districts/preprocess.py +++ b/scripts/india_lgd/local_government_directory_districts/preprocess.py @@ -45,6 +45,16 @@ }, } +# On Wikidata for some of the districts they +# have created a new entity. Since our DCID +# is based on the WikidataId, we cant use the new ones +# as it will change the mapping and hence this override. + +WIKIDATAID_DCID_OVERRIDE_MAPPING = { + "Q15399": "Q28169759", + "Q107016021": "Q1470987" +} + class LocalGovermentDirectoryDistrictsDataLoader: @@ -80,7 +90,7 @@ def get_closest_district_label(self, lgddata_row): lgdCensus2011Code = lgddata_row["LGDCensus2011Code"] # Lets match them based on census code 2011 first - if lgdCensus2011Code is not None and lgdCensus2011Code is not "": + if lgdCensus2011Code is not None and lgdCensus2011Code != "": wikidata_df_row = self.wikidata_df.loc[ self.wikidata_df["census2011Code"] == lgdCensus2011Code] if wikidata_df_row.empty: @@ -152,6 +162,10 @@ def _load_and_format_lgd(self): axis=1) def _get_district_dcid(self, row): + # checkif there is override, then use it + if row["WikiDataId"] in WIKIDATAID_DCID_OVERRIDE_MAPPING: + return "wikidataId/{0}".format( + WIKIDATAID_DCID_OVERRIDE_MAPPING[row["WikiDataId"]]) return "wikidataId/{0}".format(row["WikiDataId"]) def _get_state_dcid(self, row): @@ -238,4 +252,4 @@ def main(): if __name__ == '__main__': - main() + main() \ No newline at end of file diff --git a/scripts/india_lgd/local_government_directory_districts/preprocess_test.py b/scripts/india_lgd/local_government_directory_districts/preprocess_test.py index bde6609ae9..1e9de54d05 100644 --- a/scripts/india_lgd/local_government_directory_districts/preprocess_test.py +++ b/scripts/india_lgd/local_government_directory_districts/preprocess_test.py @@ -67,6 +67,7 @@ def test_create_csv(self): row = clean_df.loc[clean_df["LGDDistrictName"] == "malerkotla"] self.assertEqual("malerkotla", row.iloc[0]["closestDistrictLabel"]) self.assertEqual("Q107016021", row.iloc[0]["WikiDataId"]) + self.assertEqual("wikidataId/Q1470987", row.iloc[0]["DistrictDCID"]) # `Warangal Urban` renamed `Hanamkonda` row = clean_df.loc[clean_df["WikiDataId"] == "Q213077"] @@ -75,9 +76,13 @@ def test_create_csv(self): # `Warangal Rural` renamed `Warangal` row = clean_df.loc[clean_df["WikiDataId"] == "Q15399"] self.assertEqual("warangal", row.iloc[0]["LGDDistrictName"]) + self.assertEqual("wikidataId/Q28169759", row.iloc[0]["DistrictDCID"]) + + row = clean_df.loc[clean_df["WikiDataId"] == "Q8560886"] + self.assertEqual("new delhi", row.iloc[0]["LGDDistrictName"]) os.remove(clean_csv) if __name__ == '__main__': - unittest.main() + unittest.main() \ No newline at end of file diff --git a/scripts/oecd/sdmx/README.md b/scripts/oecd/sdmx/README.md new file mode 100644 index 0000000000..c080200426 --- /dev/null +++ b/scripts/oecd/sdmx/README.md @@ -0,0 +1,30 @@ +# OECD Bulk Import + +This folder contains scripts for the bulk OECD import. This is currently a schemaless import. + +Note: This was a very quick first pass attempt to get some data in, so only contains a few hundred of the OECD datasets that follow a specific format. + +TODO(nhdiaz): Add tests / get remaining data. + +To download data: +``` +OPENSSL_CONF=openssl.cnf python3 download.py +``` + +To process data and generate artifacts: +``` +python3 process.py +``` + +## SDMX + +OECD uses the SDMX format for their data. We have translated this into the Data Commons data model as follows: + +* The LOCATION dimension is used for observationAbout +* The TIME_PERIOD dimension is used for observationDate +* The TIME_FORMAT attribute is used for observationPeriod +* The UNIT attribute is used for unit +* The POWERCODE attribute is used for scalingFactor +* The OBS_STATUS (observation level) attribute is used for measurementMethod +* All other dimensions and attributes are added the stat var definition +* The series is used as the parent SVG \ No newline at end of file diff --git a/scripts/oecd/sdmx/countries b/scripts/oecd/sdmx/countries new file mode 100644 index 0000000000..a8fa622104 --- /dev/null +++ b/scripts/oecd/sdmx/countries @@ -0,0 +1,265 @@ +ABW +AFG +AFI +AGO +AIA +ALB +AND +ANT +ARE +ARG +ARM +ASM +ATA +ATB +ATF +ATG +ATN +AUS +AUT +AZE +BDI +BEL +BEN +BES +BFA +BGD +BGR +BHR +BHS +BIH +BLM +BLR +BLZ +BMU +BOL +BRA +BRB +BRN +BTN +BVT +BWA +BYS +CAF +CAN +CCK +CHE +CHL +CHN +CIV +CMR +COD +COG +COK +COL +COM +CPV +CRI +CSK +CTE +CUB +CUW +CXR +CYM +CYP +CZE +DDR +DEU +DHY +DJI +DMA +DNK +DOM +DZA +ECU +EGY +ERI +ESH +ESP +EST +ETH +FIN +FJI +FLK +FRA +FRO +FSM +FXX +GAB +GBR +GEL +GEO +GGY +GHA +GIB +GIN +GLP +GMB +GNB +GNQ +GRC +GRD +GRL +GTM +GUF +GUM +GUY +HKG +HMD +HND +HRV +HTI +HUN +HVO +IDN +IMN +IND +IOT +IRL +IRN +IRQ +ISL +ISR +ITA +JAM +JEY +JOR +JPN +KAZ +KEN +KGZ +KHM +KIR +KNA +KOR +KWT +LAO +LBN +LBR +LBY +LCA +LIE +LKA +LSO +LTU +LUX +LVA +MAC +MAF +MAR +MCO +MDA +MDG +MDV +MEX +MHL +MKD +MLI +MLT +MMR +MNE +MNG +MNP +MOZ +MRT +MSR +MTQ +MUS +MWI +MYS +MYT +NAM +NCL +NER +NFK +NGA +NHB +NIC +NIU +NLD +NOR +NPL +NRU +NZL +OMN +PAK +PAN +PCN +PER +PHL +PLW +PNG +POL +PRI +PRK +PRT +PRY +PSE +PYF +QAT +REU +ROU +RUS +RWA +SAU +SCG +SDN +SEN +SGP +SGS +SHN +SJM +SLB +SLE +SLV +SMR +SOM +SPM +SRB +SSD +STP +SUN +SUR +SVK +SVN +SWE +SWZ +SXM +SYC +SYR +TCA +TCD +TGO +THA +TJK +TKL +TKM +TLS +TON +TTO +TUN +TUR +TUV +TWN +TZA +UGA +UKR +UMI +URY +USA +UZB +VAT +VCT +VEN +VGB +VIR +VNM +VUT +WLF +WSM +XKS +YEM +YUG +ZAF +ZMB +ZWE diff --git a/scripts/oecd/sdmx/download.py b/scripts/oecd/sdmx/download.py new file mode 100644 index 0000000000..4e5852a5d2 --- /dev/null +++ b/scripts/oecd/sdmx/download.py @@ -0,0 +1,82 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +''' +Bulk downloads OECD datasets. + +Note: this currently is a "best-effort" single pass and will just skip any +datasets with errors or failures. + +Produces: +* identifiers.csv: Series codes and names. +* input/.json: Folder of all fetched input datasets. + +Usage: OPENSSL_CONF=openssl.cnf python3 download.py +''' +import csv +import json +import requests +import os +from xml.etree import ElementTree + +PREFIX = '{http://www.SDMX.org/resources/SDMXML/schemas/v2_0/' + + +def get_series(): + '''Gets all series. + + Returns: + Map of series code -> name. + ''' + series = {} + response = requests.get( + 'https://stats.oecd.org/RestSDMX/sdmx.ashx/GetKeyFamily/all') + root = ElementTree.fromstring(response.content) + for child in root: + for key in child: + if key.tag == PREFIX + 'structure}KeyFamily' and 'id' in key.attrib: + for attr in key: + if '{http://www.w3.org/XML/1998/namespace}lang' in attr.attrib and attr.attrib[ + '{http://www.w3.org/XML/1998/namespace}lang'] == 'en': + series[key.attrib['id']] = attr.text + return series + + +if __name__ == '__main__': + + # Precompute series list to avoid refetching on failure. + with open('identifiers.csv', 'w') as f: + series = get_series() + writer = csv.writer(f) + for s in sorted(series): + writer.writerow([s, series[s]]) + + if not os.path.exists('input'): + os.makedirs('input') + + with open('identifiers.csv') as f_in: + reader = csv.reader(f_in) + for row in reader: + identifier = row[0] + print(identifier) + try: + result = requests.get( + f'http://stats.oecd.org/sdmx-json/data/{identifier}/all/all' + ) + with open(f'input/{identifier}.json', 'w') as f_out: + try: + f_out.write(json.dumps(result.json())) + except: + print('Error parsing:', identifier) + except: + print('Error fetching data for:', identifier) diff --git a/scripts/oecd/sdmx/openssl.cnf b/scripts/oecd/sdmx/openssl.cnf new file mode 100644 index 0000000000..e9a4029ad2 --- /dev/null +++ b/scripts/oecd/sdmx/openssl.cnf @@ -0,0 +1,10 @@ +openssl_conf = openssl_init + +[openssl_init] +ssl_conf = ssl_sect + +[ssl_sect] +system_default = system_default_sect + +[system_default_sect] +Options = UnsafeLegacyRenegotiation diff --git a/scripts/oecd/sdmx/process.py b/scripts/oecd/sdmx/process.py new file mode 100644 index 0000000000..24323357d0 --- /dev/null +++ b/scripts/oecd/sdmx/process.py @@ -0,0 +1,329 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +'''Process OECD datasets. + +Produces: +* output/.csv: Folder of cleaned csvs. +* schema/svg.mcf: SVG custom hierarchy. +* schema/measurement_method.mcf +* schema/unit.mcf +* sv/.csv: Folder of stat var mcf. + +Usage: python3 process.py +''' +import csv +import json +import os + +FIELDNAMES = [ + 'observation_about', 'variable_measured', 'value', 'observation_date', + 'observation_period', 'measurement_method', 'unit', 'scaling_factor' +] +SKIPPED = { + 'AMOUNTTYPE', # Use UNIT instead. + 'FREQUENCY', # Use TIME_FORMAT instead. +} +with open('countries') as f: + COUNTRIES = set(f.read().split()) +SV_TEMPLATE = ''' +Node: dcid:{dcid} +typeOf: dcs:StatisticalVariable +measuredProperty: dcid:{dcid} +memberOf: dcs:{svg} +name: "{name}" +populationType: dcs:Thing +statType: dcs:measuredValue +''' +SVG_ROOT = ''' +Node: dcid:oecd/g/OECD +typeOf: dcs:StatVarGroup +name: "Organisation for Economic Co-operation and Development" +specializationOf: dcs:dc/g/Root +''' +SVG_TEMPLATE = ''' +Node: dcid:oecd/g/{dcid} +typeOf: dcs:StatVarGroup +name: "{name}" +specializationOf: dcs:oecd/g/OECD +''' +MEASUREMENT_METHOD_CLASS = ''' +Node: dcid:OECD_MeasurementMethodEnum +typeOf: schema:Class +name: "OECD_MeasurementMethodEnum" +subClassOf: dcs:Enumeration +''' +MEASUREMENT_METHOD_TEMPLATE = ''' +Node: dcid:OECD_{dcid} +typeOf: dcs:OECD_MeasurementMethodEnum +name: "{dcid}" +description: "OECD Measurement Method: {name}" +''' +UNIT_TEMPLATE = ''' +Node: dcid:OECD_{dcid} +typeOf: dcs:UnitOfMeasure +name: "{dcid}" +description: "OECD Unit: {name}" +''' + + +def get_value(a, idx, key, prop): + '''Fetches value for given index, key, and property. + + Args: + a: Input structure (dimensions or attributes). + idx: Index of concept. + key: List of concept keys. + prop: Property. + + Returns: + Corresponding value, if it exists. + ''' + if not a[idx]['values']: + return '' + if key[idx] is None: + return '' + return a[idx]['values'][key[idx]][prop] + + +def make_sv(code, series, dim, attr, dim_idx, attr_idx, dim_key, attr_key): + '''Generates stat var. + + Args: + code: Series code. + series: Series name. + dim: Dimensions structure. + attr: Attributes structure. + dim_idx: List of dimension indices to keep. + attr_idx: List of attribute indices to keep. + dim_key: List of dimension keys. + attr_key: List of attribute keys. + + Returns: + Tuple of stat var (dcid, name, series code). + ''' + dcid = 'oecd/' + code + name = series + values = [] + for idx in dim_idx: + i = get_value(dim, idx, dim_key, 'id') + if i: + dcid += '_' + i + values.append(get_value(dim, idx, dim_key, 'name').strip()) + for idx in attr_idx: + i = get_value(attr, idx, attr_key, 'id') + if i: + dcid += '_' + i + values.append(get_value(attr, idx, attr_key, 'name').strip()) + if values: + name += ': ' + ', '.join(values) + return (dcid, name, code) + + +def make_date(s): + '''Formats date. + + Args: + s: Input string. + + Returns: + Formatted date. + ''' + date = s.replace('B1', '01') + date = date.replace('B2', '06') + date = date.replace('Q1', '01') + date = date.replace('Q2', '03') + date = date.replace('Q3', '06') + return date.replace('Q4', '09') + + +def write_schema(file, prefix, items, template): + '''Writes mcf to file. + + Args: + file: Output file path. + prefix: Optional prefix MCF. + items: Set of MCF to write. + template: Template string to match. + ''' + with open(file, 'w') as f: + f.write(prefix) + for x in sorted(items): + f.write(template.format_map({ + 'dcid': x[0], + 'name': x[1], + })) + + +if __name__ == '__main__': + if not os.path.exists('output'): + os.makedirs('output') + if not os.path.exists('sv'): + os.makedirs('sv') + if not os.path.exists('schema'): + os.makedirs('schema') + + svgs = set() + measurement_methods = set() + units = set() + for file in sorted(os.listdir('input')): + with open(f'input/{file}') as f_in: + code = file.removesuffix('.json') + print(code) + try: + data = json.load(f_in) + except: + print('Error loading:', file) + continue + + s = data['structure'] + + dimensions = [] + location_idx = None + dates = [] + dim_idx = [] + for x in s['dimensions']: + for y in s['dimensions'][x]: + if 'keyPosition' in y: + dimensions.insert(int(y['keyPosition']), y) + if y['id'] == 'LOCATION': + location_idx = y['keyPosition'] + elif y['id'] == 'TIME_PERIOD': + dates = [make_date(date['id']) for date in y['values']] + elif y['id'] not in SKIPPED: + dim_idx.append(y['keyPosition']) + + # Only support LOCATION for observation_about for now. + if location_idx is None: + continue + + # Only support TIME_PERIOD for observation_date for now. + if not dates: + continue + + attributes = s['attributes']['series'] + observation_period_idx = None + unit_idx = None + scaling_factor_idx = None + attr_idx = [] + for i, x in enumerate(attributes): + if x['id'] == 'TIME_FORMAT': + observation_period_idx = i + elif x['id'] == 'UNIT': + unit_idx = i + elif x['id'] == 'POWERCODE': + scaling_factor_idx = i + elif x['id'] not in SKIPPED: + attr_idx.append(i) + + if observation_period_idx is None: + continue + + obs_status = [] + for x in s['attributes']['observation']: + if x['id'] == 'OBS_STATUS': + obs_status = x['values'] + else: + print('Additional observation attribute:', x['id'], code) + + svs = set() + with open(f'output/{code}.csv', 'w') as f_out: + writer = csv.DictWriter(f_out, fieldnames=FIELDNAMES) + writer.writeheader() + d = data['dataSets'][0] + for dimension_key in d['series']: + dim_key = [int(x) for x in dimension_key.split(':')] + observation_about = get_value(dimensions, location_idx, + dim_key, 'id') + + # Only support countries for now. + if observation_about not in COUNTRIES: + continue + + attr_key = d['series'][dimension_key]['attributes'] + sv = make_sv(code, s['name'], dimensions, attributes, + dim_idx, attr_idx, dim_key, attr_key) + + observation_period = get_value(attributes, + observation_period_idx, + attr_key, 'id') + if not observation_period: + continue + + unit = get_value(attributes, unit_idx, attr_key, + 'id') if unit_idx is not None else '' + scaling_factor = get_value( + attributes, scaling_factor_idx, attr_key, + 'id') if scaling_factor_idx is not None else '' + + obs = d['series'][dimension_key]['observations'] + for date_key in obs: + value = obs[date_key][0] + if not value: + continue + + measurement_method = obs_status[ + obs[date_key][1]] if obs_status and len( + obs[date_key]) > 1 and obs[date_key][1] else '' + writer.writerow({ + 'observation_about': + f'dcs:country/{observation_about}', + 'variable_measured': + 'dcs:' + sv[0], + 'value': + value, + 'observation_date': + dates[int(date_key)], + 'observation_period': + observation_period, + 'measurement_method': + 'dcs:OECD_' + + measurement_method['id'].replace('; ', '_') + if measurement_method else '', + 'unit': + f'dcs:OECD_{unit}' if unit else '', + 'scaling_factor': + scaling_factor, + }) + + if measurement_method: + measurement_methods.add( + (measurement_method['id'].replace('; ', '_'), + measurement_method['name'])) + + svs.add(sv) + svgs.add((code, s['name'])) + if unit: + units.add((unit, + get_value(attributes, unit_idx, attr_key, + 'name'))) + + if svs: + with open(f'sv/{code}.mcf', 'w') as f_out: + for x in sorted(svs): + f_out.write( + SV_TEMPLATE.format_map({ + 'dcid': x[0], + 'name': x[1].replace('"', '\''), + 'svg': 'oecd/g/' + x[2], + })) + + if svgs: + write_schema('schema/svg.mcf', SVG_ROOT, svgs, SVG_TEMPLATE) + + if measurement_methods: + write_schema('schema/measurement_method.mcf', MEASUREMENT_METHOD_CLASS, + measurement_methods, MEASUREMENT_METHOD_TEMPLATE) + + if units: + write_schema('schema/unit.mcf', '', units, UNIT_TEMPLATE) diff --git a/scripts/un/boundaries/.gitignore b/scripts/un/boundaries/.gitignore new file mode 100644 index 0000000000..21b61f9e7b --- /dev/null +++ b/scripts/un/boundaries/.gitignore @@ -0,0 +1 @@ +output/** diff --git a/scripts/un/boundaries/README.md b/scripts/un/boundaries/README.md new file mode 100644 index 0000000000..9796c81f05 --- /dev/null +++ b/scripts/un/boundaries/README.md @@ -0,0 +1,47 @@ +# Import Scripts for UN Country Boundaries + +### Download URL + +From [UN Geodata +Simplified](https://geoportal.un.org/arcgis/apps/sites/#/geohub/datasets/d7caaff3ef4b4f7c82689b7c4694ad92/about), +the UN team got us the BNDA geojson that is checked into `data/`. + +### Overview + +This script generates both the MCFs as well as the json caches used +in the DC website. + +Since Place geos have a single provenance and we want to use these +boundaries only for UN SDG, we add them as a new `geoJsonCoordinatesUN` +property (plus `DPx` suffixes). + +The following countries in DC do not have boundaries: +* country/ANT +* country/ATB +* country/ATN +* country/CTE +* country/FXX +* country/IOT +* country/UMI +* country/WLF +* country/XKS +* country/YUG + +Among those, the following ones have boundary from World Bank source: +* country/IOT +* country/UMI +* country/WLF + + +### Scripts + +Run the following script to generate Website cache and MCFs ready for import. + +```bash +export MIXER_API_KEY= +./run.sh +``` + +Copy the contents of `output/mcf` over for manifesting. + +Copy the contents of `output/cache` to the website repo. diff --git a/scripts/un/boundaries/__init__.py b/scripts/un/boundaries/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/scripts/un/boundaries/country_boundaries.py b/scripts/un/boundaries/country_boundaries.py new file mode 100644 index 0000000000..9c519e7518 --- /dev/null +++ b/scripts/un/boundaries/country_boundaries.py @@ -0,0 +1,326 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" +Generates mcf files for country / AdministrativeArea0 boundaries from UN data. + +MCF files are generated for both high res data from the source, and simplified boundaries for +interactive applications. Geojsons are simplified using +https://geopandas.readthedocs.io/en/latest/docs/reference/api/geopandas.GeoSeries.simplify.html + +NOTE: this file generates temporary folders that are not deleted. +""" + +from typing import Dict + +import datacommons as dc +import geopandas as gpd +from geojson_rewind import rewind +import json +import os +import requests + +from absl import app +from absl import flags + +FLAGS = flags.FLAGS +flags.DEFINE_string('input_file', 'data/UNGIS_BNDA.geojson', + 'Input geojson file') +flags.DEFINE_string( + 'output_dir', 'output', + 'Dir to output generated MCF files too. If blank, a temp folder will be used.' +) + +# Threshold to DP level map, from scripts/us_census/geojsons_low_res/generate_mcf.py +EPS_LEVEL_MAP = {0: 0, 0.03: 2, 0.05: 3, 0.125: 6, 0.225: 10, 0.3: 13} + +MCF_PATH = '{MCF_OUT_FOLDER}/mcf/countries.dp{dp_level}.mcfgeojson.mcf' +MCF_FORMAT_STR = "\n".join([ + "Node: dcid:country/{country_code}", "typeOf: dcs:Country", + "{prop}: {coords_str}", "\n" +]) +MULTILINE_GEOJSON_TYPE = "MultiLineString" +MULTIPOLYGON_GEOJSON_TYPE = "MultiPolygon" +POLYGON_GEOJSON_TYPE = "Polygon" + +# Map from parent-place DCID to DP level +PARENT_PLACES = { + 'Earth': 13, + 'asia': 10, + 'africa': 10, + 'europe': 6, + 'northamerica': 13, + 'oceania': 13, + 'southamerica': 10, + 'AustraliaAndNewZealand': 6, + 'Caribbean': 6, + 'CentralAmerica': 6, + 'CentralAsia': 6, + 'ChannelIslands': 6, + 'EasternAfrica': 6, + 'EasternAsia': 6, + 'EasternEurope': 6, + 'EuropeanUnion': 6, + 'LatinAmericaAndCaribbean': 6, + 'Melanesia': 6, + 'MiddleAfrica': 6, + 'NorthernAfrica': 6, + 'NorthernEurope': 6, + 'SouthEasternAsia': 6, + 'SouthernAfrica': 6, + 'SouthernAsia': 6, + 'SouthernEurope': 6, + 'SubSaharanAfrica': 6, + 'WesternAfrica': 6, + 'WesternAsia': 6, + 'WesternEurope': 6, + # Americas + 'undata-geo/G00134000': 6, +} + + +def get_countries_in(dcids): + resp = requests.post('https://autopush.api.datacommons.org/v2/node', + headers={ + 'X-API-Key': os.environ['MIXER_API_KEY'] + }, + json={ + 'nodes': dcids, + 'property': "<-containedInPlace+{typeOf:Country}" + }).json() + node2children = {} + for place, d in resp.get('data', {}).items(): + node2children[place] = [] + for n in d.get('arcs', {}).get('containedInPlace+', + {}).get('nodes', []): + node2children[place].append(n['dcid']) + return node2children + + +# +# Code from @chejennifer. +# +def get_multipolygon_geojson_coordinates(geojson): + """ + Gets geojson coordinates in the form of multipolygon geojson coordinates that + are in the reverse of the righthand_rule. + + GeoJSON is stored in DataCommons following the right hand rule as per rfc + spec (https://www.rfc-editor.org/rfc/rfc7946). However, d3 requires geoJSON + that violates the right hand rule (see explanation on d3 winding order here: + https://stackoverflow.com/a/49311635). This function returns coordinates in + the format expected by D3 and turns all polygons into multipolygons for + downstream consistency. + Args: + geojson: geojson of type MultiPolygon or Polygon + Returns: + Nested list of geo coordinates. + """ + # The geojson data for each place varies in whether it follows the + # righthand rule or not. We want to ensure geojsons for all places + # does follow the righthand rule. + right_handed_geojson = rewind(geojson) + geojson_type = right_handed_geojson['type'] + geojson_coords = right_handed_geojson['coordinates'] + if geojson_type == POLYGON_GEOJSON_TYPE: + geojson_coords[0].reverse() + return [geojson_coords] + elif geojson_type == MULTIPOLYGON_GEOJSON_TYPE: + for polygon in geojson_coords: + polygon[0].reverse() + return geojson_coords + else: + assert False, f"Type {geojson_type} unknown!" + + +def get_geojson_feature(geo_id: str, geo_name: str, geojson: Dict): + """ + Gets a single geojson feature from a list of json strings + """ + # Exclude geo if no renderings are present. + geo_feature = { + "type": "Feature", + "id": geo_id, + "properties": { + "name": geo_name, + "geoDcid": geo_id, + } + } + geojson_type = geojson.get("type", "") + if geojson_type == MULTILINE_GEOJSON_TYPE: + geo_feature['geometry'] = geojson + elif geojson_type == POLYGON_GEOJSON_TYPE or geojson_type == MULTIPOLYGON_GEOJSON_TYPE: + coordinates = get_multipolygon_geojson_coordinates(geojson) + geo_feature['geometry'] = { + "type": "MultiPolygon", + "coordinates": coordinates + } + else: + assert False, geojson_type + geo_feature = None + return geo_feature + + +class CountryBoundariesGenerator: + """Generates MCF files with simplified json for the WB boundaries dataset.""" + + def __init__(self, input_file, output_dir): + self.input_file = input_file + self.output_dir = output_dir + for d in ['tmp', 'mcf', 'cache']: + os.makedirs(os.path.join(self.output_dir, d), exist_ok=True) + + def load_data(self): + with open(self.input_file) as fp: + gj = json.load(fp) + with open(os.path.join(self.output_dir, 'input_formatted.json'), + 'w') as ofp: + json.dump(gj, ofp, indent=1) + return gpd.read_file(self.input_file) + + def existing_codes(self, all_countries): + """Builds mapping of column code to country codes to import. + + Only countries with DCID of the form county/{code} are included. + """ + # Call DC API to get list of countries + dc_all_countries = dc.get_property_values(['Country'], + 'typeOf', + out=False, + limit=500)['Country'] + dc_all_countries = set(dc_all_countries) + + def is_dc_country(iso): + dcid = f'country/{iso}' + return dcid in dc_all_countries + + # Compare dataset countries with results from DC + idx = all_countries['iso3cd'].apply(is_dc_country) + return sorted(all_countries.loc[idx]['iso3cd']) + + def _geojson_tmpfile(self, country_code, dp_level): + """Returns filename of the geojson output file.""" + return os.path.join(self.output_dir, 'tmp', + f'{country_code}_{dp_level}.geojson') + + def _geojson(self, country_code, dp_level): + fname = self._geojson_tmpfile(country_code, dp_level) + with open(fname) as fp: + return json.load(fp) + + def _export_country_feature(self, country_code, country_data, dp_level): + geojson = json.loads(country_data.to_json()) + features = geojson.get('features', []) + assert (len(features) == 1) + geometry = features[0].get('geometry') + fname = self._geojson_tmpfile(country_code, dp_level) + with open(fname, 'w') as f: + json.dump(geometry, f, indent=2) + + def _simplify_json(self, country_code, country_data): + """Simplifies (and exports) a geojson.""" + for tolerance, dp_level in EPS_LEVEL_MAP.items(): + if dp_level == 0: + export_data = country_data + else: + export_data = country_data.simplify(tolerance) + self._export_country_feature(country_code, export_data, dp_level) + + def extract_country_geojson(self, all_countries_df, existing_codes): + """Extract and export all geojson to tempfiles.""" + + print(f'Exporting geojson to {self.output_dir}') + col = 'iso3cd' + for country_code in existing_codes: + country_data = all_countries_df[ + (all_countries_df[col] == country_code) & + (all_countries_df['geometry'].geom_type != 'LineString') & + (all_countries_df['geometry'].geom_type != 'MultiLineString')] + country_data = country_data.dissolve( + by=col) # Join multiple rows into a single shape + self._simplify_json(country_code, country_data) + + def build_cache(self, existing_codes): + parent2children = get_countries_in(list(PARENT_PLACES.keys())) + all_children = set() + for children in parent2children.values(): + all_children.update(children) + + child2name = {} + for child, values in dc.get_property_values(list(all_children), + 'name').items(): + if values: + child2name[child] = values[0] + + for parent, dp_level in PARENT_PLACES.items(): + if not parent2children.get(parent): + print(f'Missing children for {parent}') + continue + features = [] + for child in parent2children[parent]: + if not child.startswith('country/'): + print(f'{child} of parent {parent} is not a country!') + continue + code = child.replace('country/', '') + if code not in existing_codes: + print(f'Missing geojson for {child}') + continue + geo = self._geojson(code, dp_level) + feature = get_geojson_feature(child, child2name.get(child, ''), + geo) + if feature: + features.append(feature) + result = { + "type": "FeatureCollection", + "features": features, + "properties": { + "current_geo": "Earth" + } + } + fname = f'{parent.replace("/", "").lower()}_country_dp{dp_level}.json' + with open(os.path.join(self.output_dir, 'cache', fname), 'w') as fp: + json.dump(result, fp, indent=2) + + def output_mcf(self, existing_codes): + """Generates the output MCF files for all dp levels.""" + print(f'Generating MCF to {self.output_dir}') + + def prop_for_dp_level(dp_level): + if dp_level == 0: + return "geoJsonCoordinatesUN" + return f"geoJsonCoordinatesUNDP{dp_level}" + + for _, dp_level in EPS_LEVEL_MAP.items(): + mcf_path = MCF_PATH.format(MCF_OUT_FOLDER=self.output_dir, + dp_level=dp_level) + with open(mcf_path, 'w') as mcf_fp: + for country_code in existing_codes: + geostr = self._geojson(country_code, dp_level) + mcf_fp.write( + MCF_FORMAT_STR.format(country_code=country_code, + prop=prop_for_dp_level(dp_level), + coords_str=json.dumps( + json.dumps(geostr)))) + + +def main(_): + gen = CountryBoundariesGenerator(FLAGS.input_file, FLAGS.output_dir) + all_countries = gen.load_data() + existing_codes = gen.existing_codes(all_countries) + gen.extract_country_geojson(all_countries, existing_codes) + gen.build_cache(existing_codes) + gen.output_mcf(existing_codes) + + +if __name__ == '__main__': + app.run(main) diff --git a/scripts/un/boundaries/data/UNGIS_BNDA.geojson b/scripts/un/boundaries/data/UNGIS_BNDA.geojson new file mode 100644 index 0000000000..b84d2ba791 --- /dev/null +++ b/scripts/un/boundaries/data/UNGIS_BNDA.geojson @@ -0,0 +1,355 @@ +{ +"type": "FeatureCollection", +"name": "UNGIS_BNDA_", +"crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:OGC:1.3:CRS84" } }, +"features": [ +{ "type": "Feature", "properties": { "objectid_1": null, "objectid": 1, "iso3cd": "ABW", "m49_cd": "533", "bdytyp": null, "nam_en": "Aruba", "lbl_en": "Aruba (Neth.)", "georeg": "AME", "geo_cd": 19, "name": null, "sub_cd": 419, "int_cd": 29, "subreg": "Latin 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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +python3 -m venv .env +source .env/bin/activate +pip3 install -r requirements.txt -q +python3 country_boundaries.py diff --git a/scripts/un/sdg/.gitattributes b/scripts/un/sdg/.gitattributes new file mode 100644 index 0000000000..ba109e3e5d --- /dev/null +++ b/scripts/un/sdg/.gitattributes @@ -0,0 +1,3 @@ +csv/* filter=lfs diff=lfs merge=lfs -text +schema/* filter=lfs diff=lfs merge=lfs -text +dc_generated/* filter=lfs diff=lfs merge=lfs -text diff --git a/scripts/un/sdg/README.md b/scripts/un/sdg/README.md new file mode 100644 index 0000000000..0afb292ce5 --- /dev/null +++ b/scripts/un/sdg/README.md @@ -0,0 +1,31 @@ +# UN Stats Sustainable Development Goals + +This import includes country, city, and select region-level data from the [UN SDG Global Database](https://unstats.un.org/sdgs/dataportal). Data is read from the submodule `sdg-dataset` which is managed by UN Stats. + + +To generate city dcids: +``` +python3 cities.py +``` +(Note: many of these cities will require manual curation, so this script likely should not be rerun.) + +To process data and generate artifacts: +``` +python3 process.py +``` +Produces: +* schema/ folder: + * measurement_method.mcf + * schema.mcf (classes and enums) + * sdg.textproto (vertical spec) + * series.mcf (series mcf) + * sv.mcf + * unit.mcf +* csv/ folder: + * [CODE].csv +(Note that the `schema/` folder is not included in the repository but can be regenerated by running the script.) + +To run unit tests: +``` +python3 -m unittest discover -v -s ../ -p "*_test.py" +``` diff --git a/scripts/un/sdg/__init__.py b/scripts/un/sdg/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/scripts/un/sdg/cities.csv b/scripts/un/sdg/cities.csv new file mode 100644 index 0000000000..643571d9be --- /dev/null +++ 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+MONTENEGRO_ALL,country/MNE +GHORAI,wikidataId/Q1447290 +AMSTERDAM-UTRECHT,wikidataId/Q727 +MARSHALLISLANDS,country/MHL +LIMA_CARABAYLLO, +UCAYALI_CALLERIA,wikidataId/Q2486015 +LIMA_PUENTEPIEDRA,wikidataId/Q3303771 +LIMA_LURIGANCHO,wikidataId/Q2718534 +JUNIN_ELTAMBO,wikidataId/Q5352223 +LIMA_LOSOLIVOS,wikidataId/Q2100996 +LIMA_CHORRILLOS,wikidataId/Q2321093 +LIMA_SANJUANDELURIGANCHO,wikidataId/Q2501691 +LIMA_COMAS,wikidataId/Q1113426 +LIMA_ATE,wikidataId/Q3769630 +CALLAO_CALLAOCERCADO, +LIMA_SANBORJA,wikidataId/Q2566267 +LIMA_VILLAMARIADELTRIUNFO,wikidataId/Q2038962 +PIURA_CASTILLA,wikidataId/Q3826215 +LAHORE_PHILIPPINES, +LISBON,wikidataId/Q597 +ANGUILLA,geoId/2801500 +CASTRIES,wikidataId/Q41699 +CAPETOWN,wikidataId/Q1185115 +DURBAN,wikidataId/Q5468 +STEVE_TSHWETE,wikidataId/Q2292410 +HARARE,wikidataId/Q3921 +DAMASCUS,wikidataId/Q3766 +LOME,wikidataId/Q3792 +SOUSSE, +NORTH_MACEDONIA_ALL, +MOSHI,wikidataId/Q271733 +DARESSALAAM,wikidataId/Q1960 +TOMPKINS_COUNTY,geoId/36109 +SANFRANSCISCO,geoId/0667000 +LUSAKA,wikidataId/Q3881 +NORTHERN_GOVERNORATE,wikidataId/Q840445 +CAPITAL_GOVERNORATE,wikidataId/Q528953 +MUHARRAQ_GOVERNORATE,wikidataId/Q375630 +SOUTHERN_GOVERNORATE,wikidataId/Q838532 +FRANCISTOWN,wikidataId/Q165422 +INDAIATUBA_CORREGO, +PORTO_ALEGRE_AND_NOVO_HAMBURGO,wikidataId/Q40269 +BELEM_ANANINDEUA, +CAMPINAS_PAULINIA, +SUINING,wikidataId/Q426644 +YULIN,wikidataId/Q571918 +ARAUCA,wikidataId/Q626543 +VILLAVICENCIO,wikidataId/Q749224 +BABAHOYO,wikidataId/Q797568 +TOULOUSSE,wikidataId/Q7880 +CHOLOMA,wikidataId/Q998218 +ICELAND_ALL,wikidataId/Q1764 +BAREILLY,wikidataId/Q1797378 +PATI,wikidataId/Q10622 +SUBANG, +SAN_LUIS_RIO_COLORADO,wikidataId/Q995380 +SALTILLO,wikidataId/Q53077 +OCEANIA_EXCL_AUSTRALIA_AND_NEWZEALAND_ALL, +AL_KHOR,wikidataId/Q1156471 +HAIL,wikidataId/Q675568 +AT_TAIF,wikidataId/Q182640 +JIDDAH,wikidataId/Q374365 +KHAMIS_ABHA, +AD_DAMMAM,wikidataId/Q160320 +AL_HUFUF,wikidataId/Q27136 +AL_JUBAYL,wikidataId/Q27430 +AL_KHARJ,wikidataId/Q2162128 +ALFASHIR,wikidataId/Q311204 +WINTERHUR,wikidataId/Q9125 +AL_FUJAYRAH,wikidataId/Q4091 +RAS_AL_KHAIMAH, +HOUSTON,geoId/4835000 +CLEVELAND,geoId/3916000 +NAVOI_KARMANA, +BARCELONA_AND_PUERTO_LA_CRUZ,wikidataId/Q379509 diff --git a/scripts/un/sdg/cities.py b/scripts/un/sdg/cities.py new file mode 100644 index 0000000000..d9a7b13ad5 --- /dev/null +++ b/scripts/un/sdg/cities.py @@ -0,0 +1,79 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +'''Finds dcids for cities. + +Produces: +* cities.csv: dcid for each city code + +There are a few city codes that are still missing. +These can be manually filled in and verified. +**This script ideally shouldn't need to be run again.** + +Usage: python3 cities.py +''' +import csv +import requests +import pandas as pd +import sys + + +def get_cities(json, api_key): + '''Applies find entities API for given json. + + Args: + json: Input json. + api_key: API key. + + Returns: + API response. + ''' + return requests.post('https://api.datacommons.org/v1/bulk/find/entities', + headers={ + 'X-API-Key': api_key + }, + json=json).json() + + +def write_cities(file, cities, api_key): + '''Writes city codes and names to file. + + Args: + file: Output file path. + cities: Map of city names to codes. + api_key: API key. + ''' + with open(file, 'w') as f: + writer = csv.DictWriter(f, fieldnames=['name', 'dcid']) + writer.writeheader() + for city in list(cities.keys()): + json = {'entities': [{'description': city}]} + response = get_cities(json, api_key) + try: + for entity in response['entities']: + dcid = entity['dcids'][0] if 'dcids' in entity else '' + writer.writerow({ + 'name': cities[entity['description']], + 'dcid': dcid + }) + except KeyError: + writer.writerow({'name': cities[city], 'dcid': ''}) + + +if __name__ == '__main__': + df = pd.read_excel(f'sdg-dataset/output/SDG_cities_enumeration.xlsx') + cities = {} + for _, row in df.iterrows(): + cities[row['CITY_NAME'] + ', ' + row['GEO_AREA_NAME'].replace( + '_', ' ').title()] = row['CITY_CODE'] + write_cities('cities_test.csv', cities, sys.argv[1]) diff --git a/scripts/un/sdg/cities_test.py b/scripts/un/sdg/cities_test.py new file mode 100644 index 0000000000..aafee5f17e --- /dev/null +++ b/scripts/un/sdg/cities_test.py @@ -0,0 +1,58 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +'''Tests for cities.py. + +Usage: python3 -m unittest discover -v -s ../ -p "cities_test.py" +''' +import os +import sys +import tempfile +import unittest +from unittest import mock + +sys.path.append( + os.path.dirname(os.path.dirname(os.path.dirname( + os.path.abspath(__file__))))) +from un.sdg import cities + +module_dir_ = os.path.dirname(__file__) + +CITIES = { + 'Mazār-e Sharīf, Afghanistan': 'AF_MAZAR_E_SHARIF', +} +RESPONSE = { + 'entities': [{ + 'description': 'Mazār-e Sharīf, Afghanistan', + 'dcids': ['wikidataId/Q130469'] + }] +} + + +class CitiesTest(unittest.TestCase): + + def test_write_cities(self): + with tempfile.TemporaryDirectory() as tmp_dir: + cities.get_cities = mock.Mock(return_value=RESPONSE) + output = os.path.join(tmp_dir, 'output.csv') + cities.write_cities(output, CITIES, '') + with open(output) as result: + with open( + os.path.join( + module_dir_, + 'testdata/expected_cities.csv')) as expected: + self.assertEqual(result.read(), expected.read()) + + +if __name__ == '__main__': + unittest.main() diff --git a/scripts/un/sdg/m49.csv b/scripts/un/sdg/m49.csv new file mode 100644 index 0000000000..a90189880a --- /dev/null +++ b/scripts/un/sdg/m49.csv @@ -0,0 +1,250 @@ +Country or Area M49 code ISO-alpha3 code +Afghanistan 004 AFG +Åland Islands 248 ALA +Albania 008 ALB +Algeria 012 DZA +American Samoa 016 ASM +Andorra 020 AND +Angola 024 AGO +Anguilla 660 AIA +Antarctica 010 ATA +Antigua and Barbuda 028 ATG +Argentina 032 ARG +Armenia 051 ARM +Aruba 533 ABW +Australia 036 AUS +Austria 040 AUT +Azerbaijan 031 AZE +Bahamas 044 BHS +Bahrain 048 BHR +Bangladesh 050 BGD +Barbados 052 BRB +Belarus 112 BLR +Belgium 056 BEL +Belize 084 BLZ +Benin 204 BEN +Bermuda 060 BMU +Bhutan 064 BTN +Bolivia (Plurinational State of) 068 BOL +Bonaire, Sint Eustatius and Saba 535 BES +Bosnia and Herzegovina 070 BIH +Botswana 072 BWA +Bouvet Island 074 BVT +Brazil 076 BRA +British Indian Ocean Territory 086 IOT +British Virgin Islands 092 VGB +Brunei Darussalam 096 BRN +Bulgaria 100 BGR +Burkina Faso 854 BFA +Burundi 108 BDI +Cabo Verde 132 CPV +Cambodia 116 KHM +Cameroon 120 CMR +Canada 124 CAN +Cayman Islands 136 CYM +Central African Republic 140 CAF +Chad 148 TCD +Chile 152 CHL +China 156 CHN +China, Hong Kong Special Administrative Region 344 HKG +China, Macao Special Administrative Region 446 MAC +Christmas Island 162 CXR +Cocos (Keeling) Islands 166 CCK +Colombia 170 COL +Comoros 174 COM +Congo 178 COG +Cook Islands 184 COK +Costa Rica 188 CRI +Côte d’Ivoire 384 CIV +Croatia 191 HRV +Cuba 192 CUB +Curaçao 531 CUW +Cyprus 196 CYP +Czechia 203 CZE +Democratic People's Republic of Korea 408 PRK +Democratic Republic of the Congo 180 COD +Denmark 208 DNK +Djibouti 262 DJI +Dominica 212 DMA +Dominican Republic 214 DOM +Ecuador 218 ECU +Egypt 818 EGY +El Salvador 222 SLV +Equatorial Guinea 226 GNQ +Eritrea 232 ERI +Estonia 233 EST +Eswatini 748 SWZ +Ethiopia 231 ETH +Falkland Islands (Malvinas) 238 FLK +Faroe Islands 234 FRO +Fiji 242 FJI +Finland 246 FIN +France 250 FRA +French Guiana 254 GUF +French Polynesia 258 PYF +French Southern Territories 260 ATF +Gabon 266 GAB +Gambia 270 GMB +Georgia 268 GEO +Germany 276 DEU +Ghana 288 GHA +Gibraltar 292 GIB +Greece 300 GRC +Greenland 304 GRL +Grenada 308 GRD +Guadeloupe 312 GLP +Guam 316 GUM +Guatemala 320 GTM +Guernsey 831 GGY +Guinea 324 GIN +Guinea-Bissau 624 GNB +Guyana 328 GUY +Haiti 332 HTI +Heard Island and McDonald Islands 334 HMD +Holy See 336 VAT +Honduras 340 HND +Hungary 348 HUN +Iceland 352 ISL +India 356 IND +Indonesia 360 IDN +Iran (Islamic Republic of) 364 IRN +Iraq 368 IRQ +Ireland 372 IRL +Isle of Man 833 IMN +Israel 376 ISR +Italy 380 ITA +Jamaica 388 JAM +Japan 392 JPN +Jersey 832 JEY +Jordan 400 JOR +Kazakhstan 398 KAZ +Kenya 404 KEN +Kiribati 296 KIR +Kuwait 414 KWT +Kyrgyzstan 417 KGZ +Lao People's Democratic Republic 418 LAO +Latvia 428 LVA +Lebanon 422 LBN +Lesotho 426 LSO +Liberia 430 LBR +Libya 434 LBY +Liechtenstein 438 LIE +Lithuania 440 LTU +Luxembourg 442 LUX +Madagascar 450 MDG +Malawi 454 MWI +Malaysia 458 MYS +Maldives 462 MDV +Mali 466 MLI +Malta 470 MLT +Marshall Islands 584 MHL +Martinique 474 MTQ +Mauritania 478 MRT +Mauritius 480 MUS +Mayotte 175 MYT +Mexico 484 MEX +Micronesia (Federated States of) 583 FSM +Monaco 492 MCO +Mongolia 496 MNG +Montenegro 499 MNE +Montserrat 500 MSR +Morocco 504 MAR +Mozambique 508 MOZ +Myanmar 104 MMR +Namibia 516 NAM +Nauru 520 NRU +Nepal 524 NPL +Netherlands 528 NLD +New Caledonia 540 NCL +New Zealand 554 NZL +Nicaragua 558 NIC +Niger 562 NER +Nigeria 566 NGA +Niue 570 NIU +Norfolk Island 574 NFK +North Macedonia 807 MKD +Northern Mariana Islands 580 MNP +Norway 578 NOR +Oman 512 OMN +Pakistan 586 PAK +Palau 585 PLW +Panama 591 PAN +Papua New Guinea 598 PNG +Paraguay 600 PRY +Peru 604 PER +Philippines 608 PHL +Pitcairn 612 PCN +Poland 616 POL +Portugal 620 PRT +Puerto Rico 630 PRI +Qatar 634 QAT +Republic of Korea 410 KOR +Republic of Moldova 498 MDA +Réunion 638 REU +Romania 642 ROU +Russian Federation 643 RUS +Rwanda 646 RWA +Saint Barthélemy 652 BLM +Saint Helena 654 SHN +Saint Kitts and Nevis 659 KNA +Saint Lucia 662 LCA +Saint Martin (French Part) 663 MAF +Saint Pierre and Miquelon 666 SPM +Saint Vincent and the Grenadines 670 VCT +Samoa 882 WSM +San Marino 674 SMR +Sao Tome and Principe 678 STP +Sark 680 +Saudi Arabia 682 SAU +Senegal 686 SEN +Serbia 688 SRB +Seychelles 690 SYC +Sierra Leone 694 SLE +Singapore 702 SGP +Sint Maarten (Dutch part) 534 SXM +Slovakia 703 SVK +Slovenia 705 SVN +Solomon Islands 090 SLB +Somalia 706 SOM +South Africa 710 ZAF +South Georgia and the South Sandwich Islands 239 SGS +South Sudan 728 SSD +Spain 724 ESP +Sri Lanka 144 LKA +State of Palestine 275 PSE +Sudan 729 SDN +Suriname 740 SUR +Svalbard and Jan Mayen Islands 744 SJM +Sweden 752 SWE +Switzerland 756 CHE +Syrian Arab Republic 760 SYR +Tajikistan 762 TJK +Thailand 764 THA +Timor-Leste 626 TLS +Togo 768 TGO +Tokelau 772 TKL +Tonga 776 TON +Trinidad and Tobago 780 TTO +Tunisia 788 TUN +Türkiye 792 TUR +Turkmenistan 795 TKM +Turks and Caicos Islands 796 TCA +Tuvalu 798 TUV +Uganda 800 UGA +Ukraine 804 UKR +United Arab Emirates 784 ARE +United Kingdom of Great Britain and Northern Ireland 826 GBR +United Republic of Tanzania 834 TZA +United States Minor Outlying Islands 581 UMI +United States of America 840 USA +United States Virgin Islands 850 VIR +Uruguay 858 URY +Uzbekistan 860 UZB +Vanuatu 548 VUT +Venezuela (Bolivarian Republic of) 862 VEN +Viet Nam 704 VNM +Wallis and Futuna Islands 876 WLF +Western Sahara 732 ESH +Yemen 887 YEM +Zambia 894 ZMB +Zimbabwe 716 ZWE diff --git a/scripts/un/sdg/process.py b/scripts/un/sdg/process.py new file mode 100644 index 0000000000..676936392c --- /dev/null +++ b/scripts/un/sdg/process.py @@ -0,0 +1,340 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +'''Generates mcf and csv/tmcf for sdg-dataset data. + +Produces: +* schema/ folder: + * measurement_method.mcf + * schema.mcf (classes and enums) + * sdg.textproto (vertical spec) + * series.mcf (series mcf) + * sv.mcf + * unit.mcf +* csv/ folder: + * [CODE].csv + +Usage: python3 process.py +''' +import collections +import os +import pandas as pd +import shutil +import sys + +sys.path.append( + os.path.dirname(os.path.dirname(os.path.dirname( + os.path.abspath(__file__))))) +from un.sdg import util + + +def get_geography(code, type): + '''Returns dcid of geography. + + Args: + code: Geography code. + type: Geography type. + + Returns: + Geography dcid. + ''' + + # Currently only support Country, City, and select Regions . + if code in util.REGIONS: + return 'dcs:' + util.REGIONS[code] + elif type == 'Country' and code in util.PLACES: + return 'dcs:country/' + util.PLACES[code] + elif type == 'City': + # Remove country prefix for now. + city = '_'.join(code.split('_')[1:]) + if city in util.CITIES and util.CITIES[city]: + return 'dcs:' + util.CITIES[city] + return '' + + +def get_unit(units, base_period): + '''Returns dcid of unit. + + Args: + unit: Unit. + base_period: Base period of unit. + + Returns: + Unit dcid. + ''' + if util.is_valid(base_period): + return f'[{units} {base_period}]' + return 'dcs:SDG_' + units + + +def get_measurement_method(row): + '''Returns dcid of measurement method. + + Args: + row: Input DataFrame row. + + Returns: + Measurement method dcid. + ''' + mmethod = '' + if util.is_valid(row['NATURE']): + mmethod += '_' + str(row['NATURE']) + if util.is_valid(row['OBS_STATUS']): + mmethod += '_' + str(row['OBS_STATUS']) + if util.is_valid(row['REPORTING_TYPE']): + mmethod += '_' + str(row['REPORTING_TYPE']) + return 'SDG' + mmethod + + +def process(input_dir, schema_dir, csv_dir): + '''Generates mcf, csv/tmcf artifacts. + + Produces: + * schema/ folder: + * measurement_method.mcf + * schema.mcf (classes and enums) + * sdg.textproto (vertical spec) + * series.mcf (series mcf) + * sv.mcf + * unit.mcf + * csv/ folder: + * [CODE].csv + + Args: + input_dir: Path to input xlsx files. + schema_dir: Path to output schema files. + csv_dir: Path to output csv files. + ''' + with open(os.path.join(schema_dir, 'series.mcf'), 'w') as f_series: + with open(os.path.join(schema_dir, 'sdg.textproto'), 'w') as f_vertical: + df = pd.read_csv(os.path.join(input_dir, 'SDG_hierarchy.csv')) + descriptions = {} + for _, row in df.iterrows(): + if not util.is_valid(row['SeriesCode']): + continue + descriptions[str(row['SeriesCode'])] = util.format_description( + row['SeriesDescription']) + f_vertical.write('spec: {\n' + ' pop_type: "SDG_' + str(row['SeriesCode']) + + '"\n' + ' obs_props { mprop: "value" }\n' + ' vertical: "SDG_' + + str(row['IndicatorRefCode']) + '"\n' + '}\n') + for code in sorted(descriptions): + f_series.write( + util.SERIES_TEMPLATE.format_map({ + 'dcid': 'SDG_' + code, + 'description': descriptions[code] + })) + + # Process dimensions. + dimensions = collections.defaultdict(dict) + df = pd.read_csv(os.path.join(input_dir, 'SDG_enumerations.csv')) + + # Replace buggy input text. + df = df.replace('CIT_ OF_WROCLAW', 'CITY_OF_WROCLAW') + + for _, row in df.iterrows(): + if str(row['Enumeration_Code_SDMX']) != 'CUST_BREAKDOWN' and str( + row['Enumeration_Code_SDMX']) != 'COMPOSITE_BREAKDOWN': + dimensions[str(row['Enumeration_Code_SDMX'])][str( + row['EnumerationValue_Code_SDMX'])] = str( + row['EnumerationValue_Name']) + else: + dimensions[str(row['Enumeration_Code2'])][str( + row['EnumerationValue_Code2'])] = str( + row['EnumerationValue_Name']) + + sv_frames = [] + measurement_method_frames = [] + units = set() + for root, _, files in os.walk(os.path.join(input_dir, 'observations')): + for file in sorted(files): + print(file) + df = pd.read_csv(os.path.join(root, file)) + if df.empty: + continue + + properties = list( + filter(lambda x: x not in util.BASE_DIMENSIONS, df.columns)) + + # Drop rows with nan. + df = df.dropna(subset=[ + 'VARIABLE_CODE', 'GEOGRAPHY_CODE', 'TIME_PERIOD', 'OBS_VALUE' + ]) + if df.empty: + continue + + # Drop invalid values. + df['OBS_VALUE'] = df['OBS_VALUE'].apply(lambda x: x + if util.is_float(x) else '') + df = df[df['OBS_VALUE'] != ''] + if df.empty: + continue + + # Format places. + df['GEOGRAPHY_CODE'] = df.apply(lambda x: get_geography( + x['GEOGRAPHY_CODE'], x['GEOGRAPHY_TYPE']), + axis=1) + df = df[df['GEOGRAPHY_CODE'] != ''] + if df.empty: + continue + + # Special curation of names. + df['VARIABLE_DESCRIPTION'] = df.apply( + lambda x: util.format_variable_description( + x['VARIABLE_DESCRIPTION'], x['SERIES_DESCRIPTION']), + axis=1) + df['VARIABLE_CODE'] = df['VARIABLE_CODE'].apply( + lambda x: util.format_variable_code(x)) + + # Replace buggy input text. + df = df.replace( + 'SG_SCP_PROCN_LS.LEVEL_STATUS--DEG_MLOW__GOVERNMENT_NAME--CIT_OF_WROCLAW', + 'SG_SCP_PROCN_LS.LEVEL_STATUS--DEG_MLOW__GOVERNMENT_NAME--CITY_OF_WROCLAW' + ) + + sv_frames.append(df.loc[:, + ['VARIABLE_CODE', 'VARIABLE_DESCRIPTION'] + + properties].drop_duplicates()) + measurement_method_frames.append( + df.loc[:, ['NATURE', 'OBS_STATUS', 'REPORTING_TYPE']]. + drop_duplicates()) + units.update(set(df['UNIT_MEASURE'].unique())) + + df['VARIABLE_CODE'] = df['VARIABLE_CODE'].apply( + lambda x: 'dcs:sdg/' + x) + df['UNIT_MEASURE'] = df.apply( + lambda x: get_unit(x['UNIT_MEASURE'], x['BASE_PERIOD']), axis=1) + df['MEASUREMENT_METHOD'] = df.apply( + lambda x: 'dcs:' + get_measurement_method(x), axis=1) + + # Retain only columns for cleaned csv. + df = df.loc[:, [ + 'VARIABLE_CODE', 'GEOGRAPHY_CODE', 'TIME_PERIOD', 'OBS_VALUE', + 'UNIT_MEASURE', 'UNIT_MULT', 'MEASUREMENT_METHOD' + ]] + + df.to_csv(os.path.join(csv_dir, + file.split('observations_')[1]), + index=False) + + with open(os.path.join(schema_dir, 'sv.mcf'), 'w') as f: + for df in sv_frames: + for _, row in df.iterrows(): + cprops = '' + for dimension in sorted(df.columns[2:]): + # Skip totals. + if row[dimension] == util.TOTAL: + continue + + # Remove leading _. + val = str(row[dimension]) + if val[0] == '_': + val = val[1:] + + # Remove buggy input text. + val = val.replace('CIT_ OF_WROCLAW', 'CITY_OF_WROCLAW') + + enum = util.format_property(dimension) + if dimension in util.MAPPED_DIMENSIONS: + prop = util.MAPPED_DIMENSIONS[dimension] + else: + prop = 'sdg_' + enum[0].lower() + enum[1:] + + val = 'SDG_' + enum + 'Enum_' + val + cprops += f'\n{prop}: dcs:{val}' + f.write( + util.SV_TEMPLATE.format_map({ + 'dcid': + 'sdg/' + row['VARIABLE_CODE'], + 'popType': + 'SDG_' + row['VARIABLE_CODE'].split( + util.SV_CODE_SEPARATOR)[0], + 'name': + '"' + row['VARIABLE_DESCRIPTION'] + '"', + 'cprops': + cprops, + })) + + with open(os.path.join(schema_dir, 'schema.mcf'), 'w') as f: + for d in sorted(dimensions): + if d in util.BASE_DIMENSIONS or d == 'GEOGRAPHY': + continue + prop = util.format_property(d) + enum = prop + 'Enum' + if d not in util.MAPPED_DIMENSIONS: + f.write( + util.PROPERTY_TEMPLATE.format_map({ + 'dcid': prop[0].lower() + prop[1:], + 'name': util.format_title(d), + 'enum': enum + })) + f.write(util.ENUM_TEMPLATE.format_map({'enum': enum})) + for k in sorted(dimensions[d]): + + # Skip totals. + if k == util.TOTAL: + continue + + v = dimensions[d][k] + + # Remove leading _. + if k[0] == '_': + k = k[1:] + + f.write( + util.VALUE_TEMPLATE.format_map({ + 'dcid': k, + 'enum': enum, + 'name': v, + })) + + with open(os.path.join(schema_dir, 'measurement_method.mcf'), 'w') as f: + df = pd.concat(measurement_method_frames).drop_duplicates() + for _, row in df.iterrows(): + dcid = get_measurement_method(row) + if not dcid: + continue + description = 'SDG Measurement Method: [' + pvs = [] + for dimension in sorted(df.columns): + if not util.is_valid(row[dimension]): + continue + pvs.append( + util.format_title(dimension) + ' = ' + + dimensions[dimension][row[dimension]]) + f.write( + util.MMETHOD_TEMPLATE.format_map({ + 'dcid': dcid, + 'description': description + ' | '.join(pvs) + ']' + })) + + with open(os.path.join(schema_dir, 'unit.mcf'), 'w') as f: + for unit in sorted(units): + f.write( + util.UNIT_TEMPLATE.format_map({ + 'dcid': 'SDG_' + unit, + 'name': dimensions['UNIT_MEASURE'][unit] + })) + + +if __name__ == '__main__': + if os.path.exists('schema'): + shutil.rmtree('schema') + os.makedirs('schema') + if os.path.exists('csv'): + shutil.rmtree('csv') + os.makedirs('csv') + process('sdg-dataset/output', 'schema', 'csv') diff --git a/scripts/un/sdg/process_test.py b/scripts/un/sdg/process_test.py new file mode 100644 index 0000000000..e8117b5c93 --- /dev/null +++ b/scripts/un/sdg/process_test.py @@ -0,0 +1,74 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +'''Tests for util.py. + +Usage: python3 -m unittest discover -v -s ../ -p "process_test.py" +''' +import os +import pandas as pd +import sys +import tempfile +import unittest + +sys.path.append( + os.path.dirname(os.path.dirname(os.path.dirname( + os.path.abspath(__file__))))) +from un.sdg import process + +module_dir_ = os.path.dirname(__file__) + + +def assert_equal_dir(self, result_dir, expected_dir): + for root, _, files in os.walk(result_dir): + for file in sorted(files): + with open(os.path.join(root, file)) as result: + with open(os.path.join(expected_dir, file)) as expected: + self.assertEqual(result.read(), expected.read()) + + +class ProcessTest(unittest.TestCase): + + def test_get_geography(self): + self.assertEqual(process.get_geography(840, 'Country'), + 'dcs:country/USA') + self.assertEqual(process.get_geography('AF_MAZAR_E_SHARIF', 'City'), + 'dcs:wikidataId/Q130469') + self.assertEqual(process.get_geography(1, 'Region'), 'dcs:Earth') + + def test_get_unit(self): + self.assertEqual(process.get_unit('CON_USD', 2021), '[CON_USD 2021]') + self.assertEqual(process.get_unit('CON_USD', float('nan')), + 'dcs:SDG_CON_USD') + + def test_get_measurement_method(self): + d = {'NATURE': ['E'], 'OBS_STATUS': ['A'], 'REPORTING_TYPE': ['G']} + df = pd.DataFrame.from_dict(d) + for _, row in df.iterrows(): + self.assertEqual(process.get_measurement_method(row), 'SDG_E_A_G') + + def test_process(self): + with tempfile.TemporaryDirectory() as tmp_schema: + with tempfile.TemporaryDirectory() as tmp_csv: + process.process( + os.path.join(module_dir_, 'testdata/test_input'), + tmp_schema, tmp_csv) + assert_equal_dir( + self, tmp_schema, + os.path.join(module_dir_, 'testdata/test_schema')) + assert_equal_dir(self, tmp_csv, + os.path.join(module_dir_, 'testdata/test_csv')) + + +if __name__ == '__main__': + unittest.main() diff --git a/scripts/un/sdg/sdg-dataset b/scripts/un/sdg/sdg-dataset new file mode 160000 index 0000000000..410719252c --- /dev/null +++ b/scripts/un/sdg/sdg-dataset @@ -0,0 +1 @@ +Subproject commit 410719252cbd6e75f91834d5788d4e19c210abbe diff --git a/scripts/un/sdg/sdg.tmcf b/scripts/un/sdg/sdg.tmcf new file mode 100644 index 0000000000..7c88718261 --- /dev/null +++ b/scripts/un/sdg/sdg.tmcf @@ -0,0 +1,9 @@ +Node: E:SDG->E0 +typeOf: dcs:StatVarObservation +variableMeasured: C:SDG->VARIABLE_CODE +observationAbout: C:SDG->GEOGRAPHY_CODE +observationDate: C:SDG->TIME_PERIOD +value: C:SDG->OBS_VALUE +unit: C:SDG->UNIT_MEASURE +scalingFactor: C:SDG->UNIT_MULT +measurementMethod: C:SDG->MEASUREMENT_METHOD diff --git a/scripts/un/sdg/testdata/__init__.py b/scripts/un/sdg/testdata/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/scripts/un/sdg/testdata/expected_cities.csv b/scripts/un/sdg/testdata/expected_cities.csv new file mode 100644 index 0000000000..3b4ac4931e --- /dev/null +++ b/scripts/un/sdg/testdata/expected_cities.csv @@ -0,0 +1,2 @@ +name,dcid +AF_MAZAR_E_SHARIF,wikidataId/Q130469 diff --git a/scripts/un/sdg/testdata/test_csv/AG_FOOD_WST.csv b/scripts/un/sdg/testdata/test_csv/AG_FOOD_WST.csv new file mode 100644 index 0000000000..baea70e159 --- /dev/null +++ b/scripts/un/sdg/testdata/test_csv/AG_FOOD_WST.csv @@ -0,0 +1,15 @@ +VARIABLE_CODE,GEOGRAPHY_CODE,TIME_PERIOD,OBS_VALUE,UNIT_MEASURE,UNIT_MULT,MEASUREMENT_METHOD +dcs:sdg/AG_FOOD_WST,dcs:Earth,2019,930863853.95716,dcs:SDG_T,,dcs:SDG_N_A_G +dcs:sdg/AG_FOOD_WST,dcs:africa,2019,200407208.7491,dcs:SDG_T,,dcs:SDG_N_A_G +dcs:sdg/AG_FOOD_WST,dcs:country/AFG,2019,4755917.64224,dcs:SDG_T,,dcs:SDG_E_A_G +dcs:sdg/AG_FOOD_WST,dcs:southamerica,2019,46603996.09298,dcs:SDG_T,,dcs:SDG_N_A_G +dcs:sdg/AG_FOOD_WST,dcs:country/ALB,2019,363201.04528,dcs:SDG_T,,dcs:SDG_E_A_G +dcs:sdg/AG_FOOD_WST,dcs:oceania,2019,5368899.62572,dcs:SDG_T,,dcs:SDG_N_A_G +dcs:sdg/AG_FOOD_WST,dcs:country/DZA,2019,5782224.32483,dcs:SDG_T,,dcs:SDG_E_A_G +dcs:sdg/AG_FOOD_WST.FOOD_WASTE_SECTOR--FWS_HHS,dcs:Earth,2019,569007855.9533,dcs:SDG_T,,dcs:SDG_N_A_G +dcs:sdg/AG_FOOD_WST.FOOD_WASTE_SECTOR--FWS_HHS,dcs:africa,2019,143927911.95641,dcs:SDG_T,,dcs:SDG_N_A_G +dcs:sdg/AG_FOOD_WST.FOOD_WASTE_SECTOR--FWS_HHS,dcs:country/AFG,2019,3109152.67104,dcs:SDG_T,,dcs:SDG_E_A_G +dcs:sdg/AG_FOOD_WST.FOOD_WASTE_SECTOR--FWS_HHS,dcs:southamerica,2019,28233968.89021,dcs:SDG_T,,dcs:SDG_N_A_G +dcs:sdg/AG_FOOD_WST.FOOD_WASTE_SECTOR--FWS_HHS,dcs:country/ALB,2019,238491.7727,dcs:SDG_T,,dcs:SDG_E_A_G +dcs:sdg/AG_FOOD_WST.FOOD_WASTE_SECTOR--FWS_HHS,dcs:oceania,2019,3926866.98184,dcs:SDG_T,,dcs:SDG_N_A_G +dcs:sdg/AG_FOOD_WST.FOOD_WASTE_SECTOR--FWS_HHS,dcs:country/DZA,2019,3918528.68,dcs:SDG_T,,dcs:SDG_E_A_G diff --git a/scripts/un/sdg/testdata/test_input/SDG_enumerations.csv b/scripts/un/sdg/testdata/test_input/SDG_enumerations.csv new file mode 100644 index 0000000000..70a527d87c --- /dev/null +++ b/scripts/un/sdg/testdata/test_input/SDG_enumerations.csv @@ -0,0 +1,11 @@ +Enumeration_Code,Enumeration_Code_SDMX,Enumeration_Code2,Enumeration_Name,isAttribute,EnumerationValue_Code,EnumerationValue_Code_SDMX,EnumerationValue_Code2,EnumerationValue_Name,EnumerationValue_Type +4,NATURE,NATURE,Nature,True,E,E,E,Estimated data,string +4,NATURE,NATURE,Nature,True,N,N,N,Non-relevant,string +8,UNIT_MEASURE,UNIT_MEASURE,Units,True,TONNES,T,T,Tonnes,string +30,REPORTING_TYPE,REPORTING_TYPE,Reporting Type,False,G,G,G,Global,string +33,OBS_STATUS,OBS_STATUS,Observation Status,True,A,A,A,Normal value,string +47,COMPOSITE_BREAKDOWN,FOOD_WASTE_SECTOR,Food Waste Sector,False,RTL,FWS_RTL,FWS_RTL,Retail,string +47,COMPOSITE_BREAKDOWN,FOOD_WASTE_SECTOR,Food Waste Sector,False,OOHC,FWS_OOHC,FWS_OOHC,Out-of-home consumption,string +47,COMPOSITE_BREAKDOWN,FOOD_WASTE_SECTOR,Food Waste Sector,False,HHS,FWS_HHS,FWS_HHS,Households,string +47,COMPOSITE_BREAKDOWN,FOOD_WASTE_SECTOR,Food Waste Sector,False,MNFC,FWS_MNFC,FWS_MNFC,Manufacturing,string +47,COMPOSITE_BREAKDOWN,FOOD_WASTE_SECTOR,Food Waste Sector,False,ALL,_T,_T,Total or no breakdown,string diff --git a/scripts/un/sdg/testdata/test_input/SDG_hierarchy.csv b/scripts/un/sdg/testdata/test_input/SDG_hierarchy.csv new file mode 100644 index 0000000000..0ebfb16808 --- /dev/null +++ b/scripts/un/sdg/testdata/test_input/SDG_hierarchy.csv @@ -0,0 +1,10 @@ +GoalCode,GoalDescription,TargetCode,TargetDescription,TI_IsActiveRelation,IndicatorRefCode,IndicatorDescription,IndicatorStatusID,TierID,IS_IsActiveRelation,SeriesCode,SeriesDescription,SeriesStatus,NumberDecimals,SuggestedOrder,IndicatorCode,isDSDSeries +1,End poverty in all its forms everywhere,1.1,"By 2030, eradicate extreme poverty for all people everywhere, currently measured as people living on less than $1.25 a day",True,1.1.1,"Proportion of the population living below the international poverty line by sex, age, employment status and geographic location (urban/rural)",1.0,1.0,True,SI_POV_DAY1,Proportion of population below international poverty line (%),O,1.0,C010101-1,C010101,True +1,End poverty in all its forms everywhere,1.1,"By 2030, eradicate extreme poverty for all people everywhere, currently measured as people living on less than $1.25 a day",True,1.1.1,"Proportion of the population living below the international poverty line by sex, age, employment status and geographic location (urban/rural)",1.0,1.0,True,SI_POV_EMP1,"Employed population below international poverty line, by sex and age (%)",O,1.0,C010101-2,C010101,True +1,End poverty in all its forms everywhere,1.2,"By 2030, reduce at least by half the proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions",True,1.2.1,"Proportion of population living below the national poverty line, by sex and age",1.0,1.0,True,SI_POV_NAHC,Proportion of population living below the national poverty line (%),O,1.0,C010201-1,C010201,True +1,End poverty in all its forms everywhere,1.2,"By 2030, reduce at least by half the proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions",True,1.2.2,"Proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions",1.0,2.0,True,SD_MDP_MUHC,Proportion of population living in multidimensional poverty (%),O,1.0,C010202-1,C010202,True +1,End poverty in all its forms everywhere,1.2,"By 2030, reduce at least by half the proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions",True,1.2.2,"Proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions",1.0,2.0,True,SD_MDP_ANDI,Average proportion of deprivations for people multidimensionally poor (%),O,1.0,C010202-2,C010202,True +1,End poverty in all its forms everywhere,1.2,"By 2030, reduce at least by half the proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions",True,1.2.2,"Proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions",1.0,2.0,True,SD_MDP_MUHHC,Proportion of households living in multidimensional poverty (%),O,1.0,C010202-3,C010202,True +1,End poverty in all its forms everywhere,1.2,"By 2030, reduce at least by half the proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions",True,1.2.2,"Proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions",1.0,2.0,True,SD_MDP_CSMP,Proportion of children living in child-specific multidimensional poverty (%),O,1.0,C010202-4,C010202,True +1,End poverty in all its forms everywhere,1.2,"By 2030, reduce at least by half the proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions",True,1.2.2,"Proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions",1.0,2.0,True,SD_MDP_ANDIHH,Average share of weighted deprivations of total households (intensity) (%),0,1.0,C010202-5,C010202,True +1,End poverty in all its forms everywhere,1.3,"Implement nationally appropriate social protection systems and measures for all, including floors, and by 2030 achieve substantial coverage of the poor and the vulnerable",True,1.3.1,"Proportion of population covered by social protection floors/systems, by sex, distinguishing children, unemployed persons, older persons, persons with disabilities, pregnant women, newborns, work-injury victims and the poor and the vulnerable",1.0,1.0,True,SI_COV_MATNL,[ILO] Proportion of mothers with newborns receiving maternity cash benefit (%),O,1.0,C010301-1,C010301,True diff --git a/scripts/un/sdg/testdata/test_input/observations/observations_AG_FOOD_WST.csv b/scripts/un/sdg/testdata/test_input/observations/observations_AG_FOOD_WST.csv new file mode 100644 index 0000000000..c4f88f2514 --- /dev/null +++ b/scripts/un/sdg/testdata/test_input/observations/observations_AG_FOOD_WST.csv @@ -0,0 +1,21 @@ +SERIES_CODE,SERIES_DESCRIPTION,VARIABLE_CODE,VARIABLE_DESCRIPTION,VARIABLE_ACTIVE_DIMS,GEOGRAPHY_CODE,GEOGRAPHY_NAME,GEOGRAPHY_TYPE,GEO_AREA_CODE,GEO_AREA_NAME,CITIES,SAMPLING_STATIONS,IS_LATEST_PERIOD,TIME_PERIOD,TIME_DETAIL,TIME_COVERAGE,FREQ,FOOD_WASTE_SECTOR,OBS_VALUE,VALUE_TYPE,UPPER_BOUND,LOWER_BOUND,UNIT_MEASURE,UNIT_MULT,BASE_PERIOD,NATURE,SOURCE,GEO_INFO_URL,FOOT_NOTE,REPORTING_TYPE,OBS_STATUS,RELEASE_STATUS,RELEASE_NAME +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST,Food waste (Tonnes),[],1,World,Region,1,World,,,True,2019,2019,,,_T,930863853.95716,Float,,,T,,,N,Food Waste Index Report 2021 / WESR,,,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST,Food waste (Tonnes),[],2,Africa,Region,2,Africa,,,True,2019,2019,,,_T,200407208.7491,Float,,,T,,,N,Food Waste Index Report 2021 / WESR,,,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST,Food waste (Tonnes),[],4,Afghanistan,Country,4,Afghanistan,,,True,2019,2019,,,_T,4755917.64224,Float,,,T,,,E,Food Waste Index Report 2021 / WESR,,Very Low Confidence,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST,Food waste (Tonnes),[],5,South America,Region,5,South America,,,True,2019,2019,,,_T,46603996.09298,Float,,,T,,,N,Food Waste Index Report 2021 / WESR,,,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST,Food waste (Tonnes),[],8,Albania,Country,8,Albania,,,True,2019,2019,,,_T,363201.04528,Float,,,T,,,E,Food Waste Index Report 2021 / WESR,,Very Low Confidence,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST,Food waste (Tonnes),[],9,Oceania,Region,9,Oceania,,,True,2019,2019,,,_T,5368899.62572,Float,,,T,,,N,Food Waste Index Report 2021 / WESR,,,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST,Food waste (Tonnes),[],11,Western Africa,Region,11,Western Africa,,,True,2019,2019,,,_T,73695078.26203,Float,,,T,,,N,Food Waste Index Report 2021 / WESR,,,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST,Food waste (Tonnes),[],12,Algeria,Country,12,Algeria,,,True,2019,2019,,,_T,5782224.32483,Float,,,T,,,E,Food Waste Index Report 2021 / WESR,,Very Low Confidence,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST,Food waste (Tonnes),[],13,Central America,Region,13,Central America,,,True,2019,2019,,,_T,23441006.87753,Float,,,T,,,N,Food Waste Index Report 2021 / WESR,,,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST,Food waste (Tonnes),[],14,Eastern Africa,Region,14,Eastern Africa,,,True,2019,2019,,,_T,62963781.41023,Float,,,T,,,N,Food Waste Index Report 2021 / WESR,,,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST@FOOD_WASTE_SECTOR--FWS_HHS,Food waste (Tonnes) [Food Waste Sector = Households],['FOOD_WASTE_SECTOR'],1,World,Region,1,World,,,True,2019,2019,,,FWS_HHS,569007855.9533,Float,,,T,,,N,Food Waste Index Report 2021 / WESR,,,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST@FOOD_WASTE_SECTOR--FWS_HHS,Food waste (Tonnes) [Food Waste Sector = Households],['FOOD_WASTE_SECTOR'],2,Africa,Region,2,Africa,,,True,2019,2019,,,FWS_HHS,143927911.95641,Float,,,T,,,N,Food Waste Index Report 2021 / WESR,,,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST@FOOD_WASTE_SECTOR--FWS_HHS,Food waste (Tonnes) [Food Waste Sector = Households],['FOOD_WASTE_SECTOR'],4,Afghanistan,Country,4,Afghanistan,,,True,2019,2019,,,FWS_HHS,3109152.67104,Float,,,T,,,E,Food Waste Index Report 2021 / WESR,,Very Low Confidence,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST@FOOD_WASTE_SECTOR--FWS_HHS,Food waste (Tonnes) [Food Waste Sector = Households],['FOOD_WASTE_SECTOR'],5,South America,Region,5,South America,,,True,2019,2019,,,FWS_HHS,28233968.89021,Float,,,T,,,N,Food Waste Index Report 2021 / WESR,,,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST@FOOD_WASTE_SECTOR--FWS_HHS,Food waste (Tonnes) [Food Waste Sector = Households],['FOOD_WASTE_SECTOR'],8,Albania,Country,8,Albania,,,True,2019,2019,,,FWS_HHS,238491.7727,Float,,,T,,,E,Food Waste Index Report 2021 / WESR,,Low Confidence,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST@FOOD_WASTE_SECTOR--FWS_HHS,Food waste (Tonnes) [Food Waste Sector = Households],['FOOD_WASTE_SECTOR'],9,Oceania,Region,9,Oceania,,,True,2019,2019,,,FWS_HHS,3926866.98184,Float,,,T,,,N,Food Waste Index Report 2021 / WESR,,,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST@FOOD_WASTE_SECTOR--FWS_HHS,Food waste (Tonnes) [Food Waste Sector = Households],['FOOD_WASTE_SECTOR'],11,Western Africa,Region,11,Western Africa,,,True,2019,2019,,,FWS_HHS,56750560.27358,Float,,,T,,,N,Food Waste Index Report 2021 / WESR,,,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST@FOOD_WASTE_SECTOR--FWS_HHS,Food waste (Tonnes) [Food Waste Sector = Households],['FOOD_WASTE_SECTOR'],12,Algeria,Country,12,Algeria,,,True,2019,2019,,,FWS_HHS,3918528.68,Float,,,T,,,E,Food Waste Index Report 2021 / WESR,,Very Low Confidence,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST@FOOD_WASTE_SECTOR--FWS_HHS,Food waste (Tonnes) [Food Waste Sector = Households],['FOOD_WASTE_SECTOR'],13,Central America,Region,13,Central America,,,True,2019,2019,,,FWS_HHS,15774419.58244,Float,,,T,,,N,Food Waste Index Report 2021 / WESR,,,G,A,Published,2023.Q2.G.01 +AG_FOOD_WST,Food waste (Tonnes),AG_FOOD_WST@FOOD_WASTE_SECTOR--FWS_HHS,Food waste (Tonnes) [Food Waste Sector = Households],['FOOD_WASTE_SECTOR'],14,Eastern Africa,Region,14,Eastern Africa,,,True,2019,2019,,,FWS_HHS,44299890.89842,Float,,,T,,,N,Food Waste Index Report 2021 / WESR,,,G,A,Published,2023.Q2.G.01 diff --git a/scripts/un/sdg/testdata/test_schema/measurement_method.mcf b/scripts/un/sdg/testdata/test_schema/measurement_method.mcf new file mode 100644 index 0000000000..ea653c6276 --- /dev/null +++ b/scripts/un/sdg/testdata/test_schema/measurement_method.mcf @@ -0,0 +1,10 @@ + +Node: dcid:SDG_N_A_G +typeOf: dcs:SDG_MeasurementMethodEnum +name: "SDG_N_A_G" +description: "SDG Measurement Method: [Nature = Non-relevant | Obs Status = Normal value | Reporting Type = Global]" + +Node: dcid:SDG_E_A_G +typeOf: dcs:SDG_MeasurementMethodEnum +name: "SDG_E_A_G" +description: "SDG Measurement Method: [Nature = Estimated data | Obs Status = Normal value | Reporting Type = Global]" diff --git a/scripts/un/sdg/testdata/test_schema/schema.mcf b/scripts/un/sdg/testdata/test_schema/schema.mcf new file mode 100644 index 0000000000..29d3743f89 --- /dev/null +++ b/scripts/un/sdg/testdata/test_schema/schema.mcf @@ -0,0 +1,33 @@ + +Node: dcid:sdg_foodWasteSector +typeOf: schema:Property +domainIncludes: dcs:Thing +rangeIncludes: dcs:SDG_FoodWasteSectorEnum +name: "Food Waste Sector" +isProvisional: dcs:True + +Node: dcid:SDG_FoodWasteSectorEnum +typeOf: schema:Class +subClassOf: schema:Enumeration +name: "FoodWasteSectorEnum" +isProvisional: dcs:True + +Node: dcid:SDG_FoodWasteSectorEnum_FWS_HHS +typeOf: dcs:SDG_FoodWasteSectorEnum +name: "Households" +isProvisional: dcs:True + +Node: dcid:SDG_FoodWasteSectorEnum_FWS_MNFC +typeOf: dcs:SDG_FoodWasteSectorEnum +name: "Manufacturing" +isProvisional: dcs:True + +Node: dcid:SDG_FoodWasteSectorEnum_FWS_OOHC +typeOf: dcs:SDG_FoodWasteSectorEnum +name: "Out-of-home consumption" +isProvisional: dcs:True + +Node: dcid:SDG_FoodWasteSectorEnum_FWS_RTL +typeOf: dcs:SDG_FoodWasteSectorEnum +name: "Retail" +isProvisional: dcs:True diff --git a/scripts/un/sdg/testdata/test_schema/sdg.textproto b/scripts/un/sdg/testdata/test_schema/sdg.textproto new file mode 100644 index 0000000000..b071d8c252 --- /dev/null +++ b/scripts/un/sdg/testdata/test_schema/sdg.textproto @@ -0,0 +1,45 @@ +spec: { + pop_type: "SDG_SI_POV_DAY1" + obs_props { mprop: "value" } + vertical: "SDG_1.1.1" +} +spec: { + pop_type: "SDG_SI_POV_EMP1" + obs_props { mprop: "value" } + vertical: "SDG_1.1.1" +} +spec: { + pop_type: "SDG_SI_POV_NAHC" + obs_props { mprop: "value" } + vertical: "SDG_1.2.1" +} +spec: { + pop_type: "SDG_SD_MDP_MUHC" + obs_props { mprop: "value" } + vertical: "SDG_1.2.2" +} +spec: { + pop_type: "SDG_SD_MDP_ANDI" + obs_props { mprop: "value" } + vertical: "SDG_1.2.2" +} +spec: { + pop_type: "SDG_SD_MDP_MUHHC" + obs_props { mprop: "value" } + vertical: "SDG_1.2.2" +} +spec: { + pop_type: "SDG_SD_MDP_CSMP" + obs_props { mprop: "value" } + vertical: "SDG_1.2.2" +} +spec: { + pop_type: "SDG_SD_MDP_ANDIHH" + obs_props { mprop: "value" } + vertical: "SDG_1.2.2" +} +spec: { + pop_type: "SDG_SI_COV_MATNL" + obs_props { mprop: "value" } + vertical: "SDG_1.3.1" +} diff --git a/scripts/un/sdg/testdata/test_schema/series.mcf b/scripts/un/sdg/testdata/test_schema/series.mcf new file mode 100644 index 0000000000..1d279ab42b --- /dev/null +++ b/scripts/un/sdg/testdata/test_schema/series.mcf @@ -0,0 +1,36 @@ + +Node: dcid:SDG_SD_MDP_ANDI +name: "Average proportion of deprivations for people multidimensionally poor" +typeOf: dcs:SDG_Series + +Node: dcid:SDG_SD_MDP_ANDIHH +name: "Average share of weighted deprivations of total households" +typeOf: dcs:SDG_Series + +Node: dcid:SDG_SD_MDP_CSMP +name: "Proportion of children living in child-specific multidimensional poverty" +typeOf: dcs:SDG_Series + +Node: dcid:SDG_SD_MDP_MUHC +name: "Proportion of population living in multidimensional poverty" +typeOf: dcs:SDG_Series + +Node: dcid:SDG_SD_MDP_MUHHC +name: "Proportion of households living in multidimensional poverty" +typeOf: dcs:SDG_Series + +Node: dcid:SDG_SI_COV_MATNL +name: "Proportion of mothers with newborns receiving maternity cash benefit" +typeOf: dcs:SDG_Series + +Node: dcid:SDG_SI_POV_DAY1 +name: "Proportion of population below international poverty line" +typeOf: dcs:SDG_Series + +Node: dcid:SDG_SI_POV_EMP1 +name: "Employed population below international poverty line" +typeOf: dcs:SDG_Series + +Node: dcid:SDG_SI_POV_NAHC +name: "Proportion of population living below the national poverty line" +typeOf: dcs:SDG_Series diff --git a/scripts/un/sdg/testdata/test_schema/sv.mcf b/scripts/un/sdg/testdata/test_schema/sv.mcf new file mode 100644 index 0000000000..3a11701a59 --- /dev/null +++ b/scripts/un/sdg/testdata/test_schema/sv.mcf @@ -0,0 +1,15 @@ + +Node: dcid:sdg/AG_FOOD_WST +typeOf: dcs:StatisticalVariable +measuredProperty: dcs:value +name: "Food waste" +populationType: dcs:SDG_AG_FOOD_WST +statType: dcs:measuredValue + +Node: dcid:sdg/AG_FOOD_WST.FOOD_WASTE_SECTOR--FWS_HHS +typeOf: dcs:StatisticalVariable +measuredProperty: dcs:value +name: "Food waste [Food Waste Sector = Households]" +populationType: dcs:SDG_AG_FOOD_WST +statType: dcs:measuredValue +sdg_foodWasteSector: dcs:SDG_FoodWasteSectorEnum_FWS_HHS diff --git a/scripts/un/sdg/testdata/test_schema/unit.mcf b/scripts/un/sdg/testdata/test_schema/unit.mcf new file mode 100644 index 0000000000..4547609251 --- /dev/null +++ b/scripts/un/sdg/testdata/test_schema/unit.mcf @@ -0,0 +1,4 @@ + +Node: dcid:SDG_T +typeOf: dcs:SDG_UnitOfMeasure +name: "Tonnes" diff --git a/scripts/un/sdg/util.py b/scripts/un/sdg/util.py new file mode 100644 index 0000000000..f3e35aa61b --- /dev/null +++ b/scripts/un/sdg/util.py @@ -0,0 +1,262 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +'''Shared util functions and constants.''' +import csv +import math +import os +import re +import sys + +module_dir_ = os.path.dirname(__file__) +sys.path.append(os.path.join(module_dir_)) + +# SDMX indicator for 'total' value in dimension. +TOTAL = '_T' + +# Used to split the series code from constraint properties in stat var dcids. +SV_CODE_SEPARATOR = '.' + +SERIES_TEMPLATE = ''' +Node: dcid:{dcid} +name: "{description}" +typeOf: dcs:SDG_Series +''' +PROPERTY_TEMPLATE = ''' +Node: dcid:sdg_{dcid} +typeOf: schema:Property +domainIncludes: dcs:Thing +rangeIncludes: dcs:SDG_{enum} +name: "{name}" +isProvisional: dcs:True +''' +ENUM_TEMPLATE = ''' +Node: dcid:SDG_{enum} +typeOf: schema:Class +subClassOf: schema:Enumeration +name: "{enum}" +isProvisional: dcs:True +''' +VALUE_TEMPLATE = ''' +Node: dcid:SDG_{enum}_{dcid} +typeOf: dcs:SDG_{enum} +name: "{name}" +isProvisional: dcs:True +''' +SV_TEMPLATE = ''' +Node: dcid:{dcid} +typeOf: dcs:StatisticalVariable +measuredProperty: dcs:value +name: {name} +populationType: dcs:{popType} +statType: dcs:measuredValue{cprops} +''' +MMETHOD_TEMPLATE = ''' +Node: dcid:{dcid} +typeOf: dcs:SDG_MeasurementMethodEnum +name: "{dcid}" +description: "{description}" +''' +UNIT_TEMPLATE = ''' +Node: dcid:{dcid} +typeOf: dcs:SDG_UnitOfMeasure +name: "{name}" +''' + +# Use existing properties. +# TODO: Also map enums to existing nodes. +MAPPED_DIMENSIONS = { + 'AGE': 'age', + 'CAUSE_OF_DEATH': 'causeOfDeath', + 'DISABILITY_STATUS': 'disabilityStatus', + 'EDUCATION_LEV': 'educationalAttainment', + 'SEX': 'gender' +} + +# Shared dimensions across all input csv files. +BASE_DIMENSIONS = { + 'SERIES_CODE', 'SERIES_DESCRIPTION', 'VARIABLE_CODE', + 'VARIABLE_DESCRIPTION', 'VARIABLE_ACTIVE_DIMS', 'GEOGRAPHY_CODE', + 'GEOGRAPHY_NAME', 'GEOGRAPHY_TYPE', 'GEO_AREA_CODE', 'GEO_AREA_NAME', + 'CITIES', 'SAMPLING_STATIONS', 'IS_LATEST_PERIOD', 'TIME_PERIOD', + 'TIME_DETAIL', 'TIME_COVERAGE', 'FREQ', 'OBS_VALUE', 'VALUE_TYPE', + 'UPPER_BOUND', 'LOWER_BOUND', 'UNIT_MEASURE', 'UNIT_MULT', 'BASE_PERIOD', + 'NATURE', 'SOURCE', 'GEO_INFO_URL', 'FOOT_NOTE', 'REPORTING_TYPE', + 'OBS_STATUS', 'RELEASE_STATUS', 'RELEASE_NAME' +} + +# Supported Regions. +# TODO: Add other regions. +REGIONS = { + 1: 'Earth', + 2: 'africa', + 5: 'southamerica', + 9: 'oceania', + 10: 'antarctica', + 21: 'northamerica', + 142: 'asia', + 150: 'europe', +} + + +def get_country_map(file): + ''' Creates map of M49 -> ISO-alpha3 for countries. + + Args: + file: Path to input file. + + Returns: + Country map. + ''' + with open(file) as f: + places = {} + reader = csv.DictReader(f, delimiter='\t') + for row in reader: + if not row['ISO-alpha3 code']: # Only countries for now. + continue + places[int(row['M49 code'])] = row['ISO-alpha3 code'] + return places + + +PLACES = get_country_map(os.path.join(module_dir_, 'm49.csv')) + + +def get_city_map(file): + ''' Creates map of name -> dcid for supported cities. + + Args: + file: Path to input file. + + Returns: + City map. + ''' + with open(file) as f: + reader = csv.DictReader(f) + return {row['name']: row['dcid'] for row in reader} + + +CITIES = get_city_map(os.path.join(module_dir_, 'cities.csv')) + + +def format_description(s): + '''Formats input with curated style. + + Args: + s: Input string. + + Returns: + Curated string. + ''' + # Remove <=2 levels of (). + formatted = re.sub('\((?:[^)(]|\([^)(]*\))*\)', '', s) + # Remove <=2 levels of []. + formatted = re.sub('\[(?:[^)(]|\[[^)(]*\])*\]', '', formatted) + # Remove attributes indicated with 'by'. + formatted = formatted.split(', by')[0] + # Remove references indicated by 'million USD'. + formatted = formatted.split(', million USD')[0] + # Remove extra spaces. + formatted = formatted.replace(' , ', ', ').replace(' ', ' ').strip() + # Remove trailing commas. + if formatted[-1] == ',': + formatted = formatted[:-1] + # Replace 100,000 with 100K. + formatted = formatted.replace('100,000', '100K') + # Make ascii. + return formatted.replace('Â', + '').replace('’', '\'').replace('₂', '2').replace( + '\xa0', ' ').replace('−', '-') + + +def is_float(element): + '''Checks if value can be interpreted as float. + + Args: + element: Input. + + Returns: + Whether the value can be cast as a float. + ''' + if element is None: + return False + try: + float(element) + return True + except ValueError: + return False + + +def is_valid(v): + '''Checks if value should be included in csv. + + Args: + v: Input. + + Returns: + Whether the value can be used. + ''' + try: + return not math.isnan(float(v)) + except ValueError: + return v and not v == 'nan' + + +def format_variable_description(variable, series): + '''Curates variable descriptions. + + Args: + variable: Full variable description. + series: Series portion of description. + + Returns: + Formatted description. + ''' + parts = variable.split(series) + return format_description(series) + parts[1] if len( + parts) > 1 else format_description(series) + + +def format_variable_code(code): + '''Curates variable codes with URL-safe encoding. + + Args: + code: Input code. + + Returns: + Formatted code. + ''' + return code.replace('@', SV_CODE_SEPARATOR).replace(' ', '') + + +def format_title(s): + '''Formats string as title. + + Args: + s: Input string. + + Returns: + Formatted string. + ''' + return s.replace('_', ' ').title() + + +def format_property(s): + '''Formats string as property. + + Args: + s: Input string. + + Returns: + Formatted string. + ''' + return format_title(s).replace(' ', '') diff --git a/scripts/un/sdg/util_test.py b/scripts/un/sdg/util_test.py new file mode 100644 index 0000000000..4ba3482fde --- /dev/null +++ b/scripts/un/sdg/util_test.py @@ -0,0 +1,67 @@ +# Copyright 2023 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +'''Tests for util.py. + +Usage: python3 -m unittest discover -v -s ../ -p "util_test.py" +''' +import os +import sys +import unittest + +sys.path.append( + os.path.dirname(os.path.dirname(os.path.dirname( + os.path.abspath(__file__))))) +from un.sdg import util + + +class UtilTest(unittest.TestCase): + + def test_format_description(self): + self.assertEqual( + util.format_description( + 'Indicator of Food Price Anomalies (IFPA), by Consumer Food Price Index' + ), 'Indicator of Food Price Anomalies') + + def test_is_float(self): + self.assertTrue(util.is_float(7.28)) + self.assertFalse(util.is_float('NA')) + + def test_is_valid(self): + self.assertFalse(util.is_valid(float('nan'))) + self.assertFalse(util.is_valid('')) + + def test_format_variable_description(self): + self.assertEqual( + util.format_variable_description( + 'Food waste (Tonnes) [Food Waste Sector = Households]', + 'Food waste (Tonnes)'), + 'Food waste [Food Waste Sector = Households]') + + def test_format_variable_code(self): + self.assertEqual( + util.format_variable_code( + 'AG_FOOD_WST@FOOD_WASTE_SECTOR--FWS_OOHC'), + 'AG_FOOD_WST.FOOD_WASTE_SECTOR--FWS_OOHC') + + def test_format_title(self): + self.assertEqual(util.format_title('FOOD_WASTE_SECTOR'), + 'Food Waste Sector') + + def test_format_property(self): + self.assertEqual(util.format_property('FOOD_WASTE_SECTOR'), + 'FoodWasteSector') + + +if __name__ == '__main__': + unittest.main() diff --git a/scripts/us_census/acs5yr/subject_tables/common/acs_spec_generator.py b/scripts/us_census/acs5yr/subject_tables/common/acs_spec_generator.py index 98af8c304b..d0793bfa1f 100644 --- a/scripts/us_census/acs5yr/subject_tables/common/acs_spec_generator.py +++ b/scripts/us_census/acs5yr/subject_tables/common/acs_spec_generator.py @@ -147,8 +147,9 @@ def create_combined_spec(all_specs: list, if enum_token not in out_spec['enumSpecializations']: out_spec['enumSpecializations'][enum_token] = cur_spec[ 'enumSpecializations'][enum_token] - elif out_spec['enumSpecializations'][enum_token] != cur_spec[ - 'enumSpecializations'][enum_token]: + elif out_spec['enumSpecializations'][ + enum_token] != cur_spec['enumSpecializations'][ + enum_token]: print('Error:', enum_token, 'already assigned to enumSpecialization', out_spec['enumSpecializations'][enum_token], diff --git a/scripts/us_census/api_utils/census_api_config_fetcher.py b/scripts/us_census/api_utils/census_api_config_fetcher.py index 08e398dfa8..0d14367047 100644 --- a/scripts/us_census/api_utils/census_api_config_fetcher.py +++ b/scripts/us_census/api_utils/census_api_config_fetcher.py @@ -163,9 +163,9 @@ def compile_year_map(store_path: str = CONFIG_PATH_, print('/'.join(cur_dataset_dict['c_dataset']), 'year not available and not timeseries') - if cur_dataset_dict['distribution'][ - 0]['accessURL'] != _generate_url_prefix( - link_tree, year)[:-1]: + if cur_dataset_dict['distribution'][0][ + 'accessURL'] != _generate_url_prefix(link_tree, + year)[:-1]: if 'url_mismatch' not in error_dict: error_dict['url_mismatch'] = [] error_dict['url_mismatch'].append({ @@ -176,8 +176,9 @@ def compile_year_map(store_path: str = CONFIG_PATH_, }) print(link_tree, 'accessURL unexpected') - if cur_dataset_dict['c_geographyLink'] != generate_url_geography( - link_tree, year): + if cur_dataset_dict[ + 'c_geographyLink'] != generate_url_geography( + link_tree, year): if 'url_mismatch' not in error_dict: error_dict['url_mismatch'] = [] error_dict['url_mismatch'].append({ @@ -196,8 +197,9 @@ def compile_year_map(store_path: str = CONFIG_PATH_, }) print(link_tree, 'c_groupsLink unexpected') - if cur_dataset_dict['c_variablesLink'] != generate_url_variables( - link_tree, year): + if cur_dataset_dict[ + 'c_variablesLink'] != generate_url_variables( + link_tree, year): if 'url_mismatch' not in error_dict: error_dict['url_mismatch'] = [] error_dict['url_mismatch'].append({ diff --git a/scripts/us_epa/superfund/site_and_funding_status/data/test_data/superfund_sites_expected.csv b/scripts/us_epa/superfund/site_and_funding_status/data/test_data/superfund_sites_expected.csv index 5ca19a79ce..5a92972e0c 100644 --- a/scripts/us_epa/superfund/site_and_funding_status/data/test_data/superfund_sites_expected.csv +++ b/scripts/us_epa/superfund/site_and_funding_status/data/test_data/superfund_sites_expected.csv @@ -1,2 +1,2 @@ "siteName","epaId","siteScore","regionCode","dcid","location","containedInPlace","establishmentOwnership" -"Mid-Atlantic Wood Preservers Inc.","MDD064882889",42.31,3,"epaSuperfundSiteId/MDD064882889","[latLong 39.163611 -76.698331]","zip/21077, geoId/2402, geoId/2400390008, geoId/24003751200, geoId/24003, geoId/24","PrivatelyOwned" +"Mid-Atlantic Wood Preservers Inc.","MDD064882889",42.31,3,"epaSuperfundSiteId/MDD064882889","[latLong 39.163611 -76.698331]","zip/21077, geoId/2402, geoId/2400390008, geoId/240037512003, geoId/24003751200, geoId/24003, geoId/24","PrivatelyOwned" diff --git a/scripts/us_usda/nass_census/README.md b/scripts/us_usda/nass_census/README.md new file mode 100644 index 0000000000..f0dc36d2e6 --- /dev/null +++ b/scripts/us_usda/nass_census/README.md @@ -0,0 +1,32 @@ +# US Census of Agriculture Import + +The Census of Agriculture, taken only once every five years, looks at land use and ownership, operator characteristics, production practices, income and expenditures. + +This import includes tables 1, 48-54 for the 2017 Census: + +* 1 - County Summary Highlights +* 48 - Hispanic, Latino, or Spanish Origin Producers +* 49 - American Indian or Alaska Native Producers +* 50 - Asian Producers +* 51 - Black or African American Producers +* 52 - Native Hawaiian or Other Pacific Islander Producers +* 53 - White Producers +* 54 - Producers Reporting More Than One Race + +Source: https://www.nass.usda.gov/AgCensus/index.php + +Places: US, State, County + +The source data is currently in `https://storage.cloud.google.com/datcom-csv/usda/2017_cdqt_data.txt`. + +To generate CSV: +``` +python3 process.py +``` + +The output will be `agriculture.csv`. + +To run unit tests: +``` +python3 process_test.py +``` diff --git a/scripts/us_usda/nass_census/agriculture.mcf b/scripts/us_usda/nass_census/agriculture.mcf new file mode 100644 index 0000000000..6614a705a0 --- /dev/null +++ b/scripts/us_usda/nass_census/agriculture.mcf @@ -0,0 +1,1676 @@ +Node: dcid:Count_Farm +description: "Number of farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue + +Node: dcid:Area_Farm +description: "Area of farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue + +Node: dcid:Mean_Area_Farm +description: "Mean area of farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:meanValue + +Node: dcid:Median_Area_Farm +description: "Median area of farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:medianValue + +Node: dcid:Mean_MarketValue_Farm_LandAndBuildings +description: "Mean market value of farm land and buildings." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:marketValue +statType: dcs:meanValue +farmInventoryType: dcs:LandAndBuildings + +Node: dcid:MarketValue_Farm_MachineryAndEquipment +description: "Market value of farm machinery and equipment." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:marketValue +statType: dcs:measuredValue +farmInventoryType: dcs:MachineryAndEquipment + +Node: dcid:Mean_MarketValue_Farm_MachineryAndEquipment +description: "Mean market value of farm machinery and equipment." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:marketValue +statType: dcs:meanValue +farmInventoryType: dcs:MachineryAndEquipment + +Node: dcid:Count_Farm_1To9.9Acre +description: "Number of farms of size 1-9.9 acres." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmSize: [Acre 1 9.9] + +Node: dcid:Count_Farm_10To49.9Acre +description: "Number of farms of size 10-49.9 acres." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmSize: [Acre 10 49.9] + +Node: dcid:Count_Farm_50To179Acre +description: "Number of farms of size 50-179 acres." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmSize: [Acre 50 179] + +Node: dcid:Count_Farm_180To499Acre +description: "Number of farms of size 180-499 acres." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmSize: [Acre 180 499] + +Node: dcid:Count_Farm_500To999Acre +description: "Number of farms of size 500-999 acres." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmSize: [Acre 500 999] + +Node: dcid:Count_1000OnwardsAcre +description: "Number of farms of size 1000 or more acres." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmSize: [Acre 1000 -] + +Node: dcid:Count_Farm_Cropland +description: "Numberu of farms with cropland." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmType: dcs:Cropland + +Node: dcid:Area_Farm_Cropland +description: "Area of farms with cropland." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmType: dcs:Cropland + +Node: dcid:Count_Farm_HarvestedCropland +description: "Number of farms with harvested cropland." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmType: dcs:HarvestedCropland + +Node: dcid:Area_Farm_HarvestedCropland +description: "Area of farms with harvested cropland." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmType: dcs:HarvestedCropland + +Node: dcid:Count_Farm_IrrigatedLand +description: "Number of farms with irrigated land." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmType: dcs:IrrigatedLand + +Node: dcid:Area_Farm_IrrigatedLand +description: "Area of farms with irrigated land." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmType: dcs:IrrigatedLand + +Node: dcid:MarketValue_Farm_AgriculturalProducts +description: "Market value of farm agricultural products." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:marketValue +statType: dcs:measuredValue +farmInventoryType: dcs:AgriculturalProducts + +Node: dcid:Mean_MarketValue_Farm_AgriculturalProducts +description: "Mean market value of farm agricultural products." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:marketValue +statType: dcs:meanValue +farmInventoryType: dcs:AgriculturalProducts + +Node: dcid:MarketValue_Farm_Crops +description: "Market value of farm crops." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:marketValue +statType: dcs:measuredValue +farmInventoryType: dcs:Crops + +Node: dcid:MarketValue_Farm_LivestockAndPoultry +description: "Market value of farm livestock and poultry." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:marketValue +statType: dcs:measuredValue +farmInventoryType: dcs:LivestockAndPoultry + +Node: dcid:Count_Farm_Upto1000USDollar +description: "Number of farms with value of sales up to $1000." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +valueOfSales: [USDollar - 1000] + +Node: dcid:Count_Farm_2500To4999USDollar +description: "Number of farms with value of sales $2500 - $4999." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +valueOfSales: [USDollar 2500 4999] + +Node: dcid:Count_Farm_5000To9999USDollar +description: "Number of farms with value of sales 5000 - $9999." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +valueOfSales: [USDollar 5000 9999] + +Node: dcid:Count_Farm_10000To24999USDollar +description: "Number of farms with value of sales $10000 - $24999." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +valueOfSales: [USDollar 10000 24999] + +Node: dcid:Count_Farm_25000To49999USDollar +description: "Number of farms with value of sales $25009 - $49999." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +valueOfSales: [USDollar 25000 49999] + +Node: dcid:Count_Farm_50000To99999USDollar +description: "Number of farms with value of sales $50000 - $99999." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +valueOfSales: [USDollar 50000 99999] + +Node: dcid:Count_Farm_100000OnwardsUSDollar +description: "Number of farms with value of sales $10000 or more." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +valueOfSales: [USDollar 100000 -] + +Node: dcid:Count_Farm_ReceivedGovernmentPayment +description: "Number of farms that received government payments." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +governmentPaymentStatus: dcs:GovernmentPayment + +Node: dcid:MonetaryValue_Farm_GovernmentPayment +description: "Value of government payments to farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:monetaryValue +statType: dcs:measuredValue +governmentPaymentStatus: dcs:GovernmentPayment + +Node: dcid:Count_Farm_ReportedIncome +description: "Number of farms that reported income." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +incomeStatus: dcs:ReportedIncome + +Node: dcid:Income_Farm +description: "Income from farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:income +statType: dcs:measuredValue + +Node: dcid:Expenses_Farm +description: "Farm expenses." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:expenses +statType: dcs:measuredValue + +Node: dcid:Mean_Expenses_Farm +description: "Mean farm expenses." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:expenses +statType: dcs:meanValue + +Node: dcid:Count_Farm_ReportedNetIncome +description: "Number of farms that reported net income." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +incomeStatus: dcs:ReportedNetIncome + +Node: dcid:NetMeasure_Income_Farm +description: "Net income from farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:income +statType: dcs:measuredValue +measurementQualifier: dcs:NetMeasure + +Node: dcid:Mean_NetMeasure_Income_Farm +description: "Mean net income from farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:income +statType: dcs:meanValue +measurementQualifier: dcs:NetMeasure + +Node: dcid:Count_Farm_CattleAndCalves +description: "Number of farms with cattle and calves." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:CattleAndCalves + +Node: dcid:Count_FarmInventory_CattleAndCalves +description: "Number of cattle and calves on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:CattleAndCalves + +Node: dcid:Count_Farm_BeefCows +description: "Number of farms with beef cows." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:BeefCows + +Node: dcid:Count_FarmInventory_BeefCows +description: "Number of beef cows on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:BeefCows + +Node: dcid:Count_Farm_MilkCows +description: "Number of farms with milke cows." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:MilkCows + +Node: dcid:Count_FarmInventory_MilkCows +description: "Number of milk cows on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:MilkCows + +Node: dcid:Count_Farm_InventorySold_CattleAndCalves +description: "Number of farms that sold cattle and calves." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryStatus: dcs:InventorySold +farmInventoryType: dcs:CattleAndCalves + +Node: dcid:QuantitySold_FarmInventory_CattleAndCalves +description: "Number of cattle and calves sold froms farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:quantitySold +statType: dcs:measuredValue +farmInventoryType: dcs:CattleAndCalves + +Node: dcid:Count_Farm_HogsAndPigs +description: "Number of farms with hogs and pigs." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:HogsAndPigs + +Node: dcid:Count_FarmInventory_HogsAndPigs +description: "Number of hogs and pigs on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:HogsAndPigs + +Node: dcid:Count_Farm_InventorySold_HogsAndPigs +description: "Number of farms that sold hogs and pigs." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryStatus: dcs:InventorySold +farmInventoryType: dcs:HogsAndPigs + +Node: dcid:QuantitySold_FarmInventory_HogsAndPigs +description: "Number of hogs and pigs sold froms farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:quantitySold +statType: dcs:measuredValue +farmInventoryType: dcs:HogsAndPigs + +Node: dcid:Count_Farm_SheepAndLambs +description: "Number of farms with sheep and lambs." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:SheepAndLambs + +Node: dcid:Count_FarmInventory_SheepAndLambs +description: "Number of sheep and lambs on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:SheepAndLambs + +Node: dcid:Count_Farm_Layers +description: "Number of farms with layers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:Layers + +Node: dcid:Count_FarmInventory_Layers +description: "Number of layers on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:Layers + +Node: dcid:Count_Farm_Broilers +description: "Number of farms with broilers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:Broilers + +Node: dcid:Count_FarmInventory_Broilers +description: "Number of broilers on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:Broilers + +Node: dcid:Count_Farm_CornForGrain +description: "Number of farms with corn for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:CornForGrain + +Node: dcid:Area_Farm_CornForGrain +description: "Area of farms with corn for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:CornForGrain + +Node: dcid:Amout_FarmInventory_CornForGrain +description: "Amount of corn for grain on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:CornForGrain + +Node: dcid:Count_Farm_CornForSilageOrGreenchop +description: "Number of farms with corn for silage or greenchop." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:CornForSilageOrGreenchop + +Node: dcid:Area_Farm_CornForSilageOrGreenchop +description: "Area of farms with corn for silage or greenchop." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:CornForSilageOrGreenchop + +Node: dcid:Amount_FarmInventory_CornForSilageOrGreenchop +description: "Amount of corn for silage or greenchop on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:CornForSilageOrGreenchop + +Node: dcid:Count_Farm_WheatForGrain +description: "Number of farms with wheat for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:WheatForGrain + +Node: dcid:Area_Farm_WheatForGrain +description: "Area of farms with wheat for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:WheatForGrain + +Node: dcid:Amount_FarmInventory_WheatForGrain +description: "Amount of wheat for grain on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:WheatForGrain + +Node: dcid:Count_Farm_DurumWheatForGrain +description: "Number of farms with durum wheat for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:DurumWheatForGrain + +Node: dcid:Area_Farm_DurumWheatForGrain +description: "Area of farms with durum wheat for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:DurumWheatForGrain + +Node: dcid:Amount_FarmInventory_DurumWheatForGrain +description: "Amount of durum wheat for grain on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:DurumWheatForGrain + +Node: dcid:Count_Farm_OtherSpringWheatForGrain +description: "Number of farms with other spring wheat for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:OtherSpringWheatForGrain + +Node: dcid:Area_Farm_OtherSpringWheatForGrain +description: "Area of farms with other spring wheat for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:OtherSpringWheatForGrain + +Node: dcid:Amount_FarmInventory_OtherSpringWheatForGrain +description: "Amount of other spring wheat for grain on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:OtherSpringWheatForGrain + +Node: dcid:Count_Farm_WinterWheatForGrain +description: "Number of farms with winter wheat for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:WinterWheatForGrain + +Node: dcid:Area_Farm_WinterWheatForGrain +description: "Area of farms with winter wheat for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:WinterWheatForGrain + +Node: dcid:AmountFarmInventory_WinterWheatForGrain +description: "Amount of winter wheat for grain on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:WinterWheatForGrain + +Node: dcid:Count_Farm_OatsForGrain +description: "Number of farms with oats for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:OatsForGrain + +Node: dcid:Area_Farm_OatsForGrain +description: "Area of farms with oats for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:OatsForGrain + +Node: dcid:Amount_FarmInventory_OatsForGrain +description: "Amount of oats for grain on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:OatsForGrain + +Node: dcid:Count_Farm_BarleyForGrain +description: "Number of farms with barley for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:BarleyForGrain + +Node: dcid:Area_Farm_BarleyForGrain +description: "Area of farms with barley for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:BarleyForGrain + +Node: dcid:Amount_FarmInventory_BarleyForGrain +description: "Amount of barley for grain on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:BarleyForGrain + +Node: dcid:Count_Farm_SorghumForGrain +description: "Number of farms with sorghum for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:SorghumForGrain + +Node: dcid:Area_Farm_SorghumForGrain +description: "Area of farms with sorghum for grain." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:SorghumForGrain + +Node: dcid:Amount_FarmInventory_SorghumForGrain +description: "Amount of sorghum for grain on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:SorghumForGrain + +Node: dcid:Count_Farm_SorghumForSilageOrGreenchop +description: "Number of farms with sorghum for silage or greenchop." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:SorghumForSilageOrGreenchop + +Node: dcid:Area_Farm_SorghumForSilageOrGreenchop +description: "Area of farms with sorghum for silage or greenchop." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:SorghumForSilageOrGreenchop + +Node: dcid:Amount_FarmInventory_SorghumForSilageOrGreenchop +description: "Amount of sorghum for silage or greenchop on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:SorghumForSilageOrGreenchop + +Node: dcid:Count_Farm_DryEdibleBeans +description: "Number of farms with dry edible beans." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:DryEdibleBeans + +Node: dcid:Area_Farm_DryEdibleBeans +description: "Area of farms with dry edible beans." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:DryEdibleBeans + +Node: dcid:Amount_FarmInventory_DryEdibleBeans +description: "Amount of dry edible beans on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:DryEdibleBeans + +Node: dcid:Count_Farm_Cotton +description: "Number of farms with cotton." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:Cotton + +Node: dcid:Area_Farm_Cotton +description: "Area of farms with cotton." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:Cotton + +Node: dcid:Amount_FarmInventory_Cotton +description: "Amount of cotton on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:Cotton + +Node: dcid:Count_Farm_UplandCotton +description: "Number of farms with upland cotton." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:UplandCotton + +Node: dcid:Area_Farm_UplandCotton +description: "Area of farms with upland cotton." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:UplandCotton + +Node: dcid:Amount_FarmInventory_UplandCotton +description: "Amount of upland cotton on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:UplandCotton + +Node: dcid:Count_Farm_PimaCotton +description: "Number of farms with pima cotton." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:PimaCotton + +Node: dcid:Area_Farm_PimaCotton +description: "Area of farms with pima cotton." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:PimaCotton + +Node: dcid:Amount_FarmInventory_PimaCotton +description: "Amount of pima cotton on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:PimaCotton + +Node: dcid:Count_Farm_Forage +description: "Number of farms with forage." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:Forage + +Node: dcid:Area_Farm_Forage +description: "Area of farms with forage." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:Forage + +Node: dcid:Amount_FarmInventory_Forage +description: "Amount of forage on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:Forage + +Node: dcid:Count_Farm_Rice +description: "Number of farms with rice." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:Rice + +Node: dcid:Area_Farm_Rice +description: "Area of farms with rice." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:Rice + +Node: dcid:Amount_FarmInventory_Rice +description: "Amount of forage on rice." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:Rice + +Node: dcid:Count_Farm_SunflowerSeed +description: "Number of farms with sunflower seed." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:SunflowerSeed + +Node: dcid:Area_Farm_SunflowerSeed +description: "Area of farms with sunflower seed." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:SunflowerSeed + +Node: dcid:Amount_FarmInventory_SunflowerSeed +description: "Amount of forage on sunflower seed." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:SunflowerSeed + +Node: dcid:Count_Farm_SugarbeetsForSugar +description: "Number of farms with sugarbeets for sugar." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:SugarbeetsForSugar + +Node: dcid:Area_Farm_SugarbeetsForSugar +description: "Area of farms with sugarbeets for sugar." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:SugarbeetsForSugar + +Node: dcid:Amount_FarmInventory_SugarbeetsForSugar +description: "Amount of forage on sugarbeets for sugar." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:SugarbeetsForSugar + +Node: dcid:Count_Farm_PeanutsForNuts +description: "Number of farms with peanuts for nuts." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:PeanutsForNuts + +Node: dcid:Area_Farm_PeanutsForNuts +description: "Area of farms with peanuts for nuts." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:PeanutsForNuts + +Node: dcid:Amount_FarmInventory_PeanutsForNuts +description: "Amount of peanuts for nuts on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:FarmInventory +measuredProperty: dcs:amount +statType: dcs:measuredValue +farmInventoryType: dcs:PeanutsForNuts + +Node: dcid:Count_Farm_VegetablesHarvestedForSale +description: "Number of farms with vegetables harvested for sale." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:VegetablesHarvestedForSale + +Node: dcid:Area_Farm_VegetablesHarvestedForSale +description: "Area of farms with vegetables harvested for sale." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:VegetablesHarvestedForSale + +Node: dcid:Count_Farm_Potatoes +description: "Number of farms with potatoes." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:Potatoes + +Node: dcid:Area_Farm_Potatoes +description: "Area of farms with potatoes." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:Potatoes + +Node: dcid:Count_Farm_SweetPotatoes +description: "Number of farms with sweet potatoes." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:SweetPotatoes + +Node: dcid:Area_Farm_SweetPotatoes +description: "Area of farms with sweet potatoes." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:SweetPotatoes + +Node: dcid:Count_Farm_Orchards +description: "Number of farms with orchards." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +farmInventoryType: dcs:Orchards + +Node: dcid:Area_Farm_Orchards +description: "Area of farms with orchards." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +farmInventoryType: dcs:Orchards + +Node: dcid:Count_Farm_Producer_HispanicOrLatino +description: "Number of farms with Hispanic or Latino producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:HispanicOrLatino + +Node: dcid:Count_Person_Producer_HispanicOrLatino +description: "Number of Hispanic or Latino producers on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:Person +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:HispanicOrLatino + +Node: dcid:Area_Farm_Producer_HispanicOrLatino +description: "Area of farms with Hispanic or Latino producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:HispanicOrLatino + +Node: dcid:Count_Farm_PrimaryProducer_HispanicOrLatino +description: "Number of farms with Hispanic or Latino primary producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:PrimaryProducer +race: dcs:HispanicOrLatino + +Node: dcid:Area_Farm_PrimaryProducer_HispanicOrLatino +description: "Area of farms with Hispanic or Latino primary producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +ownershipStatus: dcs:PrimaryProducer +race: dcs:HispanicOrLatino + +Node: dcid:Count_Farm_Producer_AmericanIndianOrAlaskaNativeAlone +description: "Number of farms with American Indian or Alaska Native producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:AmericanIndianOrAlaskaNativeAlone + +Node: dcid:Count_Person_Producer_AmericanIndianOrAlaskaNativeAlone +description: "Number of American Indian or Alaska Native producers on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:Person +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:AmericanIndianOrAlaskaNativeAlone + +Node: dcid:Area_Farm_Producer_AmericanIndianOrAlaskaNativeAlone +description: "Area of farms with American Indian or Alaska Native producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:AmericanIndianOrAlaskaNativeAlone + +Node: dcid:Count_Farm_PrimaryProducer_AmericanIndianOrAlaskaNativeAlone +description: "Number of farms with American Indian or Alaska Native primary producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:PrimaryProducer +race: dcs:AmericanIndianOrAlaskaNativeAlone + +Node: dcid:Area_Farm_PrimaryProducer_AmericanIndianOrAlaskaNativeAlone +description: "Area of farms with American Indian or Alaska Native primary producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +ownershipStatus: dcs:PrimaryProducer +race: dcs:AmericanIndianOrAlaskaNativeAlone + +Node: dcid:Count_Farm_Producer_AsianAlone +description: "Number of farms with Asian producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:AsianAlone + +Node: dcid:Count_Person_Producer_AsianAlone +description: "Number of Asian producers on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:Person +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:AsianAlone + +Node: dcid:Area_Farm_Producer_AsianAlone +description: "Area of farms with Asian producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:AsianAlone + +Node: dcid:Count_Farm_PrimaryProducer_AsianAlone +description: "Number of farms with Asian primary producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:PrimaryProducer +race: dcs:AsianAlone + +Node: dcid:Area_Farm_PrimaryProducer_AsianAlone +description: "Area of farms with Asian primary producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +ownershipStatus: dcs:PrimaryProducer +race: dcs:AsianAlone + +Node: dcid:Count_Farm_Producer_BlackOrAfricanAmericanAlone +description: "Number of farms with Black or African American producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:BlackOrAfricanAmericanAlone + +Node: dcid:Count_Person_Producer_BlackOrAfricanAmericanAlone +description: "Number of Black or African American producers on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:Person +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:BlackOrAfricanAmericanAlone + +Node: dcid:Area_Farm_Producer_BlackOrAfricanAmericanAlone +description: "Area of farms with Black or African American producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:BlackOrAfricanAmericanAlone + +Node: dcid:Count_Farm_PrimaryProducer_BlackOrAfricanAmericanAlone +description: "Number of farms with Black or African American priamry producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:PrimaryProducer +race: dcs:BlackOrAfricanAmericanAlone + +Node: dcid:Area_Farm_PrimaryProducer_BlackOrAfricanAmericanAlone +description: "Area of farms with Black or African American primary producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +ownershipStatus: dcs:PrimaryProducer +race: dcs:BlackOrAfricanAmericanAlone + +Node: dcid:Count_Farm_Producer_NativeHawaiianOrOtherPacificIslanderAlone +description: "Number of farms with Native Hawaiian or other Pacific Islander producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:NativeHawaiianOrOtherPacificIslanderAlone + +Node: dcid:Count_Person_Producer_NativeHawaiianOrOtherPacificIslanderAlone +description: "Number of Native Hawaiian or other Pacific Islander producers on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:Person +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:NativeHawaiianOrOtherPacificIslanderAlone + +Node: dcid:Area_Farm_Producer_NativeHawaiianOrOtherPacificIslanderAlone +description: "Area of farms with Native Hawaiian or other Pacific Islander producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:NativeHawaiianOrOtherPacificIslanderAlone + +Node: dcid:Count_Farm_PrimaryProducer_NativeHawaiianOrOtherPacificIslanderAlone +description: "Number of farms with Native Hawaiian or other Pacific Islander primary producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:PrimaryProducer +race: dcs:NativeHawaiianOrOtherPacificIslanderAlone + +Node: dcid:Area_Farm_PrimaryProducer_NativeHawaiianOrOtherPacificIslanderAlone +description: "Area of farms with Native Hawaiian or other Pacific Islander primary producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +ownershipStatus: dcs:PrimaryProducer +race: dcs:NativeHawaiianOrOtherPacificIslanderAlone + +Node: dcid:Count_Farm_Producer_WhiteAlone +description: "Number of farms with White producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:WhiteAlone + +Node: dcid:Count_Person_Producer_WhiteAlone +description: "Number of White producers on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:Person +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:WhiteAlone + +Node: dcid:Area_Farm_Producer_WhiteAlone +description: "Area of farms with White producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:WhiteAlone + +Node: dcid:Count_Farm_PrimaryProducer_WhiteAlone +description: "Number of farms with White primary producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:PrimaryProducer +race: dcs:WhiteAlone + +Node: dcid:Area_Farm_PrimaryProducer_WhiteAlone +description: "Area of farms with White primary producers." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +ownershipStatus: dcs:PrimaryProducer +race: dcs:WhiteAlone + +Node: dcid:Count_Farm_Producer_TwoOrMoreRaces +description: "Number of farms with producers of two or more races." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:TwoOrMoreRaces + +Node: dcid:Count_Person_Producer_TwoOrMoreRaces +description: "Number of producers of two of more races on farms." +typeOf: dcs:StatisticalVariable +populationType: dcs:Person +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:TwoOrMoreRaces + +Node: dcid:Area_Farm_Producer_TwoOrMoreRaces +description: "Area of farms with producers of two or more races." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +ownershipStatus: dcs:Producer +race: dcs:TwoOrMoreRaces + +Node: dcid:Count_Farm_PrimaryProducer_TwoOrMoreRaces +description: "Number of farms with primary producers of two or more races." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:count +statType: dcs:measuredValue +ownershipStatus: dcs:PrimaryProducer +race: dcs:TwoOrMoreRaces + +Node: dcid:Area_Farm_PrimaryProducer_TwoOrMoreRaces +description: "Area of farms with primary producers of two or more races." +typeOf: dcs:StatisticalVariable +populationType: dcs:Farm +measuredProperty: dcs:area +statType: dcs:measuredValue +ownershipStatus: dcs:PrimaryProducer +race: dcs:TwoOrMoreRaces + +## Classes + +Node: dcid:Farm +typeOf: schema:Class +description: "An area of land and its buildings used for growing crops and rearing animals." +subClassOf: schema:Place +name: "Farm" + +Node: dcid:FarmInventory +typeOf: schema:Class +description: "Something grown or produced on a farm." +subClassOf: schema:Thing +name: "FarmInventory" + +Node: dcid:Bushel +typeOf: dcs:VolumeUnitOfMeasure +description: "A measure of capacity equal to 64 US pints (equivalent to 35.2 liters), used for dry goods." +name: "Bushel" + +Node: dcid:Bale +typeOf: dcs:VolumeUnitOfMeasure +description: "A bundle of paper, hay, cotton, etc., tightly wrapped and bound with cords or hoops." +name: "Bale" + +Node: dcid:Ton +typeOf: dcs:WeightUnitOfMeasure +description: "A unit of weight equal to 2,000 pounds avoirdupois (907.19 kg)." +name: "Ton" + +Node: dcid:Pound +typeOf: dcs:WeightUnitOfMeasure +description: "A unit of weight in general use equal to 16 oz. avoirdupois (0.4536 kg)." +name: "Pound" + +Node: dcid:Hundredweight +typeOf: dcs:WeightUnitOfMeasure +description: "A unit of weight equal to 100 lb avoirdupois (about 45.4 kg)." +name: "Hundredweight" + +Node: dcid:USDollarPerFarm +typeOf: dcs:CurrencyUnitOfMeasure +name: "USDollarPerFarm" + +Node: dcid:USDollarPerAcre +typeOf: dcs:CurrencyUnitOfMeasure +name: "USDollarPerAcre" + +## Properties + +Node: dcid:marketValue +typeOf: schema:Property +domainIncludes: dcs:Farm +rangeIncludes: dcs:Quantity +name: "marketValue" + +Node: dcid:farmSize +typeOf: schema:Property +domainIncludes: dcs:Farm +rangeIncludes: dcs:QuantityRange +name: "farmSize" + +Node: dcid:valueOfSales +typeOf: schema:Property +domainIncludes: dcs:Farm +rangeIncludes: dcs:QuantityRange +name: "valueOfSales" + +Node: dcid:farmType +typeOf: schema:Property +domainIncludes: dcs:Farm +rangeIncludes: dcs:FarmTypeEnum +name: "farmType" + +Node: dcid:governmentPaymentStatus +typeOf: schema:Property +domainIncludes: dcs:Farm +rangeIncludes: dcs:GovernmentPaymentStatusEnum +name: "governmentPaymentStatus" + +Node: dcid:incomeStatus +typeOf: schema:Property +domainIncludes: dcs:Farm +rangeIncludes: dcs:IncomeStatusEnum +name: "incomeStatus" + +Node: dcid:expenses +typeOf: schema:Property +domainIncludes: dcs:Farm +rangeIncludes: dcs:Quantity +name: "expenses" + +Node: dcid:farmInventoryType +typeOf: schema:Property +domainIncludes: dcs:Farm, dcs:FarmInventory +rangeIncludes: dcs:FarmInventoryTypeEnum +name: "farmInventoryType" + +Node: dcid:quantitySold +typeOf: schema:Property +domainIncludes: dcs:FarmInventory +rangeIncludes: dcs:Quantity +name: "quantitySold" + +Node: dcid:farmInventoryStatus +typeOf: schema:Property +domainIncludes: dcs:Farm +rangeIncludes: dcs:FarmInventoryStatusEnum +name: "farmInventoryStatus" + +Node: dcid:ownershipStatus +typeOf: schema:Property +domainIncludes: dcs:Farm +rangeIncludes: dcs:OwnershipStatusEnum +name: "ownershipStatus" + +Node: dcid:amount +typeOf: schema:Property +domainIncludes: dcs:FarmInventory + +Node: dcid:area +typeOf: schema:Property +domainIncludes: dcs:Farm + +Node: dcid:income +typeOf: schema:Property +domainIncludes: dcs:Farm + +Node: dcid:monetaryValue +typeOf: schema:Property +domainIncludes: dcs:Farm + +## Enums + +Node: dcid:FarmTypeEnum +typeOf: schema:Class +subClassOf: schema:Enumeration +name: "FarmTypeEnum" + +Node: dcid:Cropland +typeOf: dcs:FarmTypeEnum +name: "Cropland" + +Node: dcid:HarvestedCropland +typeOf: dcs:FarmTypeEnum +name: "HarvestedCropland" +specializationOf: dcs:Cropland + +Node: dcid:IrrigatedLand +typeOf: dcs:FarmTypeEnum +name: "IrrigatedLand" + +Node: dcid:GovernmentPaymentStatusEnum +typeOf: schema:Class +subClassOf: schema:Enumeration +name: "GovernmentPaymentStatusEnum" + +Node: dcid:GovernmentPayment +typeOf: dcs:GovernmentPaymentStatusEnum +name: "GovernmentPayment" + +Node: dcid:IncomePaymentStatusEnum +typeOf: schema:Class +subClassOf: schema:Enumeration +name: "IncomePaymentStatusEnum" + +Node: dcid:ReportedIncome +typeOf: dcs:IncomePaymentStatusEnum +name: "ReportedIncome" + +Node: dcid:ReportedNetIncome +typeOf: dcs:IncomePaymentStatusEnum +name: "ReportedNetIncome" + +Node: dcid:IncomeMeasurementEnum +typeOf: schema:Class +subClassOf: schema:Enumeration +name: "IncomeMeasurementEnum" + +Node: dcid:NetMeasure +typeOf: dcs:IncomeMeasurementEnum +name: "NetMeasure" + +Node: dcid:FarmInventoryTypeEnum +typeOf: schema:Class +subClassOf: schema:Enumeration +name: "FarmInventoryTypeEnum" + +Node: dcid:LandAndBuildings +typeOf: dcs:FarmInventoryTypeEnum +name: "LandAndBuildings" + +Node: dcid:MachineryAndEquipment +typeOf: dcs:FarmInventoryTypeEnum +name: "MachineryAndEquipment" + +Node: dcid:AgriculturalProducts +typeOf: dcs:FarmInventoryTypeEnum +name: "AgriculturalProducts" + +Node: dcid:LivestockAndPoultry +typeOf: dcs:FarmInventoryTypeEnum +name: "LivestockAndPoultry" +specializationOf: dcs:AgriculturalProducts + +Node: dcid:CattleAndCalves +typeOf: dcs:FarmInventoryTypeEnum +name: "CattleAndCalves" +specializationOf: dcs:LivestockAndPoultry + +Node: dcid:BeefCows +typeOf: dcs:FarmInventoryTypeEnum +name: "BeefCows" +specializationOf: dcs:CattleAndCalves + +Node: dcid:MilkCows +typeOf: dcs:FarmInventoryTypeEnum +name: "MilkCows" +specializationOf: dcs:CattleAndCalves + +Node: dcid:HogsAndPigs +typeOf: dcs:FarmInventoryTypeEnum +name: "HogsAndPigs" +specializationOf: dcs:LivestockAndPoultry + +Node: dcid:SheepAndLambs +typeOf: dcs:FarmInventoryTypeEnum +name: "SheepAndLambs" +specializationOf: dcs:LivestockAndPoultry + +Node: dcid:Layers +typeOf: dcs:FarmInventoryTypeEnum +name: "Layers" +specializationOf: dcs:LivestockAndPoultry + +Node: dcid:Broilers +typeOf: dcs:FarmInventoryTypeEnum +name: "Broilers" +specializationOf: dcs:LivestockAndPoultry + +Node: dcid:Crops +typeOf: dcs:FarmInventoryTypeEnum +name: "Crops" +specializationOf: dcs:AgriculturalProducts + +Node: dcid:Corn +typeOf: dcs:FarmInventoryTypeEnum +name: "Corn" +specializationOf: dcs:Crops + +Node: dcid:CornForGrain +typeOf: dcs:FarmInventoryTypeEnum +name: "CornForGrain" +specializationOf: dcs:Corn + +Node: dcid:CornForSilageOrGreenchop +typeOf: dcs:FarmInventoryTypeEnum +name: "CornForSilageOrGreenchop" +specializationOf: dcs:Corn + +Node: dcid:WheatForGrain +typeOf: dcs:FarmInventoryTypeEnum +name: "WheatForGrain" +specializationOf: dcs:Crops + +Node: dcid:DurumWheatForGrain +typeOf: dcs:FarmInventoryTypeEnum +name: "DurumWheatForGrain" +specializationOf: dcs:WheatForGrain + +Node: dcid:OtherSpringWheatForGrain +typeOf: dcs:FarmInventoryTypeEnum +name: "OtherSpringWheatForGrain" +specializationOf: dcs:WheatForGrain + +Node: dcid:WinterWheatForGrain +typeOf: dcs:FarmInventoryTypeEnum +name: "WinterWheatForGrain" +specializationOf: dcs:WheatForGrain + +Node: dcid:OatsForGrain +typeOf: dcs:FarmInventoryTypeEnum +name: "OatsForGrain" +specializationOf: dcs:Crops + +Node: dcid:BarleyForGrain +typeOf: dcs:FarmInventoryTypeEnum +name: "BarleyForGrain" +specializationOf: dcs:Crops + +Node: dcid:BarleyForGrain +typeOf: dcs:FarmInventoryTypeEnum +name: "BarleyForGrain" +specializationOf: dcs:Crops + +Node: dcid:SorghumForGrain +typeOf: dcs:FarmInventoryTypeEnum +name: "SorghumForGrain" +specializationOf: dcs:Crops + +Node: dcid:SorghumForSilageOrGreenchop +typeOf: dcs:FarmInventoryTypeEnum +name: "SorghumForSilageOrGreenchop" +specializationOf: dcs:Crops + +Node: dcid:DryEdibleBeans +typeOf: dcs:FarmInventoryTypeEnum +name: "DryEdibleBeans" +specializationOf: dcs:Crops + +Node: dcid:Cotton +typeOf: dcs:FarmInventoryTypeEnum +name: "Cotton" +specializationOf: dcs:Crops + +Node: dcid:UplandCotton +typeOf: dcs:FarmInventoryTypeEnum +name: "UplandCotton" +specializationOf: dcs:Cotton + +Node: dcid:PimaCotton +typeOf: dcs:FarmInventoryTypeEnum +name: "PimaCotton" +specializationOf: dcs:Cotton + +Node: dcid:Forage +typeOf: dcs:FarmInventoryTypeEnum +name: "Forage" +specializationOf: dcs:Crops + +Node: dcid:Rice +typeOf: dcs:FarmInventoryTypeEnum +name: "Rice" +specializationOf: dcs:Crops + +Node: dcid:SunflowerSeed +typeOf: dcs:FarmInventoryTypeEnum +name: "SunflowerSeed" +specializationOf: dcs:Crops + +Node: dcid:SugarbeetsForSugar +typeOf: dcs:FarmInventoryTypeEnum +name: "SugarbeetsForSugar" +specializationOf: dcs:Crops + +Node: dcid:PeanutsForNuts +typeOf: dcs:FarmInventoryTypeEnum +name: "PeanutsForNuts" +specializationOf: dcs:Crops + +Node: dcid:VegetablesHarvestedForSale +typeOf: dcs:FarmInventoryTypeEnum +name: "VegetablesHarvestedForSale" +specializationOf: dcs:Crops + +Node: dcid:Potatoes +typeOf: dcs:FarmInventoryTypeEnum +name: "Potatoes" +specializationOf: dcs:VegetablesHarvestedForSale + +Node: dcid:SweetPotatoes +typeOf: dcs:FarmInventoryTypeEnum +name: "SweetPotatoes" +specializationOf: dcs:VegetablesHarvestedForSale + +Node: dcid:Orchards +typeOf: dcs:FarmInventoryTypeEnum +name: "Orchards" +specializationOf: dcs:Crops + +Node: dcid:FarmInventoryStatusEnum +typeOf: schema:Class +subClassOf: schema:Enumeration +name: "FarmInventoryStatusEnum" + +Node: dcid:InventorySold +typeOf: dcs:FarmInventoryStatusEnum +name: "InventorySold" + +Node: dcid:OwnershipStatusEnum +typeOf: schema:Class +subClassOf: schema:Enumeration +name: "OwnershipStatusEnum" + +Node: dcid:Producer +typeOf: dcs:OwnershipStatusEnum +name: "Producer" + +Node: dcid:PrimaryProducer +typeOf: dcs:OwnershipStatusEnum +name: "PrimaryProducer" diff --git a/scripts/us_usda/nass_census/agriculture.tmcf b/scripts/us_usda/nass_census/agriculture.tmcf new file mode 100644 index 0000000000..8b098ca201 --- /dev/null +++ b/scripts/us_usda/nass_census/agriculture.tmcf @@ -0,0 +1,8 @@ +Node: E:USDA_AgricultureCensus->E0 +typeOf: dcs:StatVarObservation +variableMeasured: C:USDA_AgricultureCensus->variableMeasured +observationDate: "2017" +observationAbout: C:USDA_AgricultureCensus->observationAbout +observationPeriod: "P5Y" +value: C:USDA_AgricultureCensus->value +unit: C:USDA_AgricultureCensus->unit diff --git a/scripts/us_usda/nass_census/dc_generated/report.json b/scripts/us_usda/nass_census/dc_generated/report.json new file mode 100644 index 0000000000..2ac4b1ed1e --- /dev/null +++ b/scripts/us_usda/nass_census/dc_generated/report.json @@ -0,0 +1,265 @@ +{ + "levelSummary": { + "LEVEL_INFO": { + "counters": { + "NumRowSuccesses": "661158", + "NumPVSuccesses": "5569995", + "Existence_NumChecks": "5189568", + "NumNodeSuccesses": "661158", + "Existence_NumDcCalls": "2" + } + }, + "LEVEL_WARNING": { + "counters": { + "StrSplit_EmptyToken_unit": "380427" + } + } + }, + "entries": [{ + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "2" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "3" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "4" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "5" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "6" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "7" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "8" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "9" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "10" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "11" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "12" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "13" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "14" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "15" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "16" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "17" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "18" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "19" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "20" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "21" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "22" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "23" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "24" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "25" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "26" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "27" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "28" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "29" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "30" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }, { + "level": "LEVEL_WARNING", + "location": { + "file": "agriculture.csv", + "lineNumber": "31" + }, + "userMessage": "Empty value found :: value: '', column: 'unit', property: 'unit', node: 'E:USDA_AgricultureCensus->E0'", + "counterKey": "StrSplit_EmptyToken_unit" + }], + "commandArgs": { + "existenceChecks": true, + "resolution": "RESOLUTION_MODE_LOCAL", + "numThreads": 1, + "statChecks": true + } +} \ No newline at end of file diff --git a/scripts/us_usda/nass_census/process.py b/scripts/us_usda/nass_census/process.py new file mode 100644 index 0000000000..3e0d69d314 --- /dev/null +++ b/scripts/us_usda/nass_census/process.py @@ -0,0 +1,82 @@ +# Copyright 2021 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Import USDA Census of Agriculture.""" + +import csv +import io +from google.cloud import storage + +CSV_COLUMNS = [ + 'variableMeasured', + 'observationAbout', + 'value', + 'unit', +] + +SKIPPED_VALUES = [ + '(D)', + '(Z)', +] + + +def get_statvars(filename): + d = {} + f = open(filename) + lines = f.readlines() + for l in lines: + l = l[:-1] # trim newline character + p = l.split('^') + d[p[0]] = tuple(p[1:]) + f.close() + return d + + +def write_csv(reader, out, d): + writer = csv.DictWriter(out, fieldnames=CSV_COLUMNS, lineterminator='\n') + writer.writeheader() + for r in reader: + key = r['SHORT_DESC'] + if r['DOMAINCAT_DESC']: + key += '%%' + r['DOMAINCAT_DESC'] + if key not in d: + continue + if r['VALUE'] in SKIPPED_VALUES: + continue + value = d[key] + if r['AGG_LEVEL_DESC'] == 'NATIONAL': + observationAbout = 'dcid:country/USA' + elif r['AGG_LEVEL_DESC'] == 'STATE': + observationAbout = 'dcid:geoId/' + r['STATE_FIPS_CODE'] + elif r['AGG_LEVEL_DESC'] == 'COUNTY': + observationAbout = 'dcid:geoId/' + r['STATE_FIPS_CODE'] + r[ + 'COUNTY_CODE'] + row = { + 'variableMeasured': 'dcs:' + value[0], + 'observationAbout': observationAbout, + 'value': int(r['VALUE'].replace(',', '')), + } + if len(value) > 1: + row['unit'] = 'dcs:' + value[1] + writer.writerow(row) + + +if __name__ == '__main__': + d = get_statvars('statvars') + client = storage.Client() + bucket = client.get_bucket('datcom-csv') + blob = bucket.get_blob('usda/2017_cdqt_data.txt') + s = blob.download_as_string().decode('utf-8') + reader = csv.DictReader(io.StringIO(s), delimiter='\t') + out = open('agriculture.csv', 'w', newline='') + write_csv(reader, out, d) diff --git a/scripts/us_usda/nass_census/process_test.py b/scripts/us_usda/nass_census/process_test.py new file mode 100644 index 0000000000..9979b0425a --- /dev/null +++ b/scripts/us_usda/nass_census/process_test.py @@ -0,0 +1,37 @@ +# Copyright 2021 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for process.py""" + +import csv +import io +import unittest +from process import get_statvars, write_csv + + +class ProcessTest(unittest.TestCase): + + def test_write_csv(self): + with open('./testdata/input.csv') as f_in: + d = get_statvars('statvars') + reader = csv.DictReader(f_in, delimiter='\t') + f_out = io.StringIO() + f_expected = open('testdata/expected.csv') + expected = f_expected.read() + f_expected.close() + write_csv(reader, f_out, d) + self.assertEqual(expected, f_out.getvalue()) + + +if __name__ == '__main__': + unittest.main() diff --git a/scripts/us_usda/nass_census/statvars b/scripts/us_usda/nass_census/statvars new file mode 100644 index 0000000000..5d4ee53987 --- /dev/null +++ b/scripts/us_usda/nass_census/statvars @@ -0,0 +1,158 @@ +FARM OPERATIONS - NUMBER OF OPERATIONS^Count_Farm +FARM OPERATIONS - NUMBER OF OPERATIONS%%AREA OPERATED: (1.0 TO 9.9 ACRES)^Count_Farm_1To9.9Acre +FARM OPERATIONS - NUMBER OF OPERATIONS%%AREA OPERATED: (10.0 TO 49.9 ACRES)^Count_Farm_10To49.9Acre +FARM OPERATIONS - NUMBER OF OPERATIONS%%AREA OPERATED: (50 TO 179 ACRES)^Count_Farm_50To179Acre +FARM OPERATIONS - NUMBER OF OPERATIONS%%AREA OPERATED: (180 TO 499 ACRES)^Count_Farm_180To499Acre +FARM OPERATIONS - NUMBER OF OPERATIONS%%AREA OPERATED: (500 TO 999 ACRES)^Count_Farm_500To999Acre +FARM OPERATIONS - NUMBER OF OPERATIONS%%AREA OPERATED: (1,000 OR MORE ACRES)^Count_1000OnwardsAcre +FARM OPERATIONS - ACRES OPERATED^Area_Farm^Acre +FARM OPERATIONS - AREA OPERATED, MEASURED IN ACRES / OPERATION^Mean_Area_Farm^Acre +FARM OPERATIONS - AREA OPERATED, MEASURED IN ACRES / OPERATION, MEDIAN^Median_Area_Farm^Acre +AG LAND, INCL BUILDINGS - ASSET VALUE, MEASURED IN $ / OPERATION^Mean_MarketValue_Farm_LandAndBuildings^USDollarPerFarm +AG LAND, INCL BUILDINGS - ASSET VALUE, MEASURED IN $ / ACRE^Mean_MarketValue_Farm_LandAndBuildings^USDollarPerAcre +MACHINERY TOTALS - ASSET VALUE, MEASURED IN $^MarketValue_Farm_MachineryAndEquipment^USDollar +MACHINERY TOTALS - ASSET VALUE, MEASURED IN $ / OPERATION^Mean_MarketValue_Farm_MachineryAndEquipment^USDollarPerFarm +AG LAND, CROPLAND - NUMBER OF OPERATIONS^Count_Farm_Cropland +AG LAND, CROPLAND - ACRES^Area_Farm_Cropland^Acre +AG LAND, CROPLAND, HARVESTED - NUMBER OF OPERATIONS^Count_Farm_HarvestedCropland +AG LAND, CROPLAND, HARVESTED - ACRES^Area_Farm_HarvestedCropland^Acre +AG LAND, IRRIGATED - NUMBER OF OPERATIONS^Count_Farm_IrrigatedLand +AG LAND, IRRIGATED - ACRES^Area_Farm_IrrigatedLand^Acre +COMMODITY TOTALS - SALES, MEASURED IN $^MarketValue_Farm_AgriculturalProducts^USDollar +COMMODITY TOTALS - SALES, MEASURED IN $ / OPERATION^Mean_MarketValue_Farm_AgriculturalProducts^USDollarPerFarm +CROP TOTALS - SALES, MEASURED IN $^MarketValue_Farm_Crops^USDollar +ANIMAL TOTALS, INCL PRODUCTS - SALES, MEASURED IN $^MarketValue_Farm_LivestockAndPoultry^USDollar +COMMODITY TOTALS - OPERATIONS WITH SALES%%FARM SALES: (LESS THAN 2,500 $)^Count_Farm_Upto1000USDollar +COMMODITY TOTALS - OPERATIONS WITH SALES%%FARM SALES: (2,500 TO 4,999 $)^Count_Farm_2500To4999USDollar +COMMODITY TOTALS - OPERATIONS WITH SALES%%FARM SALES: (5,000 TO 9,999 $)^Count_Farm_5000To9999USDollar +COMMODITY TOTALS - OPERATIONS WITH SALES%%FARM SALES: (10,000 TO 24,999 $)^Count_Farm_10000To24999USDollar +COMMODITY TOTALS - OPERATIONS WITH SALES%%FARM SALES: (25,000 TO 49,999 $)^Count_Farm_25000To49999USDollar +COMMODITY TOTALS - OPERATIONS WITH SALES%%FARM SALES: (50,000 TO 99,999 $)^Count_Farm_50000To99999USDollar +COMMODITY TOTALS - OPERATIONS WITH SALES%%FARM SALES: (100,000 OR MORE $)^Count_Farm_100000OnwardsUSDollar +GOVT PROGRAMS, FEDERAL - OPERATIONS WITH RECEIPTS^Count_Farm_ReceivedGovernmentPayment +GOVT PROGRAMS, FEDERAL - RECEIPTS, MEASURED IN $^MonetaryValue_Farm_GovernmentPayment^USDollar +INCOME, FARM-RELATED - OPERATIONS WITH RECEIPTS^Count_Farm_ReportedIncome +INCOME, FARM-RELATED - RECEIPTS, MEASURED IN $^Income_Farm^USDollar +EXPENSE TOTALS, OPERATING - EXPENSE, MEASURED IN $^Expenses_Farm^USDollar +EXPENSE TOTALS, OPERATING - EXPENSE, MEASURED IN $ / OPERATION^Mean_Expenses_Farm^USDollarPerFarm +INCOME, NET CASH FARM, OF OPERATIONS - OPERATIONS WITH NET INCOME^Count_Farm_ReportedNetIncome +INCOME, NET CASH FARM, OF OPERATIONS - NET INCOME, MEASURED IN $^NetMeasure_Income_Farm^USDollar +INCOME, NET CASH FARM, OF OPERATIONS - NET INCOME, MEASURED IN $ / OPERATION^Mean_NetMeasure_Income_Farm^USDollarPerFarm +CATTLE, INCL CALVES - OPERATIONS WITH INVENTORY^Count_Farm_CattleAndCalves +CATTLE, INCL CALVES - INVENTORY^Count_FarmInventory_CattleAndCalves +CATTLE, COWS, BEEF - OPERATIONS WITH INVENTORY^Count_Farm_BeefCows +CATTLE, COWS, BEEF - INVENTORY^Count_FarmInventory_BeefCows +CATTLE, COWS, MILK - OPERATIONS WITH INVENTORY^Count_Farm_MilkCows +CATTLE, COWS, MILK - INVENTORY^Count_FarmInventory_MilkCows +CATTLE, INCL CALVES - OPERATIONS WITH SALES^Count_Farm_InventorySold_CattleAndCalves +CATTLE, INCL CALVES - SALES, MEASURED IN HEAD^QuantitySold_FarmInventory_CattleAndCalves +HOGS - OPERATIONS WITH INVENTORY^Count_Farm_HogsAndPigs +HOGS - INVENTORY^Count_FarmInventory_HogsAndPigs +HOGS - OPERATIONS WITH SALES^Count_Farm_InventorySold_HogsAndPigs +HOGS - SALES, MEASURED IN HEAD^QuantitySold_FarmInventory_HogsAndPigs +SHEEP, INCL LAMBS - OPERATIONS WITH INVENTORY^Count_Farm_SheepAndLambs +SHEEP, INCL LAMBS - INVENTORY^Count_FarmInventory_SheepAndLambs +CHICKENS, LAYERS - OPERATIONS WITH INVENTORY^Count_Farm_Layers +CHICKENS, LAYERS - INVENTORY^Count_FarmInventory_Layers +CHICKENS, BROILERS - OPERATIONS WITH SALES^Count_Farm_Broilers +CHICKENS, BROILERS - SALES, MEASURED IN HEAD^Count_FarmInventory_Broilers +CORN, GRAIN - OPERATIONS WITH AREA HARVESTED^Count_Farm_CornForGrain +CORN, GRAIN - ACRES HARVESTED^Area_Farm_CornForGrain^Acre +CORN, GRAIN - PRODUCTION, MEASURED IN BU^Amout_FarmInventory_CornForGrain^Bushel +CORN, SILAGE - OPERATIONS WITH AREA HARVESTED^Count_Farm_CornForSilageOrGreenchop +CORN, SILAGE - ACRES HARVESTED^Area_Farm_CornForSilageOrGreenchop^Acre +CORN, SILAGE - PRODUCTION, MEASURED IN TONS^Amount_FarmInventory_CornForSilageOrGreenchop^Ton +WHEAT - OPERATIONS WITH AREA HARVESTED^Count_Farm_WheatForGrain +WHEAT - ACRES HARVESTED^Area_Farm_WheatForGrain^Acre +WHEAT - PRODUCTION, MEASURED IN BU^Amount_FarmInventory_WheatForGrain^Bushel +WHEAT, SPRING, DURUM - OPERATIONS WITH AREA HARVESTED^Count_Farm_DurumWheatForGrain +WHEAT, SPRING, DURUM - ACRES HARVESTED^Area_Farm_DurumWheatForGrain^Acre +WHEAT, SPRING, DURUM - PRODUCTION, MEASURED IN BU^Amount_FarmInventory_DurumWheatForGrain^Bushel +WHEAT, SPRING, (EXCL DURUM) - OPERATIONS WITH AREA HARVESTED^Count_Farm_OtherSpringWheatForGrain +WHEAT, SPRING, (EXCL DURUM) - ACRES HARVESTED^Area_Farm_OtherSpringWheatForGrain^Acre +WHEAT, SPRING, (EXCL DURUM) - PRODUCTION, MEASURED IN BU^Amount_FarmInventory_OtherSpringWheatForGrain^Bushel +WHEAT, WINTER - OPERATIONS WITH AREA HARVESTED^Count_Farm_WinterWheatForGrain +WHEAT, WINTER - ACRES HARVESTED^Area_Farm_WinterWheatForGrain^Acre +WHEAT, WINTER - PRODUCTION, MEASURED IN BU^AmountFarmInventory_WinterWheatForGrain^Bushel +OATS - OPERATIONS WITH AREA HARVESTED^Count_Farm_OatsForGrain +OATS - ACRES HARVESTED^Area_Farm_OatsForGrain^Acre +OATS - PRODUCTION, MEASURED IN BU^Amount_FarmInventory_OatsForGrain^Bushel +BARLEY - OPERATIONS WITH AREA HARVESTED^Count_Farm_BarleyForGrain +BARLEY - ACRES HARVESTED^Area_Farm_BarleyForGrain^Acre +BARLEY - PRODUCTION, MEASURED IN BU^Amount_FarmInventory_BarleyForGrain^Bushel +SORGHUM, GRAIN - OPERATIONS WITH AREA HARVESTED^Count_Farm_SorghumForGrain +SORGHUM, GRAIN - ACRES HARVESTED^Area_Farm_SorghumForGrain^Acre +SORGHUM, GRAIN - PRODUCTION, MEASURED IN BU^Amount_FarmInventory_SorghumForGrain^Bushel +SORGHUM, SILAGE - OPERATIONS WITH AREA HARVESTED^Count_Farm_SorghumForSilageOrGreenchop +SORGHUM, SILAGE - ACRES HARVESTED^Area_Farm_SorghumForSilageOrGreenchop^Acre +SORGHUM, SILAGE - PRODUCTION, MEASURED IN TONS^Amount_FarmInventory_SorghumForSilageOrGreenchop^Ton +BEANS, DRY EDIBLE, (EXCL CHICKPEAS & LIMA) - OPERATIONS WITH AREA HARVESTED^Count_Farm_DryEdibleBeans +BEANS, DRY EDIBLE, (EXCL CHICKPEAS & LIMA) - ACRES HARVESTED^Area_Farm_DryEdibleBeans^Acre +BEANS, DRY EDIBLE, (EXCL CHICKPEAS & LIMA) - PRODUCTION, MEASURED IN CWT^Amount_FarmInventory_DryEdibleBeans^Hundredweight +COTTON - OPERATIONS WITH AREA HARVESTED^Count_Farm_Cotton +COTTON - ACRES HARVESTED^Area_Farm_Cotton^Acre +COTTON - PRODUCTION, MEASURED IN BALES^Amount_FarmInventory_Cotton^Bale +COTTON, UPLAND - OPERATIONS WITH AREA HARVESTED^Count_Farm_UplandCotton +COTTON, UPLAND - ACRES HARVESTED^Area_Farm_UplandCotton^Acre +COTTON, UPLAND - PRODUCTION, MEASURED IN BALES^Amount_FarmInventory_UplandCotton^Bale +COTTON, PIMA - OPERATIONS WITH AREA HARVESTED^Count_Farm_PimaCotton +COTTON, PIMA - ACRES HARVESTED^Area_Farm_PimaCotton^Acre +COTTON, PIMA - PRODUCTION, MEASURED IN BALES^Amount_FarmInventory_PimaCotton^Bale +HAY & HAYLAGE - OPERATIONS WITH AREA HARVESTED^Count_Farm_Forage +HAY & HAYLAGE - ACRES HARVESTED^Area_Farm_Forage^Acre +HAY & HAYLAGE - PRODUCTION, MEASURED IN TONS, DRY BASIS^Amount_FarmInventory_Forage^Ton +RICE - OPERATIONS WITH AREA HARVESTED^Count_Farm_Rice +RICE - ACRES HARVESTED^Area_Farm_Rice^Acre +RICE - PRODUCTION, MEASURED IN CWT^Amount_FarmInventory_Rice^Hundredweight +SUNFLOWER - OPERATIONS WITH AREA HARVESTED^Count_Farm_SunflowerSeed +SUNFLOWER - ACRES HARVESTED^Area_Farm_SunflowerSeed^Acre +SUNFLOWER - PRODUCTION, MEASURED IN LB^Amount_FarmInventory_SunflowerSeed^Pound +SUGARBEETS - OPERATIONS WITH AREA HARVESTED^Count_Farm_SugarbeetsForSugar +SUGARBEETS - ACRES HARVESTED^Area_Farm_SugarbeetsForSugar^Acre +SUGARBEETS - PRODUCTION, MEASURED IN TONS^Amount_FarmInventory_SugarbeetsForSugar^Ton +PEANUTS - OPERATIONS WITH AREA HARVESTED^Count_Farm_PeanutsForNuts +PEANUTS - ACRES HARVESTED^Area_Farm_PeanutsForNuts^Acre +PEANUTS - PRODUCTION, MEASURED IN LB^Amount_FarmInventory_PeanutsForNuts^Pound +VEGETABLE TOTALS, IN THE OPEN - OPERATIONS WITH AREA HARVESTED^Count_Farm_VegetablesHarvestedForSale +VEGETABLE TOTALS, IN THE OPEN - ACRES HARVESTED^Area_Farm_VegetablesHarvestedForSale^Acre +POTATOES - OPERATIONS WITH AREA HARVESTED^Count_Farm_Potatoes +POTATOES - ACRES HARVESTED^Area_Farm_Potatoes^Acre +SWEET POTATOES - OPERATIONS WITH AREA HARVESTED^Count_Farm_SweetPotatoes +SWEET POTATOES - ACRES HARVESTED^Area_Farm_SweetPotatoes^Acre +ORCHARDS - OPERATIONS WITH AREA BEARING & NON-BEARING^Count_Farm_Orchards +ORCHARDS - ACRES BEARING & NON-BEARING^Area_Farm_Orchards^Acre +PRODUCERS, HISPANIC - NUMBER OF OPERATIONS^Count_Farm_Producer_HispanicOrLatino +PRODUCERS, HISPANIC - NUMBER OF PRODUCERS^Count_Person_Producer_HispanicOrLatino +PRODUCERS, HISPANIC - ACRES OPERATED^Area_Farm_Producer_HispanicOrLatino^Acre +PRODUCERS, PRINCIPAL, HISPANIC - NUMBER OF OPERATIONS^Count_Farm_PrimaryProducer_HispanicOrLatino +PRODUCERS, PRINCIPAL, HISPANIC - ACRES OPERATED^Area_Farm_PrimaryProducer_HispanicOrLatino^Acre +PRODUCERS, AMERICAN INDIAN OR ALASKA NATIVE - NUMBER OF OPERATIONS^Count_Farm_Producer_AmericanIndianOrAlaskaNativeAlone +PRODUCERS, AMERICAN INDIAN OR ALASKA NATIVE - NUMBER OF PRODUCERS^Count_Person_Producer_AmericanIndianOrAlaskaNativeAlone +PRODUCERS, AMERICAN INDIAN OR ALASKA NATIVE - ACRES OPERATED^Area_Farm_Producer_AmericanIndianOrAlaskaNativeAlone^Acre +PRODUCERS, PRINCIPAL, AMERICAN INDIAN OR ALASKA NATIVE - NUMBER OF OPERATIONS^Count_Farm_PrimaryProducer_AmericanIndianOrAlaskaNativeAlone +PRODUCERS, PRINCIPAL, AMERICAN INDIAN OR ALASKA NATIVE - ACRES OPERATED^Area_Farm_PrimaryProducer_AmericanIndianOrAlaskaNativeAlone^Acre +PRODUCERS, ASIAN - NUMBER OF OPERATIONS^Count_Farm_Producer_AsianAlone +PRODUCERS, ASIAN - NUMBER OF PRODUCERS^Count_Person_Producer_AsianAlone +PRODUCERS, ASIAN - ACRES OPERATED^Area_Farm_Producer_AsianAlone^Acre +PRODUCERS, PRINCIPAL, ASIAN - NUMBER OF OPERATIONS^Count_Farm_PrimaryProducer_AsianAlone +PRODUCERS, PRINCIPAL, ASIAN - ACRES OPERATED^Area_Farm_PrimaryProducer_AsianAlone^Acre +PRODUCERS, BLACK OR AFRICAN AMERICAN - NUMBER OF OPERATIONS^Count_Farm_Producer_BlackOrAfricanAmericanAlone +PRODUCERS, BLACK OR AFRICAN AMERICAN - NUMBER OF PRODUCERS^Count_Person_Producer_BlackOrAfricanAmericanAlone +PRODUCERS, BLACK OR AFRICAN AMERICAN - ACRES OPERATED^Area_Farm_Producer_BlackOrAfricanAmericanAlone^Acre +PRODUCERS, PRINCIPAL, BLACK OR AFRICAN AMERICAN - NUMBER OF OPERATIONS^Count_Farm_PrimaryProducer_BlackOrAfricanAmericanAlone +PRODUCERS, PRINCIPAL, BLACK OR AFRICAN AMERICAN - ACRES OPERATED^Area_Farm_PrimaryProducer_BlackOrAfricanAmericanAlone^Acre +PRODUCERS, NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER - NUMBER OF OPERATIONS^Count_Farm_Producer_NativeHawaiianOrOtherPacificIslanderAlone +PRODUCERS, NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER - NUMBER OF PRODUCERS^Count_Person_Producer_NativeHawaiianOrOtherPacificIslanderAlone +PRODUCERS, NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER - ACRES OPERATED^Area_Farm_Producer_NativeHawaiianOrOtherPacificIslanderAlone^Acre +PRODUCERS, PRINCIPAL, NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER - NUMBER OF OPERATIONS^Count_Farm_PrimaryProducer_NativeHawaiianOrOtherPacificIslanderAlone +PRODUCERS, PRINCIPAL, NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER - ACRES OPERATED^Area_Farm_PrimaryProducer_NativeHawaiianOrOtherPacificIslanderAlone^Acre +PRODUCERS, WHITE - NUMBER OF OPERATIONS^Count_Farm_Producer_WhiteAlone +PRODUCERS, WHITE - NUMBER OF PRODUCERS^Count_Person_Producer_WhiteAlone +PRODUCERS, WHITE - ACRES OPERATED^Area_Farm_Producer_WhiteAlone^Acre +PRODUCERS, PRINCIPAL, WHITE - NUMBER OF OPERATIONS^Count_Farm_PrimaryProducer_WhiteAlone +PRODUCERS, PRINCIPAL, WHITE - ACRES OPERATED^Area_Farm_PrimaryProducer_WhiteAlone^Acre +PRODUCERS, MULTI-RACE - NUMBER OF OPERATIONS^Count_Farm_Producer_TwoOrMoreRaces +PRODUCERS, MULTI-RACE - NUMBER OF PRODUCERS^Count_Person_Producer_TwoOrMoreRaces +PRODUCERS, MULTI-RACE - ACRES OPERATED^Area_Farm_Producer_TwoOrMoreRaces^Acre +PRODUCERS, PRINCIPAL, MULTI-RACE - NUMBER OF OPERATIONS^Count_Farm_PrimaryProducer_TwoOrMoreRaces +PRODUCERS, PRINCIPAL, MULTI-RACE - ACRES OPERATED^Area_Farm_PrimaryProducer_TwoOrMoreRaces^Acre diff --git a/scripts/us_usda/nass_census/testdata/expected.csv b/scripts/us_usda/nass_census/testdata/expected.csv new file mode 100644 index 0000000000..574d355daa --- /dev/null +++ b/scripts/us_usda/nass_census/testdata/expected.csv @@ -0,0 +1,11 @@ +variableMeasured,observationAbout,value,unit +dcs:Count_Farm,dcid:country/USA,2042220, +dcs:Area_Farm,dcid:country/USA,900217576,dcs:Acre +dcs:Mean_Area_Farm,dcid:country/USA,441,dcs:Acre +dcs:Mean_MarketValue_Farm_LandAndBuildings,dcid:country/USA,1311808,dcs:USDollarPerFarm +dcs:Mean_MarketValue_Farm_LandAndBuildings,dcid:country/USA,2976,dcs:USDollarPerAcre +dcs:Count_Farm_Producer_HispanicOrLatino,dcid:country/USA,86278, +dcs:Count_Farm_PrimaryProducer_HispanicOrLatino,dcid:country/USA,77416, +dcs:Area_Farm_Producer_HispanicOrLatino,dcid:country/USA,32079910,dcs:Acre +dcs:Area_Farm_PrimaryProducer_HispanicOrLatino,dcid:country/USA,26041600,dcs:Acre +dcs:Count_Person_Producer_HispanicOrLatino,dcid:country/USA,112451, diff --git a/scripts/us_usda/nass_census/testdata/input.csv b/scripts/us_usda/nass_census/testdata/input.csv new file mode 100644 index 0000000000..de64bb03df --- /dev/null +++ b/scripts/us_usda/nass_census/testdata/input.csv @@ -0,0 +1,11 @@ +CENSUS_CHAPTER CENSUS_TABLE CENSUS_ROW CENSUS_COLUMN SECTOR_DESC SHORT_DESC COMMODITY_DESC AGG_LEVEL_DESC STATE_FIPS_CODE STATE_ALPHA STATE_NAME COUNTY_CODE COUNTY_NAME DOMAINCAT_DESC VALUE +1 1 1 1 ECONOMICS FARM OPERATIONS - NUMBER OF OPERATIONS FARM OPERATIONS NATIONAL 99 US US TOTAL NULL NULL 2,042,220 +1 1 2 1 ECONOMICS FARM OPERATIONS - ACRES OPERATED FARM OPERATIONS NATIONAL 99 US US TOTAL NULL NULL 900,217,576 +1 1 3 1 ECONOMICS FARM OPERATIONS - AREA OPERATED, MEASURED IN ACRES / OPERATION FARM OPERATIONS NATIONAL 99 US US TOTAL NULL NULL 441 +1 1 4 1 ECONOMICS AG LAND, INCL BUILDINGS - ASSET VALUE, MEASURED IN $ / OPERATION AG LAND NATIONAL 99 US US TOTAL NULL NULL 1,311,808 +1 1 5 1 ECONOMICS AG LAND, INCL BUILDINGS - ASSET VALUE, MEASURED IN $ / ACRE AG LAND NATIONAL 99 US US TOTAL NULL NULL 2,976 +1 59 1 1 DEMOGRAPHICS PRODUCERS, HISPANIC - NUMBER OF OPERATIONS PRODUCERS NATIONAL 99 US US TOTAL NULL NULL 86,278 +1 59 1 2 DEMOGRAPHICS PRODUCERS, PRINCIPAL, HISPANIC - NUMBER OF OPERATIONS PRODUCERS, PRINCIPAL NATIONAL 99 US US TOTAL NULL NULL 77,416 +1 59 2 1 DEMOGRAPHICS PRODUCERS, HISPANIC - ACRES OPERATED PRODUCERS NATIONAL 99 US US TOTAL NULL NULL 32,079,910 +1 59 2 2 DEMOGRAPHICS PRODUCERS, PRINCIPAL, HISPANIC - ACRES OPERATED PRODUCERS, PRINCIPAL NATIONAL 99 US US TOTAL NULL NULL 26,041,600 +1 60 1 1 DEMOGRAPHICS PRODUCERS, HISPANIC - NUMBER OF PRODUCERS PRODUCERS NATIONAL 99 US US TOTAL NULL NULL 112,451 diff --git a/scripts/us_usda/quickstats/.gitignore b/scripts/us_usda/quickstats/.gitignore new file mode 100644 index 0000000000..1c37506365 --- /dev/null +++ b/scripts/us_usda/quickstats/.gitignore @@ -0,0 +1,2 @@ +/output/ +dc_generated \ No newline at end of file diff --git a/scripts/us_usda/quickstats/README.md b/scripts/us_usda/quickstats/README.md new file mode 100644 index 0000000000..72f13fba76 --- /dev/null +++ b/scripts/us_usda/quickstats/README.md @@ -0,0 +1,20 @@ +The `process.py` script generates statvars based on the +USDA agriculture survey (and census data very soon) data +using the USDA quickstats [API][api]. + +[api]: https://quickstats.nass.usda.gov/api/ + +To generate CSV: +``` +python3 process.py +``` + +The output will be `output/ag-2023.csv`. + +The latest StatisticalVariable mappings are in `sv.csv`. The CSV fields are as follows: + +* `name`: The "Data Item" in the USDA/NASS QuickStats tool +* `sv`: The corresponding StatisticalVariable dcid +* `unit`: The unit dcid, if it exists + +TODO: Add additional mappings for other StatisticalVariables. \ No newline at end of file diff --git a/scripts/us_usda/quickstats/ag.tmcf b/scripts/us_usda/quickstats/ag.tmcf new file mode 100644 index 0000000000..69f8319733 --- /dev/null +++ b/scripts/us_usda/quickstats/ag.tmcf @@ -0,0 +1,8 @@ +Node: E:USDA_AgricultureSurvey->E0 +typeOf: dcs:StatVarObservation +variableMeasured: C:USDA_AgricultureSurvey->variableMeasured +observationDate: C:USDA_AgricultureSurvey->observationDate +observationAbout: C:USDA_AgricultureSurvey->observationAbout +observationPeriod: "P1Y" +value: C:USDA_AgricultureSurvey->value +unit: C:USDA_AgricultureSurvey->unit \ No newline at end of file diff --git a/scripts/us_usda/quickstats/manifest.json b/scripts/us_usda/quickstats/manifest.json new file mode 100644 index 0000000000..53032776a5 --- /dev/null +++ b/scripts/us_usda/quickstats/manifest.json @@ -0,0 +1,16 @@ +{ + "import_specifications": [ + { + "import_name": "UsdaAgSurvey", + "curator_emails": ["keyurs@google.com"], + "provenance_url": "https://quickstats.nass.usda.gov/api/", + "provenance_description": "The National Agricultural Statistics Service (NASS) offers Quick Stats, an on-line database containing official published aggregate estimates related to U.S. agricultural production.", + "scripts": ["process.py"], + "import_inputs": [{ + "template_mcf": "ag.tmcf", + "cleaned_csv": "output/consolidated.csv" + }], + "cron_schedule": "0 10 * * 2" + } + ] +} diff --git a/scripts/us_usda/quickstats/process.py b/scripts/us_usda/quickstats/process.py new file mode 100644 index 0000000000..b0db6fb150 --- /dev/null +++ b/scripts/us_usda/quickstats/process.py @@ -0,0 +1,314 @@ +# Copyright 2021 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Import USDA Agriculture Survey data. + +To run this script, specify a USDA api key as follows: + +python3 process.py --usda_api_key= + +You can request an API key here: https://quickstats.nass.usda.gov/api/ + +If the key is not specified as above, it falls back to using a key specified +in a GCS config file. However, that file is available to DC team members only. + +""" + +import json + +import requests +import sys +import csv +import multiprocessing +from itertools import repeat +import os +from datetime import datetime +from google.cloud import storage +from absl import app +from absl import flags + +API_BASE = 'https://quickstats.nass.usda.gov/api' + +CSV_COLUMNS = [ + 'variableMeasured', + 'observationDate', + 'observationAbout', + 'value', + 'unit', +] + +SKIPPED_VALUES = {'(D)', '(Z)'} + +SKIPPED_COUNTY_CODES = set([ + '998', # "OTHER" county code +]) + +_GCS_PROJECT_ID = "datcom-204919" +_GCS_BUCKET = "datcom-csv" +_GCS_FILE_PATH = "usda/agriculture_survey/config.json" + +_USDA_API_KEY = 'usda_api_key' + +_FLAGS = flags.FLAGS + +flags.DEFINE_string(_USDA_API_KEY, None, 'USDA quickstats API key.') + + +def process_survey_data(year, svs, out_dir): + start = datetime.now() + print('Start', year, '=', start) + + os.makedirs(get_parts_dir(out_dir, year), exist_ok=True) + os.makedirs(get_response_dir(out_dir, year), exist_ok=True) + + print('Processing survey data for year', year) + + print('Getting county names') + county_names = get_param_values('county_name') + print('# counties =', len(county_names)) + + pool_size = max(2, multiprocessing.cpu_count() - 1) + + with multiprocessing.Pool(pool_size) as pool: + pool.starmap( + fetch_and_write, + zip(county_names, repeat(year), repeat(svs), repeat(out_dir))) + + write_aggregate_csv(year, out_dir) + + end = datetime.now() + print('End', year, '=', end) + print('Duration', year, '=', str(end - start)) + + +def get_parts_dir(out_dir, year): + return f'{out_dir}/parts/{year}' + + +def get_response_dir(out_dir, year): + return f"{out_dir}/response/{year}" + + +def get_response_file_path(out_dir, year, county): + return f"{get_response_dir(out_dir, year)}/{county}.json" + + +def get_year_csv_file_path(out_dir, year): + return f"{out_dir}/ag-{year}.csv" + + +def write_aggregate_csv(year, out_dir): + parts_dir = get_parts_dir(out_dir, year) + part_files = os.listdir(parts_dir) + out_file = get_year_csv_file_path(out_dir, year) + + print('Writing aggregate CSV', out_file) + + with open(out_file, 'w', newline='') as out: + csv_writer = csv.DictWriter(out, + fieldnames=CSV_COLUMNS, + lineterminator='\n') + csv_writer.writeheader() + for part_file in part_files: + if part_file.endswith(".csv"): + with open(f"{parts_dir}/{part_file}", 'r') as part: + csv_writer.writerows(csv.DictReader(part)) + + +def write_consolidated_csv(years, out_dir): + out_file = f"{out_dir}/consolidated.csv" + + print('Writing consolidated CSV', out_file) + + with open(out_file, 'w', newline='') as out: + csv_writer = csv.DictWriter(out, + fieldnames=CSV_COLUMNS, + lineterminator='\n') + csv_writer.writeheader() + for year in years: + with open(get_year_csv_file_path(out_dir, year), 'r') as part: + csv_writer.writerows(csv.DictReader(part)) + + +def fetch_and_write(county_name, year, svs, out_dir): + out_file = f"{get_parts_dir(out_dir, year)}/{county_name.replace('[^a-zA-Z0-9]', '')}.csv" + api_data = get_survey_county_data(year, county_name, out_dir) + county_csv_rows = to_csv_rows(api_data, svs) + print('Writing', len(county_csv_rows), 'rows for county', county_name, + 'to file', out_file) + with open(out_file, 'w', newline='') as out: + write_csv(out, county_csv_rows) + + +def get_survey_county_data(year, county, out_dir): + print('Getting', year, 'survey data for county', county) + + response_file = get_response_file_path(out_dir, year, county) + if os.path.exists(response_file): + print('Reading response from file', response_file) + with open(response_file, 'r') as f: + response = json.load(f) + else: + params = { + 'key': get_usda_api_key(), + 'source_desc': "SURVEY", + 'year': year, + 'county_name': county + } + response = get_data(params) + with open(response_file, 'w') as f: + print('Writing response to file', response_file) + json.dump(response, f, indent=2) + + if 'data' not in response: + eprint('No api records found for county', county) + return {'data': []} + + print('# api records for', county, '=', len(response['data'])) + return response + + +def get_data(params): + return requests.get(f'{API_BASE}/api_GET', params=params).json() + + +def get_param_values(param): + params = {'key': get_usda_api_key(), 'param': param} + response = requests.get(f'{API_BASE}/get_param_values', + params=params).json() + return [] if param not in response else response[param] + + +'''Converts a quickstats data row to a DC CSV row. + +data = quickstats data row +svs = {name: {name: ..., sv: ..., unit: ...}} + +returns = {variableMeasured: ..., observationAbout: ..., value: ..., unit: ...} +''' + + +def to_csv_row(data_row, svs): + name = data_row['short_desc'] + if data_row['domaincat_desc'] and data_row[ + 'domaincat_desc'] != 'NOT SPECIFIED': + name = f"{name}%%{data_row['domaincat_desc']}" + + if name not in svs: + eprint('SKIPPED, No SV mapped for', name) + return None + + county_code = data_row['county_code'] + if county_code in SKIPPED_COUNTY_CODES: + eprint('SKIPPED, Unsupported county code', county_code) + return None + + value = (data_row['value'] if 'value' in data_row else + data_row['Value']).strip().replace(',', '') + if value in SKIPPED_VALUES: + eprint('SKIPPED, Invalid value', f"'{value}'", 'for', name) + return None + value = int(value) + + observation_about = f"dcid:geoId/{data_row['state_fips_code']}{county_code}" if \ + data_row[ + 'state_fips_code'] else 'dcid:country/USA' + + sv = svs[name] + + return { + 'variableMeasured': sv['sv'], + 'observationDate': data_row['year'], + 'observationAbout': observation_about, + 'value': value, + 'unit': sv['unit'], + } + + +def to_csv_rows(api_data, svs): + csv_rows = [] + + for data_row in api_data['data']: + csv_row = to_csv_row(data_row, svs) + if csv_row: + csv_rows.append(csv_row) + + return csv_rows + + +def load_svs(): + svs = {} + with open("sv.csv", newline='') as csvfile: + reader = csv.DictReader(csvfile) + for row in reader: + svs[row['name']] = row + return svs + + +def write_csv(out, rows): + writer = csv.DictWriter(out, fieldnames=CSV_COLUMNS, lineterminator='\n') + writer.writeheader() + writer.writerows(rows) + + +def eprint(*args, **kwargs): + print(*args, file=sys.stderr, **kwargs) + + +def get_all_counties(): + svs = load_svs() + process_survey_data(2023, svs, "output") + + +def get_multiple_years(): + start = datetime.now() + print('Start', start) + + out_dir = "output" + svs = load_svs() + years = range(2000, datetime.now().year + 1) + for year in years: + process_survey_data(year, svs, out_dir) + + write_consolidated_csv(years, out_dir) + + end = datetime.now() + print('End', end) + print('Duration', str(end - start)) + + +def get_cloud_config(): + print('Getting cloud config.') + storage_client = storage.Client(_GCS_PROJECT_ID) + bucket = storage_client.bucket(_GCS_BUCKET) + blob = bucket.blob(_GCS_FILE_PATH) + return json.loads(blob.download_as_string(client=None)) + + +def load_usda_api_key(): + if get_usda_api_key() is None: + _FLAGS.set_default(_USDA_API_KEY, get_cloud_config()[_USDA_API_KEY]) + + +def get_usda_api_key(): + return _FLAGS.usda_api_key + + +def main(_): + load_usda_api_key() + print('USDA API key', get_usda_api_key()) + get_multiple_years() + + +if __name__ == '__main__': + app.run(main) diff --git a/scripts/us_usda/quickstats/process_test.py b/scripts/us_usda/quickstats/process_test.py new file mode 100644 index 0000000000..61bb4fe8e1 --- /dev/null +++ b/scripts/us_usda/quickstats/process_test.py @@ -0,0 +1,39 @@ +# Copyright 2021 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for process.py""" + +import csv +import io +import unittest +from process import to_csv_rows, get_survey_county_data, write_csv, load_svs + + +class ProcessTest(unittest.TestCase): + + def test_write_csv(self): + expected = None + with open('testdata/expected.csv') as f: + expected = f.read() + + svs = load_svs() + api_data = get_survey_county_data(2022, 'ALAMEDA', 'testdata') + csv_rows = to_csv_rows(api_data, svs) + out = io.StringIO() + print(csv_rows) + write_csv(out, csv_rows) + self.assertEqual(expected, out.getvalue()) + + +if __name__ == '__main__': + unittest.main() diff --git a/scripts/us_usda/quickstats/sv.csv b/scripts/us_usda/quickstats/sv.csv new file mode 100644 index 0000000000..43d9b67a4a --- /dev/null +++ b/scripts/us_usda/quickstats/sv.csv @@ -0,0 +1,159 @@ +name,sv,unit +FARM OPERATIONS - NUMBER OF OPERATIONS,dcs:Count_Farm, +FARM OPERATIONS - NUMBER OF OPERATIONS%%AREA OPERATED: (1.0 TO 9.9 ACRES),dcs:Count_Farm_1To9.9Acre, +FARM OPERATIONS - NUMBER OF OPERATIONS%%AREA OPERATED: (10.0 TO 49.9 ACRES),dcs:Count_Farm_10To49.9Acre, +FARM OPERATIONS - NUMBER OF OPERATIONS%%AREA OPERATED: (50 TO 179 ACRES),dcs:Count_Farm_50To179Acre, +FARM OPERATIONS - NUMBER OF OPERATIONS%%AREA OPERATED: (180 TO 499 ACRES),dcs:Count_Farm_180To499Acre, +FARM OPERATIONS - NUMBER OF OPERATIONS%%AREA OPERATED: (500 TO 999 ACRES),dcs:Count_Farm_500To999Acre, +"FARM OPERATIONS - NUMBER OF OPERATIONS%%AREA OPERATED: (1,000 OR MORE ACRES)",dcs:Count_1000OnwardsAcre, +FARM OPERATIONS - ACRES OPERATED,dcs:Area_Farm,dcs:Acre +"FARM OPERATIONS - AREA OPERATED, MEASURED IN ACRES / OPERATION",dcs:Mean_Area_Farm,dcs:Acre +"FARM OPERATIONS - AREA OPERATED, MEASURED IN ACRES / OPERATION, MEDIAN",dcs:Median_Area_Farm,dcs:Acre +"AG LAND, INCL BUILDINGS - ASSET VALUE, MEASURED IN $ / OPERATION",dcs:Mean_MarketValue_Farm_LandAndBuildings,dcs:USDollarPerFarm +"AG LAND, INCL BUILDINGS - ASSET VALUE, MEASURED IN $ / ACRE",dcs:Mean_MarketValue_Farm_LandAndBuildings,dcs:USDollarPerAcre +"MACHINERY TOTALS - ASSET VALUE, MEASURED IN $",dcs:MarketValue_Farm_MachinferyAndEquipment,dcs:USDollar +"MACHINERY TOTALS - ASSET VALUE, MEASURED IN $ / OPERATION",dcs:Mean_MarketValue_Farm_MachineryAndEquipment,dcs:USDollarPerFarm +"AG LAND, CROPLAND - NUMBER OF OPERATIONS",dcs:Count_Farm_Cropland, +"AG LAND, CROPLAND - ACRES",dcs:Area_Farm_Cropland,dcs:Acre +"AG LAND, CROPLAND, HARVESTED - NUMBER OF OPERATIONS",dcs:Count_Farm_HarvestedCropland, +"AG LAND, CROPLAND, HARVESTED - ACRES",dcs:Area_Farm_HarvestedCropland,dcs:Acre +"AG LAND, IRRIGATED - NUMBER OF OPERATIONS",dcs:Count_Farm_IrrigatedLand, +"AG LAND, IRRIGATED - ACRES",dcs:Area_Farm_IrrigatedLand,dcs:Acre +"COMMODITY TOTALS - SALES, MEASURED IN $",dcs:MarketValue_Farm_AgriculturalProducts,dcs:USDollar +"COMMODITY TOTALS - SALES, MEASURED IN $ / OPERATION",dcs:Mean_MarketValue_Farm_AgriculturalProducts,dcs:USDollarPerFarm +"CROP TOTALS - SALES, MEASURED IN $",dcs:MarketValue_Farm_Crops,dcs:USDollar +"ANIMAL TOTALS, INCL PRODUCTS - SALES, MEASURED IN $",dcs:MarketValue_Farm_LivestockAndPoultry,dcs:USDollar +"COMMODITY TOTALS - OPERATIONS WITH SALES%%FARM SALES: (LESS THAN 2,500 $)",dcs:Count_Farm_Upto1000USDollar, +"COMMODITY TOTALS - OPERATIONS WITH SALES%%FARM SALES: (2,500 TO 4,999 $)",dcs:Count_Farm_2500To4999USDollar, +"COMMODITY TOTALS - OPERATIONS WITH SALES%%FARM SALES: (5,000 TO 9,999 $)",dcs:Count_Farm_5000To9999USDollar, +"COMMODITY TOTALS - OPERATIONS WITH SALES%%FARM SALES: (10,000 TO 24,999 $)",dcs:Count_Farm_10000To24999USDollar, +"COMMODITY TOTALS - OPERATIONS WITH SALES%%FARM SALES: (25,000 TO 49,999 $)",dcs:Count_Farm_25000To49999USDollar, +"COMMODITY TOTALS - OPERATIONS WITH SALES%%FARM SALES: (50,000 TO 99,999 $)",dcs:Count_Farm_50000To99999USDollar, +"COMMODITY TOTALS - OPERATIONS WITH SALES%%FARM SALES: (100,000 OR MORE $)",dcs:Count_Farm_100000OnwardsUSDollar, +"GOVT PROGRAMS, FEDERAL - OPERATIONS WITH RECEIPTS",dcs:Count_Farm_ReceivedGovernmentPayment, +"GOVT PROGRAMS, FEDERAL - RECEIPTS, MEASURED IN $",dcs:MonetaryValue_Farm_GovernmentPayment,dcs:USDollar +"INCOME, FARM-RELATED - OPERATIONS WITH RECEIPTS",dcs:Count_Farm_ReportedIncome, +"INCOME, FARM-RELATED - RECEIPTS, MEASURED IN $",dcs:Income_Farm,dcs:USDollar +"EXPENSE TOTALS, OPERATING - EXPENSE, MEASURED IN $",dcs:Expenses_Farm,dcs:USDollar +"EXPENSE TOTALS, OPERATING - EXPENSE, MEASURED IN $ / OPERATION",dcs:Mean_Expenses_Farm,dcs:USDollarPerFarm +"INCOME, NET CASH FARM, OF OPERATIONS - OPERATIONS WITH NET INCOME",dcs:Count_Farm_ReportedNetIncome, +"INCOME, NET CASH FARM, OF OPERATIONS - NET INCOME, MEASURED IN $",dcs:NetMeasure_Income_Farm,dcs:USDollar +"INCOME, NET CASH FARM, OF OPERATIONS - NET INCOME, MEASURED IN $ / OPERATION",dcs:Mean_NetMeasure_Income_Farm,dcs:USDollarPerFarm +"CATTLE, INCL CALVES - OPERATIONS WITH INVENTORY",dcs:Count_Farm_CattleAndCalves, +"CATTLE, INCL CALVES - INVENTORY",dcs:Count_FarmInventory_CattleAndCalves, +"CATTLE, COWS, BEEF - OPERATIONS WITH INVENTORY",dcs:Count_Farm_BeefCows, +"CATTLE, COWS, BEEF - INVENTORY",dcs:Count_FarmInventory_BeefCows, +"CATTLE, COWS, MILK - OPERATIONS WITH INVENTORY",dcs:Count_Farm_MilkCows, +"CATTLE, COWS, MILK - INVENTORY",dcs:Count_FarmInventory_MilkCows, +"CATTLE, INCL CALVES - OPERATIONS WITH SALES",dcs:Count_Farm_InventorySold_CattleAndCalves, +"CATTLE, INCL CALVES - SALES, MEASURED IN HEAD",dcs:QuantitySold_FarmInventory_CattleAndCalves, +HOGS - OPERATIONS WITH INVENTORY,dcs:Count_Farm_HogsAndPigs, +HOGS - INVENTORY,dcs:Count_FarmInventory_HogsAndPigs, +HOGS - OPERATIONS WITH SALES,dcs:Count_Farm_InventorySold_HogsAndPigs, +"HOGS - SALES, MEASURED IN HEAD",dcs:QuantitySold_FarmInventory_HogsAndPigs, +"SHEEP, INCL LAMBS - OPERATIONS WITH INVENTORY",dcs:Count_Farm_SheepAndLambs, +"SHEEP, INCL LAMBS - INVENTORY",dcs:Count_FarmInventory_SheepAndLambs, +"CHICKENS, LAYERS - OPERATIONS WITH INVENTORY",dcs:Count_Farm_Layers, +"CHICKENS, LAYERS - INVENTORY",dcs:Count_FarmInventory_Layers, +"CHICKENS, BROILERS - OPERATIONS WITH SALES",dcs:Count_Farm_Broilers, +"CHICKENS, BROILERS - SALES, MEASURED IN HEAD",dcs:Count_FarmInventory_Broilers, +"CORN, GRAIN - OPERATIONS WITH AREA HARVESTED",dcs:Count_Farm_CornForGrain, +"CORN, GRAIN - ACRES HARVESTED",dcs:Area_Farm_CornForGrain,dcs:Acre +"CORN, GRAIN - PRODUCTION, MEASURED IN BU",dcs:Amout_FarmInventory_CornForGrain,dcs:Bushel +"CORN, SILAGE - OPERATIONS WITH AREA HARVESTED",dcs:Count_Farm_CornForSilageOrGreenchop, +"CORN, SILAGE - ACRES HARVESTED",dcs:Area_Farm_CornForSilageOrGreenchop,dcs:Acre +"CORN, SILAGE - PRODUCTION, MEASURED IN TONS",dcs:Amount_FarmInventory_CornForSilageOrGreenchop,dcs:Ton +WHEAT - OPERATIONS WITH AREA HARVESTED,dcs:Count_Farm_WheatForGrain, +WHEAT - ACRES HARVESTED,dcs:Area_Farm_WheatForGrain,dcs:Acre +"WHEAT - PRODUCTION, MEASURED IN BU",dcs:Amount_FarmInventory_WheatForGrain,dcs:Bushel +"WHEAT, SPRING, DURUM - OPERATIONS WITH AREA HARVESTED",dcs:Count_Farm_DurumWheatForGrain, +"WHEAT, SPRING, DURUM - ACRES HARVESTED",dcs:Area_Farm_DurumWheatForGrain,dcs:Acre +"WHEAT, SPRING, DURUM - PRODUCTION, MEASURED IN BU",dcs:Amount_FarmInventory_DurumWheatForGrain,dcs:Bushel +"WHEAT, SPRING, (EXCL DURUM) - OPERATIONS WITH AREA HARVESTED",dcs:Count_Farm_OtherSpringWheatForGrain, +"WHEAT, SPRING, (EXCL DURUM) - ACRES HARVESTED",dcs:Area_Farm_OtherSpringWheatForGrain,dcs:Acre +"WHEAT, SPRING, (EXCL DURUM) - PRODUCTION, MEASURED IN BU",dcs:Amount_FarmInventory_OtherSpringWheatForGrain,dcs:Bushel +"WHEAT, WINTER - OPERATIONS WITH AREA HARVESTED",dcs:Count_Farm_WinterWheatForGrain, +"WHEAT, WINTER - ACRES HARVESTED",dcs:Area_Farm_WinterWheatForGrain,dcs:Acre +"WHEAT, WINTER - PRODUCTION, MEASURED IN BU",dcs:AmountFarmInventory_WinterWheatForGrain,dcs:Bushel +OATS - OPERATIONS WITH AREA HARVESTED,dcs:Count_Farm_OatsForGrain, +OATS - ACRES HARVESTED,dcs:Area_Farm_OatsForGrain,dcs:Acre +"OATS - PRODUCTION, MEASURED IN BU",dcs:Amount_FarmInventory_OatsForGrain,dcs:Bushel +BARLEY - OPERATIONS WITH AREA HARVESTED,dcs:Count_Farm_BarleyForGrain, +BARLEY - ACRES HARVESTED,dcs:Area_Farm_BarleyForGrain,dcs:Acre +"BARLEY - PRODUCTION, MEASURED IN BU",dcs:Amount_FarmInventory_BarleyForGrain,dcs:Bushel +"SORGHUM, GRAIN - OPERATIONS WITH AREA HARVESTED",dcs:Count_Farm_SorghumForGrain, +"SORGHUM, GRAIN - ACRES HARVESTED",dcs:Area_Farm_SorghumForGrain,dcs:Acre +"SORGHUM, GRAIN - PRODUCTION, MEASURED IN BU",dcs:Amount_FarmInventory_SorghumForGrain,dcs:Bushel +"SORGHUM, SILAGE - OPERATIONS WITH AREA HARVESTED",dcs:Count_Farm_SorghumForSilageOrGreenchop, +"SORGHUM, SILAGE - ACRES HARVESTED",dcs:Area_Farm_SorghumForSilageOrGreenchop,dcs:Acre +"SORGHUM, SILAGE - PRODUCTION, MEASURED IN TONS",dcs:Amount_FarmInventory_SorghumForSilageOrGreenchop,dcs:Ton +"BEANS, DRY EDIBLE, (EXCL CHICKPEAS & LIMA) - OPERATIONS WITH AREA HARVESTED",dcs:Count_Farm_DryEdibleBeans, +"BEANS, DRY EDIBLE, (EXCL CHICKPEAS & LIMA) - ACRES HARVESTED",dcs:Area_Farm_DryEdibleBeans,dcs:Acre +"BEANS, DRY EDIBLE, (EXCL CHICKPEAS & LIMA) - PRODUCTION, MEASURED IN CWT",dcs:Amount_FarmInventory_DryEdibleBeans,dcs:Hundredweight +COTTON - OPERATIONS WITH AREA HARVESTED,dcs:Count_Farm_Cotton, +COTTON - ACRES HARVESTED,dcs:Area_Farm_Cotton,dcs:Acre +"COTTON - PRODUCTION, MEASURED IN BALES",dcs:Amount_FarmInventory_Cotton,dcs:Bale +"COTTON, UPLAND - OPERATIONS WITH AREA HARVESTED",dcs:Count_Farm_UplandCotton, +"COTTON, UPLAND - ACRES HARVESTED",dcs:Area_Farm_UplandCotton,dcs:Acre +"COTTON, UPLAND - PRODUCTION, MEASURED IN BALES",dcs:Amount_FarmInventory_UplandCotton,dcs:Bale +"COTTON, PIMA - OPERATIONS WITH AREA HARVESTED",dcs:Count_Farm_PimaCotton, +"COTTON, PIMA - ACRES HARVESTED",dcs:Area_Farm_PimaCotton,dcs:Acre +"COTTON, PIMA - PRODUCTION, MEASURED IN BALES",dcs:Amount_FarmInventory_PimaCotton,dcs:Bale +HAY & HAYLAGE - OPERATIONS WITH AREA HARVESTED,dcs:Count_Farm_Forage, +HAY & HAYLAGE - ACRES HARVESTED,dcs:Area_Farm_Forage,dcs:Acre +"HAY & HAYLAGE - PRODUCTION, MEASURED IN TONS, DRY BASIS",dcs:Amount_FarmInventory_Forage,dcs:Ton +RICE - OPERATIONS WITH AREA HARVESTED,dcs:Count_Farm_Rice, +RICE - ACRES HARVESTED,dcs:Area_Farm_Rice,dcs:Acre +"RICE - PRODUCTION, MEASURED IN CWT",dcs:Amount_FarmInventory_Rice,dcs:Hundredweight +SUNFLOWER - OPERATIONS WITH AREA HARVESTED,dcs:Count_Farm_SunflowerSeed, +SUNFLOWER - ACRES HARVESTED,dcs:Area_Farm_SunflowerSeed,dcs:Acre +"SUNFLOWER - PRODUCTION, MEASURED IN LB",dcs:Amount_FarmInventory_SunflowerSeed,dcs:Pound +SUGARBEETS - OPERATIONS WITH AREA HARVESTED,dcs:Count_Farm_SugarbeetsForSugar, +SUGARBEETS - ACRES HARVESTED,dcs:Area_Farm_SugarbeetsForSugar,dcs:Acre +"SUGARBEETS - PRODUCTION, MEASURED IN TONS",dcs:Amount_FarmInventory_SugarbeetsForSugar,dcs:Ton +PEANUTS - OPERATIONS WITH AREA HARVESTED,dcs:Count_Farm_PeanutsForNuts, +PEANUTS - ACRES HARVESTED,dcs:Area_Farm_PeanutsForNuts,dcs:Acre +"PEANUTS - PRODUCTION, MEASURED IN LB",dcs:Amount_FarmInventory_PeanutsForNuts,dcs:Pound +"VEGETABLE TOTALS, IN THE OPEN - OPERATIONS WITH AREA HARVESTED",dcs:Count_Farm_VegetablesHarvestedForSale, +"VEGETABLE TOTALS, IN THE OPEN - ACRES HARVESTED",dcs:Area_Farm_VegetablesHarvestedForSale,dcs:Acre +POTATOES - OPERATIONS WITH AREA HARVESTED,dcs:Count_Farm_Potatoes, +POTATOES - ACRES HARVESTED,dcs:Area_Farm_Potatoes,dcs:Acre +SWEET POTATOES - OPERATIONS WITH AREA HARVESTED,dcs:Count_Farm_SweetPotatoes, +SWEET POTATOES - ACRES HARVESTED,dcs:Area_Farm_SweetPotatoes,dcs:Acre +ORCHARDS - OPERATIONS WITH AREA BEARING & NON-BEARING,dcs:Count_Farm_Orchards, +ORCHARDS - ACRES BEARING & NON-BEARING,dcs:Area_Farm_Orchards,dcs:Acre +"PRODUCERS, HISPANIC - NUMBER OF OPERATIONS",dcs:Count_Farm_Producer_HispanicOrLatino, +"PRODUCERS, HISPANIC - NUMBER OF PRODUCERS",dcs:Count_Person_Producer_HispanicOrLatino, +"PRODUCERS, HISPANIC - ACRES OPERATED",dcs:Area_Farm_Producer_HispanicOrLatino,dcs:Acre +"PRODUCERS, PRINCIPAL, HISPANIC - NUMBER OF OPERATIONS",dcs:Count_Farm_PrimaryProducer_HispanicOrLatino, +"PRODUCERS, PRINCIPAL, HISPANIC - ACRES OPERATED",dcs:Area_Farm_PrimaryProducer_HispanicOrLatino,dcs:Acre +"PRODUCERS, AMERICAN INDIAN OR ALASKA NATIVE - NUMBER OF OPERATIONS",dcs:Count_Farm_Producer_AmericanIndianOrAlaskaNativeAlone, +"PRODUCERS, AMERICAN INDIAN OR ALASKA NATIVE - NUMBER OF PRODUCERS",dcs:Count_Person_Producer_AmericanIndianOrAlaskaNativeAlone, +"PRODUCERS, AMERICAN INDIAN OR ALASKA NATIVE - ACRES OPERATED",dcs:Area_Farm_Producer_AmericanIndianOrAlaskaNativeAlone,dcs:Acre +"PRODUCERS, PRINCIPAL, AMERICAN INDIAN OR ALASKA NATIVE - NUMBER OF OPERATIONS",dcs:Count_Farm_PrimaryProducer_AmericanIndianOrAlaskaNativeAlone, +"PRODUCERS, PRINCIPAL, AMERICAN INDIAN OR ALASKA NATIVE - ACRES OPERATED",dcs:Area_Farm_PrimaryProducer_AmericanIndianOrAlaskaNativeAlone,dcs:Acre +"PRODUCERS, ASIAN - NUMBER OF OPERATIONS",dcs:Count_Farm_Producer_AsianAlone, +"PRODUCERS, ASIAN - NUMBER OF PRODUCERS",dcs:Count_Person_Producer_AsianAlone, +"PRODUCERS, ASIAN - ACRES OPERATED",dcs:Area_Farm_Producer_AsianAlone,dcs:Acre +"PRODUCERS, PRINCIPAL, ASIAN - NUMBER OF OPERATIONS",dcs:Count_Farm_PrimaryProducer_AsianAlone, +"PRODUCERS, PRINCIPAL, ASIAN - ACRES OPERATED",dcs:Area_Farm_PrimaryProducer_AsianAlone,dcs:Acre +"PRODUCERS, BLACK OR AFRICAN AMERICAN - NUMBER OF OPERATIONS",dcs:Count_Farm_Producer_BlackOrAfricanAmericanAlone, +"PRODUCERS, BLACK OR AFRICAN AMERICAN - NUMBER OF PRODUCERS",dcs:Count_Person_Producer_BlackOrAfricanAmericanAlone, +"PRODUCERS, BLACK OR AFRICAN AMERICAN - ACRES OPERATED",dcs:Area_Farm_Producer_BlackOrAfricanAmericanAlone,dcs:Acre +"PRODUCERS, PRINCIPAL, BLACK OR AFRICAN AMERICAN - NUMBER OF OPERATIONS",dcs:Count_Farm_PrimaryProducer_BlackOrAfricanAmericanAlone, +"PRODUCERS, PRINCIPAL, BLACK OR AFRICAN AMERICAN - ACRES OPERATED",dcs:Area_Farm_PrimaryProducer_BlackOrAfricanAmericanAlone,dcs:Acre +"PRODUCERS, NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER - NUMBER OF OPERATIONS",dcs:Count_Farm_Producer_NativeHawaiianOrOtherPacificIslanderAlone, +"PRODUCERS, NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER - NUMBER OF PRODUCERS",dcs:Count_Person_Producer_NativeHawaiianOrOtherPacificIslanderAlone, +"PRODUCERS, NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER - ACRES OPERATED",dcs:Area_Farm_Producer_NativeHawaiianOrOtherPacificIslanderAlone,dcs:Acre +"PRODUCERS, PRINCIPAL, NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER - NUMBER OF OPERATIONS",dcs:Count_Farm_PrimaryProducer_NativeHawaiianOrOtherPacificIslanderAlone, +"PRODUCERS, PRINCIPAL, NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER - ACRES OPERATED",dcs:Area_Farm_PrimaryProducer_NativeHawaiianOrOtherPacificIslanderAlone,dcs:Acre +"PRODUCERS, WHITE - NUMBER OF OPERATIONS",dcs:Count_Farm_Producer_WhiteAlone, +"PRODUCERS, WHITE - NUMBER OF PRODUCERS",dcs:Count_Person_Producer_WhiteAlone, +"PRODUCERS, WHITE - ACRES OPERATED",dcs:Area_Farm_Producer_WhiteAlone,dcs:Acre +"PRODUCERS, PRINCIPAL, WHITE - NUMBER OF OPERATIONS",dcs:Count_Farm_PrimaryProducer_WhiteAlone, +"PRODUCERS, PRINCIPAL, WHITE - ACRES OPERATED",dcs:Area_Farm_PrimaryProducer_WhiteAlone,dcs:Acre +"PRODUCERS, MULTI-RACE - NUMBER OF OPERATIONS",dcs:Count_Farm_Producer_TwoOrMoreRaces, +"PRODUCERS, MULTI-RACE - NUMBER OF PRODUCERS",dcs:Count_Person_Producer_TwoOrMoreRaces, +"PRODUCERS, MULTI-RACE - ACRES OPERATED",dcs:Area_Farm_Producer_TwoOrMoreRaces,dcs:Acre +"PRODUCERS, PRINCIPAL, MULTI-RACE - NUMBER OF OPERATIONS",dcs:Count_Farm_PrimaryProducer_TwoOrMoreRaces, +"PRODUCERS, PRINCIPAL, MULTI-RACE - ACRES OPERATED",dcs:Area_Farm_PrimaryProducer_TwoOrMoreRaces,dcs:Acre diff --git a/scripts/us_usda/quickstats/testdata/expected.csv b/scripts/us_usda/quickstats/testdata/expected.csv new file mode 100644 index 0000000000..d42999033d --- /dev/null +++ b/scripts/us_usda/quickstats/testdata/expected.csv @@ -0,0 +1,3 @@ +variableMeasured,observationDate,observationAbout,value,unit +dcs:Count_FarmInventory_BeefCows,2022,dcid:geoId/06001,11400, +dcs:Count_FarmInventory_CattleAndCalves,2022,dcid:geoId/06001,19200, diff --git a/scripts/us_usda/quickstats/testdata/response/2022/ALAMEDA.json b/scripts/us_usda/quickstats/testdata/response/2022/ALAMEDA.json new file mode 100644 index 0000000000..6c7f774588 --- /dev/null +++ b/scripts/us_usda/quickstats/testdata/response/2022/ALAMEDA.json @@ -0,0 +1,250 @@ +{ + "data": [ + { + "congr_district_code": "", + "state_fips_code": "06", + "group_desc": "LIVESTOCK", + "country_name": "UNITED STATES", + "prodn_practice_desc": "ALL PRODUCTION PRACTICES", + "unit_desc": "HEAD", + "source_desc": "SURVEY", + "reference_period_desc": "FIRST OF JAN", + "freq_desc": "POINT IN TIME", + "year": 2022, + "county_name": "ALAMEDA", + "statisticcat_desc": "INVENTORY", + "sector_desc": "ANIMALS & PRODUCTS", + "state_name": "CALIFORNIA", + "domain_desc": "TOTAL", + "Value": "11,400", + "asd_code": "40", + "state_alpha": "CA", + "class_desc": "COWS, BEEF", + "week_ending": "", + "zip_5": "", + "short_desc": "CATTLE, COWS, BEEF - INVENTORY", + "country_code": "9000", + "agg_level_desc": "COUNTY", + "domaincat_desc": "NOT SPECIFIED", + "commodity_desc": "CATTLE", + "county_code": "001", + "watershed_code": "00000000", + "begin_code": "01", + "CV (%)": "", + "load_time": "2023-05-08 15:00:00.000", + "util_practice_desc": "ALL UTILIZATION PRACTICES", + "asd_desc": "CENTRAL COAST", + "state_ansi": "06", + "watershed_desc": "", + "end_code": "01", + "county_ansi": "001", + "region_desc": "", + "location_desc": "CALIFORNIA, CENTRAL COAST, ALAMEDA" + }, + { + "reference_period_desc": "FIRST OF JAN", + "freq_desc": "POINT IN TIME", + "year": 2022, + "statisticcat_desc": "INVENTORY", + "county_name": "ALAMEDA", + "state_name": "CALIFORNIA", + "sector_desc": "ANIMALS & PRODUCTS", + "domain_desc": "TOTAL", + "Value": " (D)", + "asd_code": "40", + "state_alpha": "CA", + "class_desc": "COWS, MILK", + "week_ending": "", + "short_desc": "CATTLE, COWS, MILK - INVENTORY", + "zip_5": "", + "country_code": "9000", + "congr_district_code": "", + "state_fips_code": "06", + "group_desc": "LIVESTOCK", + "country_name": "UNITED STATES", + "prodn_practice_desc": "ALL PRODUCTION PRACTICES", + "unit_desc": "HEAD", + "source_desc": "SURVEY", + "CV (%)": "", + "load_time": "2023-05-08 15:00:00.000", + "util_practice_desc": "ALL UTILIZATION PRACTICES", + "asd_desc": "CENTRAL COAST", + "state_ansi": "06", + "watershed_desc": "", + "county_ansi": "001", + "end_code": "01", + "region_desc": "", + "location_desc": "CALIFORNIA, CENTRAL COAST, ALAMEDA", + "agg_level_desc": "COUNTY", + "domaincat_desc": "NOT SPECIFIED", + "commodity_desc": "CATTLE", + "county_code": "001", + "watershed_code": "00000000", + "begin_code": "01" + }, + { + "begin_code": "01", + "watershed_code": "00000000", + "domaincat_desc": "NOT SPECIFIED", + "commodity_desc": "CATTLE", + "county_code": "001", + "agg_level_desc": "COUNTY", + "region_desc": "", + "location_desc": "CALIFORNIA, CENTRAL COAST, ALAMEDA", + "state_ansi": "06", + "watershed_desc": "", + "end_code": "01", + "county_ansi": "001", + "util_practice_desc": "ALL UTILIZATION PRACTICES", + "asd_desc": "CENTRAL COAST", + "CV (%)": "", + "load_time": "2023-05-08 15:00:00.000", + "unit_desc": "HEAD", + "source_desc": "SURVEY", + "prodn_practice_desc": "ALL PRODUCTION PRACTICES", + "country_name": "UNITED STATES", + "congr_district_code": "", + "state_fips_code": "06", + "group_desc": "LIVESTOCK", + "week_ending": "", + "country_code": "9000", + "short_desc": "CATTLE, INCL CALVES - INVENTORY", + "zip_5": "", + "Value": "19,200", + "asd_code": "40", + "state_alpha": "CA", + "class_desc": "INCL CALVES", + "state_name": "CALIFORNIA", + "sector_desc": "ANIMALS & PRODUCTS", + "domain_desc": "TOTAL", + "reference_period_desc": "FIRST OF JAN", + "freq_desc": "POINT IN TIME", + "year": 2022, + "statisticcat_desc": "INVENTORY", + "county_name": "ALAMEDA" + }, + { + "prodn_practice_desc": "IRRIGATED", + "unit_desc": "$ / ACRE", + "source_desc": "SURVEY", + "congr_district_code": "", + "state_fips_code": "06", + "group_desc": "EXPENSES", + "country_name": "UNITED STATES", + "Value": "1,330", + "asd_code": "40", + "state_alpha": "CA", + "class_desc": "CASH, CROPLAND", + "week_ending": "", + "short_desc": "RENT, CASH, CROPLAND, IRRIGATED - EXPENSE, MEASURED IN $ / ACRE", + "country_code": "9000", + "zip_5": "", + "freq_desc": "ANNUAL", + "reference_period_desc": "YEAR", + "year": 2022, + "county_name": "ALAMEDA", + "statisticcat_desc": "EXPENSE", + "state_name": "CALIFORNIA", + "sector_desc": "ECONOMICS", + "domain_desc": "TOTAL", + "watershed_code": "00000000", + "begin_code": "00", + "agg_level_desc": "COUNTY", + "commodity_desc": "RENT", + "domaincat_desc": "NOT SPECIFIED", + "county_code": "001", + "state_ansi": "06", + "watershed_desc": "", + "end_code": "00", + "county_ansi": "001", + "location_desc": "CALIFORNIA, CENTRAL COAST, ALAMEDA", + "region_desc": "", + "CV (%)": "9.3", + "load_time": "2022-08-26 15:00:22.000", + "util_practice_desc": "ALL UTILIZATION PRACTICES", + "asd_desc": "CENTRAL COAST" + }, + { + "country_name": "UNITED STATES", + "congr_district_code": "", + "state_fips_code": "06", + "group_desc": "EXPENSES", + "unit_desc": "$ / ACRE", + "source_desc": "SURVEY", + "prodn_practice_desc": "NON-IRRIGATED", + "state_name": "CALIFORNIA", + "sector_desc": "ECONOMICS", + "domain_desc": "TOTAL", + "freq_desc": "ANNUAL", + "reference_period_desc": "YEAR", + "year": 2022, + "statisticcat_desc": "EXPENSE", + "county_name": "ALAMEDA", + "week_ending": "", + "country_code": "9000", + "zip_5": "", + "short_desc": "RENT, CASH, CROPLAND, NON-IRRIGATED - EXPENSE, MEASURED IN $ / ACRE", + "Value": "20", + "asd_code": "40", + "state_alpha": "CA", + "class_desc": "CASH, CROPLAND", + "domaincat_desc": "NOT SPECIFIED", + "commodity_desc": "RENT", + "county_code": "001", + "agg_level_desc": "COUNTY", + "begin_code": "00", + "watershed_code": "00000000", + "util_practice_desc": "ALL UTILIZATION PRACTICES", + "asd_desc": "CENTRAL COAST", + "CV (%)": "6.7", + "load_time": "2022-08-26 15:00:22.000", + "location_desc": "CALIFORNIA, CENTRAL COAST, ALAMEDA", + "region_desc": "", + "state_ansi": "06", + "watershed_desc": "", + "end_code": "00", + "county_ansi": "001" + }, + { + "region_desc": "", + "location_desc": "CALIFORNIA, CENTRAL COAST, ALAMEDA", + "county_ansi": "001", + "end_code": "00", + "state_ansi": "06", + "watershed_desc": "", + "asd_desc": "CENTRAL COAST", + "util_practice_desc": "ALL UTILIZATION PRACTICES", + "CV (%)": "6.2", + "load_time": "2022-08-26 15:00:22.000", + "begin_code": "00", + "watershed_code": "00000000", + "county_code": "001", + "domaincat_desc": "NOT SPECIFIED", + "commodity_desc": "RENT", + "agg_level_desc": "COUNTY", + "short_desc": "RENT, CASH, PASTURELAND - EXPENSE, MEASURED IN $ / ACRE", + "zip_5": "", + "country_code": "9000", + "week_ending": "", + "class_desc": "CASH, PASTURELAND", + "Value": "17", + "asd_code": "40", + "state_alpha": "CA", + "domain_desc": "TOTAL", + "sector_desc": "ECONOMICS", + "state_name": "CALIFORNIA", + "year": 2022, + "statisticcat_desc": "EXPENSE", + "county_name": "ALAMEDA", + "reference_period_desc": "YEAR", + "freq_desc": "ANNUAL", + "unit_desc": "$ / ACRE", + "source_desc": "SURVEY", + "prodn_practice_desc": "ALL PRODUCTION PRACTICES", + "country_name": "UNITED STATES", + "group_desc": "EXPENSES", + "congr_district_code": "", + "state_fips_code": "06" + } + ] +} \ No newline at end of file diff --git a/scripts/world_bank/datasets/.gitignore b/scripts/world_bank/datasets/.gitignore new file mode 100644 index 0000000000..0dcc73594d --- /dev/null +++ b/scripts/world_bank/datasets/.gitignore @@ -0,0 +1,2 @@ +output/ +input/ diff --git a/scripts/world_bank/datasets/datasets.py b/scripts/world_bank/datasets/datasets.py new file mode 100644 index 0000000000..fe9d33563d --- /dev/null +++ b/scripts/world_bank/datasets/datasets.py @@ -0,0 +1,590 @@ +# Copyright 2021 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Processes WB datasets. + +Supports the following tasks: + +============================ + +fetch_datasets: Fetches WB dataset lists and resources and writes them to 'output/wb-datasets.csv' + +Run: python3 datasets.py --mode=fetch_datasets + +============================ + +download_datasets: Downloads datasets listed in 'output/wb-datasets.csv' to the 'output/downloads' folder. + +Run: python3 datasets.py --mode=download_datasets + +============================ + +write_wb_codes: Extracts World Bank indicator codes (and related information) from files downloaded in the 'output/downloads' folder to 'output/wb-codes.csv'. + +It only operates on files that are named '*_CSV.zip'. + +Run: python3 datasets.py --mode=write_wb_codes + +============================ + +load_stat_vars: Loads stat vars from a mapping file specified via the `stat_vars_file` flag. + +Use this for debugging to ensure that the mappings load correctly and fix any errors logged by this operation. + +Run: python3 datasets.py --mode=load_stat_vars --stat_vars_file=/path/to/sv_mappings.csv + +See `sample-svs.csv` for a sample mappings file. + +============================ + +write_observations: Extracts observations from files downloaded in the 'output/downloads' folder and saves them to CSVs in the 'output/observations' folder. + +The stat vars file to be used for mappings should be specified using the `stat_vars_file' flag. + +It only operates on files that are named '*_CSV.zip'. + +Run: python3 datasets.py --mode=write_observations --stat_vars_file=/path/to/sv_mappings.csv +""" + +import requests +from absl import app +from absl import logging +import os +import json +import multiprocessing +import csv +import re +import urllib3 +from urllib3.util.ssl_ import create_urllib3_context +from absl import flags +import zipfile +import codecs +from itertools import repeat +from datetime import datetime + +FLAGS = flags.FLAGS + + +class Mode: + FETCH_DATASETS = 'fetch_datasets' + DOWNLOAD_DATASETS = 'download_datasets' + WRITE_WB_CODES = 'write_wb_codes' + LOAD_STAT_VARS = 'load_stat_vars' + WRITE_OBSERVATIONS = 'write_observations' + + +flags.DEFINE_string( + 'mode', Mode.WRITE_OBSERVATIONS, + f"Specify one of the following modes: {Mode.FETCH_DATASETS}, {Mode.DOWNLOAD_DATASETS}, {Mode.WRITE_WB_CODES}, {Mode.LOAD_STAT_VARS}, {Mode.WRITE_OBSERVATIONS}" +) + +flags.DEFINE_string('stat_vars_file', 'statvars.csv', + 'Path to CSV file with Stat Var mappings.') + +ctx = create_urllib3_context() +ctx.load_default_certs() +ctx.options |= 0x4 # ssl.OP_LEGACY_SERVER_CONNECT + +DATASET_LIST_URL = 'https://datacatalogapi.worldbank.org/ddhxext/DatasetList' +DATASET_VIEW_URL = 'https://datacatalogapi.worldbank.org/ddhxext/DatasetView' + +OUTPUT_DIR = 'output' +RESPONSE_DIR = f"{OUTPUT_DIR}/response" +DATASET_LISTS_RESPONSE_DIR = f"{RESPONSE_DIR}/lists" +DATASET_VIEWS_RESPONSE_DIR = f"{RESPONSE_DIR}/views" +DATASETS_CSV_FILE_PATH = f"{OUTPUT_DIR}/wb-datasets.csv" +DOWNLOADS_DIR = f"{OUTPUT_DIR}/downloads" +OBSERVATIONS_DIR = f"{OUTPUT_DIR}/observations" + +os.makedirs(DATASET_LISTS_RESPONSE_DIR, exist_ok=True) +os.makedirs(DATASET_VIEWS_RESPONSE_DIR, exist_ok=True) +os.makedirs(DOWNLOADS_DIR, exist_ok=True) +os.makedirs(OBSERVATIONS_DIR, exist_ok=True) + +POOL_SIZE = max(2, multiprocessing.cpu_count() - 1) + +DOWNLOADABLE_RESOURCE_TYPES = set(["Download", "Dataset"]) + +DATASET_NAME_COLUMN_NAME = "Dataset Name" +DATASET_RESOURCE_NAME_COLUMN_NAME = "Resource Name" +DATASET_VIEW_FILE_COLUMN_NAME = "Dataset View File" +DATASET_FORMAT_COLUMN_NAME = "Format" +DATASET_SIZE_COLUMN_NAME = "Size" +DATASET_DOWNLOAD_URL_COLUMN_NAME = "Download URL" + +DATASETS_CSV_COLUMNS = [ + DATASET_NAME_COLUMN_NAME, DATASET_RESOURCE_NAME_COLUMN_NAME, + DATASET_VIEW_FILE_COLUMN_NAME, DATASET_FORMAT_COLUMN_NAME, + DATASET_SIZE_COLUMN_NAME, DATASET_DOWNLOAD_URL_COLUMN_NAME +] + + +def download_datasets(): + '''Downloads dataset files. This is a very expensive operation so run it with care. It assumes that the datasets CSV is already available.''' + + with open(DATASETS_CSV_FILE_PATH, 'r') as f: + csv_rows = list(csv.DictReader(f)) + download_urls = [] + for csv_row in csv_rows: + download_url = csv_row.get(DATASET_DOWNLOAD_URL_COLUMN_NAME) + if download_url: + download_urls.append(download_url) + + with multiprocessing.Pool(POOL_SIZE) as pool: + pool.starmap(download, zip(download_urls)) + + logging.info('# files downloaded: %s', len(download_urls)) + + +def download(url): + file_name = re.sub(r'[^a-zA-Z0-9\.\-_/]', '', url.split('/')[-1]) + file_path = f"{DOWNLOADS_DIR}/{file_name}" + if os.path.exists(file_path): + logging.info('Already downloaded %s to file %s', url, file_path) + return + + logging.info('Downloading %s to file %s', url, file_path) + try: + # response = requests.get(url) + # Using urllib3 for downloading content to avoid SSL issue. + # See: https://github.com/urllib3/urllib3/issues/2653#issuecomment-1165418616 + with urllib3.PoolManager(ssl_context=ctx) as http: + response = http.request("GET", url) + with open(file_path, 'wb') as f: + f.write(response.data) + except Exception as e: + logging.error("Error downloading %s", url, exc_info=e) + + +def fetch_and_write_datasets_csv(): + fetch_dataset_lists() + fetch_dataset_views() + write_datasets_csv() + + +def write_datasets_csv(): + csv_rows = get_datasets_csv_rows() + with open(DATASETS_CSV_FILE_PATH, 'w', newline='') as out: + csv_writer = csv.DictWriter(out, + fieldnames=DATASETS_CSV_COLUMNS, + lineterminator='\n') + csv_writer.writeheader() + csv_writer.writerows(csv_rows) + + +def get_datasets_csv_rows(): + # Assumes all dataset view responses have been saved to disk + view_files = os.listdir(DATASET_VIEWS_RESPONSE_DIR) + csv_rows = [] + for view_file in view_files: + json = load_json_file(f"{DATASET_VIEWS_RESPONSE_DIR}/{view_file}") + dataset_name = json.get('name') + for resource in json.get('Resources', []): + resource_type = resource.get('resource_type', '') + + if resource_type in DOWNLOADABLE_RESOURCE_TYPES: + csv_row = to_dataset_csv_row(resource, dataset_name, view_file) + if csv_row: + csv_rows.append(csv_row) + + logging.info('# downloadable datasets: %s', len(csv_rows)) + return csv_rows + + +DATASET_URL_FIELDS = ['harvet_source', 'url', 'website_url'] + +# URLs with this pattern are downloadable only if the URL is trunctated until it. Probably a bug in WB APIs. +VERSION_ID_PATTERN = '?versionId=' + + +def to_dataset_csv_row(resource, dataset_name, view_file): + format = resource.get('format') + if format is None: + return None + + url = None + for field in DATASET_URL_FIELDS: + url = resource.get(field) + if url is not None: + url = url.split(VERSION_ID_PATTERN)[0] + break + + if url is None: + return None + + return { + DATASET_NAME_COLUMN_NAME: dataset_name, + DATASET_RESOURCE_NAME_COLUMN_NAME: resource.get('name'), + DATASET_VIEW_FILE_COLUMN_NAME: view_file, + DATASET_FORMAT_COLUMN_NAME: format, + DATASET_SIZE_COLUMN_NAME: resource.get('distribution_size'), + DATASET_DOWNLOAD_URL_COLUMN_NAME: url + } + + +def fetch_dataset_view(dataset_unique_id): + params = f"dataset_unique_id={dataset_unique_id}" + response_file = f"{DATASET_VIEWS_RESPONSE_DIR}/view-{dataset_unique_id}.json" + return load_json(url=DATASET_VIEW_URL, + params=params, + response_file=response_file) + + +def fetch_dataset_views(): + # Assumes all dataset list responses have been saved to disk + list_files = os.listdir(DATASET_LISTS_RESPONSE_DIR) + dataset_unique_ids = [] + for list_file in list_files: + json = load_json_file(f"{DATASET_LISTS_RESPONSE_DIR}/{list_file}") + for dataset in json.get('data', []): + dataset_unique_id = dataset.get('dataset_unique_id') + if dataset_unique_id: + dataset_unique_ids.append(dataset_unique_id) + + with multiprocessing.Pool(POOL_SIZE) as pool: + pool.starmap(fetch_dataset_view, zip(dataset_unique_ids)) + + +def fetch_dataset_list(skip): + params = f"$skip={skip}&$top=1000" + response_file = f"{DATASET_LISTS_RESPONSE_DIR}/list-{skip}.json" + return load_json(url=DATASET_LIST_URL, + params=params, + response_file=response_file) + + +def fetch_dataset_lists(): + # 6000+ datasets, fetching 1000 at a time + skips = range(0, 7000, 1000) + with multiprocessing.Pool(POOL_SIZE) as pool: + pool.starmap(fetch_dataset_list, zip(skips)) + + +def load_json(url, params, response_file): + if os.path.exists(response_file): + logging.info('Reading response from file %s', response_file) + with open(response_file, 'r') as f: + return json.load(f) + + logging.info("Fetching url %s, params %s", url, params) + response = requests.get(url, params=params).json() + with open(response_file, 'w') as f: + logging.info('Writing response to file %s', response_file) + json.dump(response, f, indent=2) + return response + + +def load_json_file(json_file): + with open(json_file, 'r') as f: + return json.load(f) + + +DATA_FILE_SUFFIX = 'Data.csv' +SERIES_FILE_SUFFIX = 'Series.csv' +CSV_ZIP_FILE_SUFFIX = '_CSV.zip' +SERIES_CODE_KEY = 'seriescode' +NUM_DATASETS_KEY = 'numdatasets' +INDICATOR_NAME_KEY = 'indicatorname' +TOPIC_KEY = 'topic' +UNIT_OF_MEASURE_KEY = 'unitofmeasure' +UNIT_KEY = 'unit' +SHORT_DEFINITION_KEY = 'shortdefinition' +LONG_DEFINITION_KEY = 'longdefinition' +LICENSE_TYPE_KEY = 'licensetype' +STAT_VAR_KEY = 'statvar' +COUNTRY_CODE_KEY = 'countrycode' +INDICATOR_CODE_KEY = 'indicatorcode' +OBSERVATION_DATE_KEY = 'observationdate' +OBSERVATION_ABOUT_KEY = 'observationabout' +OBSERVATION_VALUE_KEY = 'observationvalue' +MEASUREMENT_METHOD_KEY = 'measurementmethod' +CODES_FILE_PATH = os.path.join(OUTPUT_DIR, 'wb-codes.csv') +CODES_CSV_COLUMNS = [ + SERIES_CODE_KEY, INDICATOR_NAME_KEY, NUM_DATASETS_KEY, TOPIC_KEY, + UNIT_OF_MEASURE_KEY, SHORT_DEFINITION_KEY, LONG_DEFINITION_KEY, + LICENSE_TYPE_KEY +] +OBS_CSV_COLUMNS = [ + INDICATOR_CODE_KEY, STAT_VAR_KEY, MEASUREMENT_METHOD_KEY, + OBSERVATION_ABOUT_KEY, OBSERVATION_DATE_KEY, OBSERVATION_VALUE_KEY, UNIT_KEY +] +EARTH_DCID = 'dcid:Earth' +COUNTRY_DCID_PREFIX = 'dcid:country' +WORLD_BANK_STAT_VAR_PREFIX = 'worldBank' +WORLD_BANK_MEASUREMENT_METHOD_PREFIX = 'WorldBank' + + +def load_stat_vars(stat_var_file): + with open(stat_var_file, 'r') as f: + csv_rows = sanitize_csv_rows(list(csv.DictReader(f))) + svs = {} + for csv_row in csv_rows: + if csv_row.get(SERIES_CODE_KEY) and csv_row.get(STAT_VAR_KEY): + svs[csv_row[SERIES_CODE_KEY]] = csv_row + else: + logging.error('SKIPPED stat var row: %s', csv_row) + + logging.info(svs) + return svs + + +def write_wb_codes(): + csv_rows = get_all_codes().values() + with open(CODES_FILE_PATH, 'w', newline='') as out: + csv_writer = csv.DictWriter(out, + fieldnames=CODES_CSV_COLUMNS, + lineterminator='\n') + csv_writer.writeheader() + csv_writer.writerows(csv_rows) + + +def get_all_codes(): + all_codes = {} + for file_name in os.listdir(DOWNLOADS_DIR): + if file_name.endswith(CSV_ZIP_FILE_SUFFIX): + zip_file = f"{DOWNLOADS_DIR}/{file_name}" + codes = get_codes_from_zip(zip_file) + if codes: + for key, value in codes.items(): + if key in all_codes: + all_codes[key][NUM_DATASETS_KEY] = all_codes[key][ + NUM_DATASETS_KEY] + 1 + else: + all_codes[key] = value + logging.info('# total codes: %s', len(all_codes)) + return all_codes + + +def get_codes_from_zip(zip_file): + with zipfile.ZipFile(zip_file, 'r') as zip: + (_, series_file) = get_data_and_series_file_names(zip) + if series_file is None: + logging.warning('No series file found in ZIP file: %s', zip_file) + else: + with zip.open(series_file, 'r') as csv_file: + series_rows = sanitize_csv_rows( + list(csv.DictReader(codecs.iterdecode(csv_file, 'utf-8')))) + num_codes = len(series_rows) + logging.info('# code(s) in %s: %s', zip_file, num_codes) + if num_codes == 0: + return {} + + if series_rows[0].get(SERIES_CODE_KEY) is None: + logging.error('No series code found in %s, sample row: %s', + zip_file, series_rows[0]) + return {} + + codes = {} + for series_row in series_rows: + code = series_row.get(SERIES_CODE_KEY) + codes[code] = { + SERIES_CODE_KEY: + code, + INDICATOR_NAME_KEY: + series_row.get(INDICATOR_NAME_KEY), + NUM_DATASETS_KEY: + 1, + TOPIC_KEY: + series_row.get(TOPIC_KEY), + UNIT_OF_MEASURE_KEY: + series_row.get(UNIT_OF_MEASURE_KEY), + SHORT_DEFINITION_KEY: + series_row.get(SHORT_DEFINITION_KEY), + LONG_DEFINITION_KEY: + series_row.get(LONG_DEFINITION_KEY), + LICENSE_TYPE_KEY: + series_row.get(LICENSE_TYPE_KEY), + } + return codes + return {} + + +def write_csv(csv_file_path, csv_columns, csv_rows): + with open(csv_file_path, 'w', newline='') as out: + csv_writer = csv.DictWriter(out, + fieldnames=csv_columns, + lineterminator='\n') + csv_writer.writeheader() + csv_writer.writerows(csv_rows) + + +def write_all_observations(stat_vars_file): + start = datetime.now() + logging.info('Start: %s', start) + + svs = load_stat_vars(stat_vars_file) + + zip_files = [] + for file_name in os.listdir(DOWNLOADS_DIR): + if file_name.endswith(CSV_ZIP_FILE_SUFFIX): + zip_files.append(f"{DOWNLOADS_DIR}/{file_name}") + + with multiprocessing.Pool(POOL_SIZE) as pool: + pool.starmap(write_observations_from_zip, zip(zip_files, repeat(svs))) + + end = datetime.now() + logging.info('End: %s', end) + logging.info('Duration: %s', str(end - start)) + + +def write_observations_from_zip(zip_file, svs): + csv_rows = get_observations_from_zip(zip_file, svs) + if len(csv_rows) == 0: + logging.info( + 'SKIPPED writing obs file, no observations extracted from %s', + zip_file) + return + + obs_file_name = f"{zip_file.split('/')[-1].split('.')[0]}_obs.csv" + obs_file_path = os.path.join(OBSERVATIONS_DIR, obs_file_name) + logging.info('Writing %s observations from %s to %s', len(csv_rows), + zip_file, obs_file_path) + write_csv(obs_file_path, OBS_CSV_COLUMNS, csv_rows) + + +def get_observations_from_zip(zip_file, svs): + with zipfile.ZipFile(zip_file, 'r') as zip: + (data_file, _) = get_data_and_series_file_names(zip) + if data_file is None: + logging.warning('No data file found in ZIP file: %s', zip_file) + return [] + else: + # Use name of file (excluding the extension) as the measurement method + measurement_method = f"{WORLD_BANK_MEASUREMENT_METHOD_PREFIX}_{zip_file.split('/')[-1].split('.')[0]}" + with zip.open(data_file, 'r') as csv_file: + data_rows = sanitize_csv_rows( + list(csv.DictReader(codecs.iterdecode(csv_file, 'utf-8')))) + num_rows = len(data_rows) + logging.info('# data rows in %s: %s', zip_file, num_rows) + + obs_csv_rows = [] + for data_row in data_rows: + obs_csv_rows.extend( + get_observations_from_data_row(data_row, svs, + measurement_method)) + + return obs_csv_rows + + +def get_observations_from_data_row(data_row, svs, measurement_method): + code = data_row.get(INDICATOR_CODE_KEY) + if code is None: + logging.error('SKIPPED data row, no indicator code: %s', data_row) + return [] + + sv = get_stat_var_from_code(code, svs) + if sv is None: + return [] + + place_dcid = data_row.get(COUNTRY_CODE_KEY) + if place_dcid: + if len(place_dcid) != 3: + logging.error('SKIPPED data row, not a country code: %s', + place_dcid) + return [] + else: + place_dcid = f"{COUNTRY_DCID_PREFIX}/{place_dcid}" + else: + place_dcid = EARTH_DCID + + obs_csv_rows = [] + for key in data_row.keys(): + # Flatten year columns with values into rows. + # Each year is a column and columns are integers. + # So we ignore those that are not. + if not key.isdecimal(): + continue + + year = key + + # We are only interested in numeric values. + value = data_row[year] + if not is_numeric(value): + continue + + obs_csv_rows.append({ + INDICATOR_CODE_KEY: code, + STAT_VAR_KEY: sv[STAT_VAR_KEY], + MEASUREMENT_METHOD_KEY: measurement_method, + OBSERVATION_ABOUT_KEY: place_dcid, + OBSERVATION_DATE_KEY: year, + OBSERVATION_VALUE_KEY: value, + UNIT_KEY: sv.get(UNIT_KEY) + }) + + return obs_csv_rows + + +def get_stat_var_from_code(code, svs): + sv_mapping = svs.get(code) + if sv_mapping is None or sv_mapping.get(STAT_VAR_KEY) is None: + logging.warning('SKIPPED, WB code not mapped: %s', code) + return None + return sv_mapping + + +def is_numeric(value): + if value is None: + return False + + if value.isdecimal(): + return True + + try: + float(value) + return True + except: + return False + + +def sanitize_csv_rows(csv_rows): + sanitized_rows = [] + for csv_row in csv_rows: + sanitized_rows.append( + dict((sanitize_csv_key(key), value) + for (key, value) in csv_row.items())) + return sanitized_rows + + +def sanitize_csv_key(key): + return re.sub(r'[^a-zA-Z0-9]', '', key).lower() + + +def get_data_and_series_file_names(zip): + for file_name in zip.namelist(): + if file_name.endswith(DATA_FILE_SUFFIX): + series_file_name = file_name.replace(DATA_FILE_SUFFIX, + SERIES_FILE_SUFFIX) + if series_file_name in zip.namelist(): + return (file_name, series_file_name) + return (None, None) + + +def main(_): + match FLAGS.mode: + case Mode.FETCH_DATASETS: + download_datasets() + case Mode.DOWNLOAD_DATASETS: + fetch_and_write_datasets_csv() + case Mode.WRITE_WB_CODES: + write_wb_codes() + case Mode.LOAD_STAT_VARS: + load_stat_vars(FLAGS.stat_vars_file) + case Mode.WRITE_OBSERVATIONS: + write_all_observations(FLAGS.stat_vars_file) + case _: + logging.error('No mode specified.') + + +if __name__ == '__main__': + app.run(main) diff --git a/scripts/world_bank/datasets/sample-statvars.csv b/scripts/world_bank/datasets/sample-statvars.csv new file mode 100644 index 0000000000..30dd91694b --- /dev/null +++ b/scripts/world_bank/datasets/sample-statvars.csv @@ -0,0 +1,4 @@ +seriescode,statvar,unit +IC.CNST.PRMT.DFRN.DB0615,worldBank/IC_CNST_PRMT_DFRN_DB0615,dcs:SomeUnit +CODE.WITH.NO.UNIT,worldBank/CODE_WITH_NO_UNIT, +CODE.WITHOUT.STATVAR.WILL.BE.SKIPPED,, diff --git a/scripts/world_bank/datasets/statvars.csv b/scripts/world_bank/datasets/statvars.csv new file mode 100644 index 0000000000..4ce1f4d22a --- /dev/null +++ b/scripts/world_bank/datasets/statvars.csv @@ -0,0 +1,2868 @@ +seriescode,unit,StatVar +1.1_ACCESS.ELECTRICITY.TOT,,worldBank/1_1_ACCESS_ELECTRICITY_TOT +1.1_TOTAL.FINAL.ENERGY.CONSUM,dcs:Terajoule,worldBank/1_1_TOTAL_FINAL_ENERGY_CONSUM +1.2_ACCESS.ELECTRICITY.RURAL,,worldBank/1_2_ACCESS_ELECTRICITY_RURAL +1.3_ACCESS.ELECTRICITY.URBAN,,worldBank/1_3_ACCESS_ELECTRICITY_URBAN +2.01.01.02.nabase,,worldBank/2_01_01_02_nabase +2.01.03.01.prcpbase,,worldBank/2_01_03_01_prcpbase +2.04.01.01.excncpt,,worldBank/2_04_01_01_excncpt +2.1_SHARE.TOTAL.RE.IN.TFEC,dcs:Percent,worldBank/2_1_SHARE_TOTAL_RE_IN_TFEC +3.01.04.01.agcen,,worldBank/3_01_04_01_agcen +3.02.01.02.fscov,,worldBank/3_02_01_02_fscov +3.1_RE.CONSUMPTION,dcs:Terajoule,worldBank/3_1_RE_CONSUMPTION +3.11.01.01.popcen,,worldBank/3_11_01_01_popcen +3.11.01.03.popreg,,worldBank/3_11_01_03_popreg +4.1_SHARE.RE.IN.ELECTRICITY,dcs:Percent,worldBank/4_1_SHARE_RE_IN_ELECTRICITY +4.1.1_TOTAL.ELECTRICITY.OUTPUT,dcs:GigawattHour,worldBank/4_1_1_TOTAL_ELECTRICITY_OUTPUT +4.1.2_REN.ELECTRICITY.OUTPUT,dcs:GigawattHour,worldBank/4_1_2_REN_ELECTRICITY_OUTPUT +5.01.01.01.indust,,worldBank/5_01_01_01_indust +5.04.01.01.exdebt,,worldBank/5_04_01_01_exdebt +5.04.01.02.impexp,,worldBank/5_04_01_02_impexp +5.12.01.01.unesco,,worldBank/5_12_01_01_unesco +5.13.01.01.hlthsurv,,worldBank/5_13_01_01_hlthsurv +5.13.01.01.who,,worldBank/5_13_01_01_who +5.14.01.01.povsurv,,worldBank/5_14_01_01_povsurv +5.21.01.01.sdds,,worldBank/5_21_01_01_sdds +5.51.01.01.poverty,,worldBank/5_51_01_01_poverty +5.51.01.02.malnut,,worldBank/5_51_01_02_malnut +5.51.01.03.mortal,,worldBank/5_51_01_03_mortal +5.51.01.04.immun,,worldBank/5_51_01_04_immun +5.51.01.05.hiv,,worldBank/5_51_01_05_hiv +5.51.01.06.matern,,worldBank/5_51_01_06_matern +5.51.01.07.gender,,worldBank/5_51_01_07_gender +5.51.01.08.primcomp,,worldBank/5_51_01_08_primcomp +5.51.01.09.water,,worldBank/5_51_01_09_water +5.51.01.10.gdp,,worldBank/5_51_01_10_gdp +6.1_PRIMARY.ENERGY.INTENSITY,,worldBank/6_1_PRIMARY_ENERGY_INTENSITY +account.t.d,,worldBank/account_t_d +account.t.d.1,,worldBank/account_t_d_1 +account.t.d.11,,worldBank/account_t_d_11 +account.t.d.12,,worldBank/account_t_d_12 +account.t.d.2,,worldBank/account_t_d_2 +account.t.d.3,,worldBank/account_t_d_3 +account.t.d.4,,worldBank/account_t_d_4 +account.t.d.5,,worldBank/account_t_d_5 +account.t.d.6,,worldBank/account_t_d_6 +account.t.d.7,,worldBank/account_t_d_7 +account.t.d.8,,worldBank/account_t_d_8 +AG.AGR.TRAC.NO,,worldBank/AG_AGR_TRAC_NO +AG.CON.FERT.PT.ZS,dcs:Percent,worldBank/AG_CON_FERT_PT_ZS +AG.CON.FERT.ZS,dcs:Percent,worldBank/AG_CON_FERT_ZS +AG.LND.AGRI.K2,,worldBank/AG_LND_AGRI_K2 +AG.LND.AGRI.ZS,dcs:Percent,worldBank/AG_LND_AGRI_ZS +AG.LND.ARBL.HA,,worldBank/AG_LND_ARBL_HA +AG.LND.ARBL.HA.PC,,worldBank/AG_LND_ARBL_HA_PC +AG.LND.ARBL.ZS,dcs:Percent,worldBank/AG_LND_ARBL_ZS +AG.LND.CREL.HA,dcs:Hectare,worldBank/AG_LND_CREL_HA +AG.LND.CROP.ZS,dcs:Percent,worldBank/AG_LND_CROP_ZS +AG.LND.EL5M.RU.K2,,worldBank/AG_LND_EL5M_RU_K2 +AG.LND.EL5M.RU.ZS,dcs:Percent,worldBank/AG_LND_EL5M_RU_ZS +AG.LND.EL5M.UR.K2,,worldBank/AG_LND_EL5M_UR_K2 +AG.LND.EL5M.UR.ZS,dcs:Percent,worldBank/AG_LND_EL5M_UR_ZS +AG.LND.EL5M.ZS,dcs:Percent,worldBank/AG_LND_EL5M_ZS +AG.LND.FRLS.HA,dcs:Hectare,worldBank/AG_LND_FRLS_HA +AG.LND.FRST.K2,,worldBank/AG_LND_FRST_K2 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+EN.ATM.PM25.MC.T3.ZS,dcs:Percent,worldBank/EN_ATM_PM25_MC_T3_ZS +EN.ATM.PM25.MC.ZS,dcs:Percent,worldBank/EN_ATM_PM25_MC_ZS +EN.ATM.SF6G.KT.CE,,worldBank/EN_ATM_SF6G_KT_CE +EN.BIR.THRD.NO,,worldBank/EN_BIR_THRD_NO +EN.CLC.CDDY.XD,dcs:Celsius,worldBank/EN_CLC_CDDY_XD +EN.CLC.CSTP.ZS,,worldBank/EN_CLC_CSTP_ZS +EN.CLC.GHGR.MT.CE,,worldBank/EN_CLC_GHGR_MT_CE +EN.CLC.HDDY.XD,dcs:Celsius,worldBank/EN_CLC_HDDY_XD +EN.CLC.HEAT.XD,,worldBank/EN_CLC_HEAT_XD +EN.CLC.SPEI.XD,,worldBank/EN_CLC_SPEI_XD +EN.FSH.THRD.NO,,worldBank/EN_FSH_THRD_NO +EN.HPT.THRD.NO,,worldBank/EN_HPT_THRD_NO +EN.LND.LTMP.DC,dcs:Celsius,worldBank/EN_LND_LTMP_DC +EN.MAM.THRD.NO,,worldBank/EN_MAM_THRD_NO +EN.POP.DNST,,worldBank/EN_POP_DNST +EN.POP.EL5M.RU.ZS,dcs:Percent,worldBank/EN_POP_EL5M_RU_ZS +EN.POP.EL5M.UR.ZS,dcs:Percent,worldBank/EN_POP_EL5M_UR_ZS +EN.POP.EL5M.ZS,dcs:Percent,worldBank/EN_POP_EL5M_ZS +EN.POP.SLUM.UR.ZS,dcs:Percent,worldBank/EN_POP_SLUM_UR_ZS +EN.URB.LCTY,,worldBank/EN_URB_LCTY +EN.URB.LCTY.UR.ZS,dcs:Percent,worldBank/EN_URB_LCTY_UR_ZS +EN.URB.MCTY,,worldBank/EN_URB_MCTY +EN.URB.MCTY.TL.ZS,dcs:Percent,worldBank/EN_URB_MCTY_TL_ZS +ENF.CONT.COEN.ATFE.PR,,worldBank/ENF_CONT_COEN_ATFE_PR +ENF.CONT.COEN.COST.ZS,dcs:Percent,worldBank/ENF_CONT_COEN_COST_ZS +ENF.CONT.COEN.COST.ZS.DFRN,dcs:Percent,worldBank/ENF_CONT_COEN_COST_ZS_DFRN +ENF.CONT.COEN.CSMG,,worldBank/ENF_CONT_COEN_CSMG +ENF.CONT.COEN.CTAU,,worldBank/ENF_CONT_COEN_CTAU +ENF.CONT.COEN.CTFE.PR,,worldBank/ENF_CONT_COEN_CTFE_PR +ENF.CONT.COEN.CTSP.DB1719,,worldBank/ENF_CONT_COEN_CTSP_DB1719 +ENF.CONT.COEN.DB0415.DFRN,,worldBank/ENF_CONT_COEN_DB0415_DFRN +ENF.CONT.COEN.DB1719.DFRN,,worldBank/ENF_CONT_COEN_DB1719_DFRN +ENF.CONT.COEN.ENFE.PR,,worldBank/ENF_CONT_COEN_ENFE_PR +EP.PMP.DESL.CD,dcs:USDollar,worldBank/EP_PMP_DESL_CD +EP.PMP.SGAS.CD,dcs:USDollar,worldBank/EP_PMP_SGAS_CD +ER.FSH.AQUA.MT,,worldBank/ER_FSH_AQUA_MT +ER.FSH.CAPT.MT,,worldBank/ER_FSH_CAPT_MT +ER.FSH.PROD.MT,,worldBank/ER_FSH_PROD_MT +ER.FST.DFST.ZG,,worldBank/ER_FST_DFST_ZG +ER.GDP.FWTL.M3.KD,,worldBank/ER_GDP_FWTL_M3_KD +ER.H2O.FWAG.ZS,dcs:Percent,worldBank/ER_H2O_FWAG_ZS +ER.H2O.FWDM.ZS,dcs:Percent,worldBank/ER_H2O_FWDM_ZS +ER.H2O.FWIN.ZS,dcs:Percent,worldBank/ER_H2O_FWIN_ZS +ER.H2O.FWST.ZS,dcs:Percent,worldBank/ER_H2O_FWST_ZS +ER.H2O.FWTL.K3,,worldBank/ER_H2O_FWTL_K3 +ER.H2O.FWTL.ZS,dcs:Percent,worldBank/ER_H2O_FWTL_ZS +ER.H2O.INTR.K3,,worldBank/ER_H2O_INTR_K3 +ER.H2O.INTR.PC,,worldBank/ER_H2O_INTR_PC +FB.AST.NPER.ZS,dcs:Percent,worldBank/FB_AST_NPER_ZS +FB.ATM.TOTL.P5,,worldBank/FB_ATM_TOTL_P5 +FB.BNK.CAPA.ZS,dcs:Percent,worldBank/FB_BNK_CAPA_ZS +FB.CBK.BRCH.P5,,worldBank/FB_CBK_BRCH_P5 +FB.CBK.BRWR.P3,,worldBank/FB_CBK_BRWR_P3 +FB.CBK.DPTR.P3,,worldBank/FB_CBK_DPTR_P3 +FD.AST.PRVT.GD.ZS,dcs:Percent,worldBank/FD_AST_PRVT_GD_ZS +FD.RES.LIQU.AS.ZS,dcs:Percent,worldBank/FD_RES_LIQU_AS_ZS +FI.RES.TOTL.CD,dcs:USDollar,worldBank/FI_RES_TOTL_CD +FI.RES.TOTL.DT.ZS,dcs:Percent,worldBank/FI_RES_TOTL_DT_ZS +FI.RES.TOTL.MO,,worldBank/FI_RES_TOTL_MO +FI.RES.XGLD.CD,dcs:USDollar,worldBank/FI_RES_XGLD_CD +fin1.t.d,,worldBank/fin1_t_d +fin1.t.d.1,,worldBank/fin1_t_d_1 +fin1.t.d.11,,worldBank/fin1_t_d_11 +fin1.t.d.12,,worldBank/fin1_t_d_12 +fin1.t.d.2,,worldBank/fin1_t_d_2 +fin1.t.d.3,,worldBank/fin1_t_d_3 +fin1.t.d.4,,worldBank/fin1_t_d_4 +fin1.t.d.5,,worldBank/fin1_t_d_5 +fin1.t.d.6,,worldBank/fin1_t_d_6 +fin1.t.d.7,,worldBank/fin1_t_d_7 +fin1.t.d.8,,worldBank/fin1_t_d_8 +fin14a.t.d,,worldBank/fin14a_t_d +fin14a.t.d.1,,worldBank/fin14a_t_d_1 +fin14a.t.d.2,,worldBank/fin14a_t_d_2 +fin14b.t.d,,worldBank/fin14b_t_d +fin14b.t.d.1,,worldBank/fin14b_t_d_1 +fin14b.t.d.2,,worldBank/fin14b_t_d_2 +fin15.t.d.2017,,worldBank/fin15_t_d_2017 +fin15.t.d.2017.1,,worldBank/fin15_t_d_2017_1 +fin15.t.d.2017.2,,worldBank/fin15_t_d_2017_2 +fin16.t.d,,worldBank/fin16_t_d +fin16.t.d.1,,worldBank/fin16_t_d_1 +fin16.t.d.2,,worldBank/fin16_t_d_2 +fin17a.t.d,,worldBank/fin17a_t_d +fin17a.t.d.1,,worldBank/fin17a_t_d_1 +fin17a.t.d.11,,worldBank/fin17a_t_d_11 +fin17a.t.d.12,,worldBank/fin17a_t_d_12 +fin17a.t.d.2,,worldBank/fin17a_t_d_2 +fin17a.t.d.3,,worldBank/fin17a_t_d_3 +fin17a.t.d.4,,worldBank/fin17a_t_d_4 +fin17a.t.d.5,,worldBank/fin17a_t_d_5 +fin17a.t.d.6,,worldBank/fin17a_t_d_6 +fin17a.t.d.7,,worldBank/fin17a_t_d_7 +fin17a.t.d.8,,worldBank/fin17a_t_d_8 +fin17b.t.d,,worldBank/fin17b_t_d +fin17b.t.d.1,,worldBank/fin17b_t_d_1 +fin17b.t.d.2,,worldBank/fin17b_t_d_2 +fin2.7.t.d,,worldBank/fin2_7_t_d +fin2.7.t.d.1,,worldBank/fin2_7_t_d_1 +fin2.7.t.d.11,,worldBank/fin2_7_t_d_11 +fin2.7.t.d.12,,worldBank/fin2_7_t_d_12 +fin2.7.t.d.2,,worldBank/fin2_7_t_d_2 +fin2.7.t.d.3,,worldBank/fin2_7_t_d_3 +fin2.7.t.d.4,,worldBank/fin2_7_t_d_4 +fin2.7.t.d.5,,worldBank/fin2_7_t_d_5 +fin2.7.t.d.6,,worldBank/fin2_7_t_d_6 +fin2.7.t.d.7,,worldBank/fin2_7_t_d_7 +fin2.7.t.d.8,,worldBank/fin2_7_t_d_8 +fin2.t.d,,worldBank/fin2_t_d +fin2.t.d.1,,worldBank/fin2_t_d_1 +fin2.t.d.11,,worldBank/fin2_t_d_11 +fin2.t.d.12,,worldBank/fin2_t_d_12 +fin2.t.d.2,,worldBank/fin2_t_d_2 +fin2.t.d.3,,worldBank/fin2_t_d_3 +fin2.t.d.4,,worldBank/fin2_t_d_4 +fin2.t.d.5,,worldBank/fin2_t_d_5 +fin2.t.d.6,,worldBank/fin2_t_d_6 +fin2.t.d.7,,worldBank/fin2_t_d_7 +fin2.t.d.8,,worldBank/fin2_t_d_8 +fin20.t.d,,worldBank/fin20_t_d +fin20.t.d.1,,worldBank/fin20_t_d_1 +fin20.t.d.2,,worldBank/fin20_t_d_2 +fin21.t.d.2017,,worldBank/fin21_t_d_2017 +fin21.t.d.2017.1,,worldBank/fin21_t_d_2017_1 +fin21.t.d.2017.2,,worldBank/fin21_t_d_2017_2 +fin21b.2014,,worldBank/fin21b_2014 +fin21b.2014.1,,worldBank/fin21b_2014_1 +fin21b.2014.2,,worldBank/fin21b_2014_2 +fin22a.c.t.d,,worldBank/fin22a_c_t_d +fin22a.c.t.d.1,,worldBank/fin22a_c_t_d_1 +fin22a.c.t.d.11,,worldBank/fin22a_c_t_d_11 +fin22a.c.t.d.12,,worldBank/fin22a_c_t_d_12 +fin22a.c.t.d.2,,worldBank/fin22a_c_t_d_2 +fin22a.c.t.d.3,,worldBank/fin22a_c_t_d_3 +fin22a.c.t.d.4,,worldBank/fin22a_c_t_d_4 +fin22a.c.t.d.5,,worldBank/fin22a_c_t_d_5 +fin22a.c.t.d.6,,worldBank/fin22a_c_t_d_6 +fin22a.c.t.d.7,,worldBank/fin22a_c_t_d_7 +fin22a.c.t.d.8,,worldBank/fin22a_c_t_d_8 +fin22b.t.d,,worldBank/fin22b_t_d +fin22b.t.d.1,,worldBank/fin22b_t_d_1 +fin22b.t.d.11,,worldBank/fin22b_t_d_11 +fin22b.t.d.12,,worldBank/fin22b_t_d_12 +fin22b.t.d.2,,worldBank/fin22b_t_d_2 +fin22b.t.d.3,,worldBank/fin22b_t_d_3 +fin22b.t.d.4,,worldBank/fin22b_t_d_4 +fin22b.t.d.5,,worldBank/fin22b_t_d_5 +fin22b.t.d.6,,worldBank/fin22b_t_d_6 +fin22b.t.d.7,,worldBank/fin22b_t_d_7 +fin22b.t.d.8,,worldBank/fin22b_t_d_8 +fin26.28.t.d,,worldBank/fin26_28_t_d +fin26.28.t.d.1,,worldBank/fin26_28_t_d_1 +fin26.28.t.d.2,,worldBank/fin26_28_t_d_2 +fin26.t.d,,worldBank/fin26_t_d +fin26.t.d.1,,worldBank/fin26_t_d_1 +fin26.t.d.2,,worldBank/fin26_t_d_2 +fin28.t.d,,worldBank/fin28_t_d +fin28.t.d.1,,worldBank/fin28_t_d_1 +fin28.t.d.2,,worldBank/fin28_t_d_2 +fin30.t.d,,worldBank/fin30_t_d +fin30.t.d.1,,worldBank/fin30_t_d_1 +fin30.t.d.2,,worldBank/fin30_t_d_2 +fin37.38.t.d,,worldBank/fin37_38_t_d +fin37.38.t.d.1,,worldBank/fin37_38_t_d_1 +fin37.38.t.d.2,,worldBank/fin37_38_t_d_2 +fin37.t.d,,worldBank/fin37_t_d +fin37.t.d.1,,worldBank/fin37_t_d_1 +fin37.t.d.2,,worldBank/fin37_t_d_2 +fin38.t.d,,worldBank/fin38_t_d +fin38.t.d.1,,worldBank/fin38_t_d_1 +fin38.t.d.2,,worldBank/fin38_t_d_2 +fin42.t.d,,worldBank/fin42_t_d +fin42.t.d.1,,worldBank/fin42_t_d_1 +fin42.t.d.2,,worldBank/fin42_t_d_2 +fin7.t.d,,worldBank/fin7_t_d +fin7.t.d.1,,worldBank/fin7_t_d_1 +fin7.t.d.11,,worldBank/fin7_t_d_11 +fin7.t.d.12,,worldBank/fin7_t_d_12 +fin7.t.d.2,,worldBank/fin7_t_d_2 +fin7.t.d.3,,worldBank/fin7_t_d_3 +fin7.t.d.4,,worldBank/fin7_t_d_4 +fin7.t.d.5,,worldBank/fin7_t_d_5 +fin7.t.d.6,,worldBank/fin7_t_d_6 +fin7.t.d.7,,worldBank/fin7_t_d_7 +fin7.t.d.8,,worldBank/fin7_t_d_8 +fin9N.10N.t.d,,worldBank/fin9N_10N_t_d +fin9N.10N.t.d.1,,worldBank/fin9N_10N_t_d_1 +fin9N.10N.t.d.2,,worldBank/fin9N_10N_t_d_2 +fing2p.t.d,,worldBank/fing2p_t_d +fing2p.t.d.1,,worldBank/fing2p_t_d_1 +fing2p.t.d.2,,worldBank/fing2p_t_d_2 +FM.AST.CGOV.ZG.M3,,worldBank/FM_AST_CGOV_ZG_M3 +FM.AST.DOMO.ZG.M3,,worldBank/FM_AST_DOMO_ZG_M3 +FM.AST.DOMS.CN,,worldBank/FM_AST_DOMS_CN +FM.AST.NFRG.CN,,worldBank/FM_AST_NFRG_CN +FM.AST.PRVT.GD.ZS,dcs:Percent,worldBank/FM_AST_PRVT_GD_ZS +FM.AST.PRVT.ZG.M3,,worldBank/FM_AST_PRVT_ZG_M3 +FM.LBL.BMNY.CN,,worldBank/FM_LBL_BMNY_CN +FM.LBL.BMNY.GD.ZS,dcs:Percent,worldBank/FM_LBL_BMNY_GD_ZS +FM.LBL.BMNY.IR.ZS,dcs:Percent,worldBank/FM_LBL_BMNY_IR_ZS +FM.LBL.BMNY.ZG,,worldBank/FM_LBL_BMNY_ZG +FP.CPI.TOTL,,worldBank/FP_CPI_TOTL +FP.CPI.TOTL.ZG,,worldBank/FP_CPI_TOTL_ZG +FP.WPI.TOTL,,worldBank/FP_WPI_TOTL +FR.INR.DPST,,worldBank/FR_INR_DPST +FR.INR.LEND,,worldBank/FR_INR_LEND +FR.INR.LNDP,,worldBank/FR_INR_LNDP +FR.INR.RINR,,worldBank/FR_INR_RINR +FR.INR.RISK,,worldBank/FR_INR_RISK +FS.AST.CGOV.GD.ZS,dcs:Percent,worldBank/FS_AST_CGOV_GD_ZS +FS.AST.DOMO.GD.ZS,dcs:Percent,worldBank/FS_AST_DOMO_GD_ZS +FS.AST.DOMS.GD.ZS,dcs:Percent,worldBank/FS_AST_DOMS_GD_ZS +FS.AST.PRVT.GD.ZS,dcs:Percent,worldBank/FS_AST_PRVT_GD_ZS +FX.OWN.TOTL.40.ZS,dcs:Percent,worldBank/FX_OWN_TOTL_40_ZS +FX.OWN.TOTL.60.ZS,dcs:Percent,worldBank/FX_OWN_TOTL_60_ZS +FX.OWN.TOTL.FE.ZS,dcs:Percent,worldBank/FX_OWN_TOTL_FE_ZS +FX.OWN.TOTL.MA.ZS,dcs:Percent,worldBank/FX_OWN_TOTL_MA_ZS +FX.OWN.TOTL.OL.ZS,dcs:Percent,worldBank/FX_OWN_TOTL_OL_ZS +FX.OWN.TOTL.PL.ZS,dcs:Percent,worldBank/FX_OWN_TOTL_PL_ZS +FX.OWN.TOTL.SO.ZS,dcs:Percent,worldBank/FX_OWN_TOTL_SO_ZS +FX.OWN.TOTL.YG.ZS,dcs:Percent,worldBank/FX_OWN_TOTL_YG_ZS +FX.OWN.TOTL.ZS,dcs:Percent,worldBank/FX_OWN_TOTL_ZS +g20.made.t.d,,worldBank/g20_made_t_d +g20.made.t.d.1,,worldBank/g20_made_t_d_1 +g20.made.t.d.2,,worldBank/g20_made_t_d_2 +g20.receive.t.d,,worldBank/g20_receive_t_d +g20.receive.t.d.1,,worldBank/g20_receive_t_d_1 +g20.receive.t.d.2,,worldBank/g20_receive_t_d_2 +g20.t.d,,worldBank/g20_t_d +g20.t.d.1,,worldBank/g20_t_d_1 +g20.t.d.2,,worldBank/g20_t_d_2 +GB.XPD.RSDV.GD.ZS,dcs:Percent,worldBank/GB_XPD_RSDV_GD_ZS +GC.AST.TOTL.CN,,worldBank/GC_AST_TOTL_CN +GC.AST.TOTL.GD.ZS,dcs:Percent,worldBank/GC_AST_TOTL_GD_ZS +GC.DOD.TOTL.CN,,worldBank/GC_DOD_TOTL_CN +GC.DOD.TOTL.GD.ZS,dcs:Percent,worldBank/GC_DOD_TOTL_GD_ZS +GC.LBL.TOTL.CN,,worldBank/GC_LBL_TOTL_CN +GC.LBL.TOTL.GD.ZS,dcs:Percent,worldBank/GC_LBL_TOTL_GD_ZS +GC.NFN.TOTL.CN,,worldBank/GC_NFN_TOTL_CN +GC.NFN.TOTL.GD.ZS,dcs:Percent,worldBank/GC_NFN_TOTL_GD_ZS +GC.NLD.TOTL.CN,,worldBank/GC_NLD_TOTL_CN +GC.NLD.TOTL.GD.ZS,dcs:Percent,worldBank/GC_NLD_TOTL_GD_ZS +GC.REV.GOTR.CN,,worldBank/GC_REV_GOTR_CN +GC.REV.GOTR.ZS,dcs:Percent,worldBank/GC_REV_GOTR_ZS +GC.REV.SOCL.CN,,worldBank/GC_REV_SOCL_CN +GC.REV.SOCL.ZS,dcs:Percent,worldBank/GC_REV_SOCL_ZS +GC.REV.XGRT.CN,,worldBank/GC_REV_XGRT_CN +GC.REV.XGRT.GD.ZS,dcs:Percent,worldBank/GC_REV_XGRT_GD_ZS +GC.TAX.EXPT.CN,,worldBank/GC_TAX_EXPT_CN +GC.TAX.EXPT.ZS,dcs:Percent,worldBank/GC_TAX_EXPT_ZS +GC.TAX.GSRV.CN,,worldBank/GC_TAX_GSRV_CN +GC.TAX.GSRV.RV.ZS,dcs:Percent,worldBank/GC_TAX_GSRV_RV_ZS +GC.TAX.GSRV.VA.ZS,dcs:Percent,worldBank/GC_TAX_GSRV_VA_ZS +GC.TAX.IMPT.CN,,worldBank/GC_TAX_IMPT_CN +GC.TAX.IMPT.ZS,dcs:Percent,worldBank/GC_TAX_IMPT_ZS +GC.TAX.INTT.CN,,worldBank/GC_TAX_INTT_CN +GC.TAX.INTT.RV.ZS,dcs:Percent,worldBank/GC_TAX_INTT_RV_ZS +GC.TAX.OTHR.CN,,worldBank/GC_TAX_OTHR_CN +GC.TAX.OTHR.RV.ZS,dcs:Percent,worldBank/GC_TAX_OTHR_RV_ZS +GC.TAX.TOTL.CN,,worldBank/GC_TAX_TOTL_CN +GC.TAX.TOTL.GD.ZS,dcs:Percent,worldBank/GC_TAX_TOTL_GD_ZS +GC.TAX.YPKG.CN,,worldBank/GC_TAX_YPKG_CN +GC.TAX.YPKG.RV.ZS,dcs:Percent,worldBank/GC_TAX_YPKG_RV_ZS +GC.TAX.YPKG.ZS,dcs:Percent,worldBank/GC_TAX_YPKG_ZS +GC.XPN.COMP.CN,,worldBank/GC_XPN_COMP_CN +GC.XPN.COMP.ZS,dcs:Percent,worldBank/GC_XPN_COMP_ZS +GC.XPN.GSRV.CN,,worldBank/GC_XPN_GSRV_CN +GC.XPN.GSRV.ZS,dcs:Percent,worldBank/GC_XPN_GSRV_ZS +GC.XPN.INTP.CN,,worldBank/GC_XPN_INTP_CN +GC.XPN.INTP.RV.ZS,dcs:Percent,worldBank/GC_XPN_INTP_RV_ZS +GC.XPN.INTP.ZS,dcs:Percent,worldBank/GC_XPN_INTP_ZS +GC.XPN.OTHR.CN,,worldBank/GC_XPN_OTHR_CN +GC.XPN.OTHR.ZS,dcs:Percent,worldBank/GC_XPN_OTHR_ZS +GC.XPN.TOTL.CN,,worldBank/GC_XPN_TOTL_CN +GC.XPN.TOTL.GD.ZS,dcs:Percent,worldBank/GC_XPN_TOTL_GD_ZS +GC.XPN.TRFT.CN,,worldBank/GC_XPN_TRFT_CN +GC.XPN.TRFT.ZS,dcs:Percent,worldBank/GC_XPN_TRFT_ZS +GE.EST,,worldBank/GE_EST +GE.NO.SRC,,worldBank/GE_NO_SRC +GE.PER.RNK,,worldBank/GE_PER_RNK +GE.PER.RNK.LOWER,,worldBank/GE_PER_RNK_LOWER +GE.PER.RNK.UPPER,,worldBank/GE_PER_RNK_UPPER +GE.STD.ERR,,worldBank/GE_STD_ERR +GF.XPD.BUDG.ZS,dcs:Percent,worldBank/GF_XPD_BUDG_ZS +GFDD.AI.01,,worldBank/GFDD_AI_01 +GFDD.AI.02,,worldBank/GFDD_AI_02 +GFDD.AI.05,,worldBank/GFDD_AI_05 +GFDD.AI.06,,worldBank/GFDD_AI_06 +GFDD.AI.07,,worldBank/GFDD_AI_07 +GFDD.AI.18,,worldBank/GFDD_AI_18 +GFDD.AI.20,,worldBank/GFDD_AI_20 +GFDD.AI.21,,worldBank/GFDD_AI_21 +GFDD.AI.25,,worldBank/GFDD_AI_25 +GFDD.AM.01,,worldBank/GFDD_AM_01 +GFDD.AM.02,,worldBank/GFDD_AM_02 +GFDD.AM.03,,worldBank/GFDD_AM_03 +GFDD.DI.01,,worldBank/GFDD_DI_01 +GFDD.DI.02,,worldBank/GFDD_DI_02 +GFDD.DI.03,,worldBank/GFDD_DI_03 +GFDD.DI.04,,worldBank/GFDD_DI_04 +GFDD.DI.05,,worldBank/GFDD_DI_05 +GFDD.DI.06,,worldBank/GFDD_DI_06 +GFDD.DI.07,,worldBank/GFDD_DI_07 +GFDD.DI.08,,worldBank/GFDD_DI_08 +GFDD.DI.09,,worldBank/GFDD_DI_09 +GFDD.DI.10,,worldBank/GFDD_DI_10 +GFDD.DI.11,,worldBank/GFDD_DI_11 +GFDD.DI.12,,worldBank/GFDD_DI_12 +GFDD.DI.13,,worldBank/GFDD_DI_13 +GFDD.DI.14,,worldBank/GFDD_DI_14 +GFDD.DM.01,,worldBank/GFDD_DM_01 +GFDD.DM.02,,worldBank/GFDD_DM_02 +GFDD.DM.03,,worldBank/GFDD_DM_03 +GFDD.DM.04,,worldBank/GFDD_DM_04 +GFDD.DM.05,,worldBank/GFDD_DM_05 +GFDD.DM.06,,worldBank/GFDD_DM_06 +GFDD.DM.07,,worldBank/GFDD_DM_07 +GFDD.DM.08,,worldBank/GFDD_DM_08 +GFDD.DM.09,,worldBank/GFDD_DM_09 +GFDD.DM.10,,worldBank/GFDD_DM_10 +GFDD.DM.11,,worldBank/GFDD_DM_11 +GFDD.DM.12,,worldBank/GFDD_DM_12 +GFDD.DM.13,,worldBank/GFDD_DM_13 +GFDD.DM.14,,worldBank/GFDD_DM_14 +GFDD.DM.15,,worldBank/GFDD_DM_15 +GFDD.DM.16,,worldBank/GFDD_DM_16 +GFDD.EI.01,,worldBank/GFDD_EI_01 +GFDD.EI.02,,worldBank/GFDD_EI_02 +GFDD.EI.03,,worldBank/GFDD_EI_03 +GFDD.EI.04,,worldBank/GFDD_EI_04 +GFDD.EI.05,,worldBank/GFDD_EI_05 +GFDD.EI.06,,worldBank/GFDD_EI_06 +GFDD.EI.07,,worldBank/GFDD_EI_07 +GFDD.EI.08,,worldBank/GFDD_EI_08 +GFDD.EI.09,,worldBank/GFDD_EI_09 +GFDD.EI.10,,worldBank/GFDD_EI_10 +GFDD.EM.01,,worldBank/GFDD_EM_01 +GFDD.OI.01,,worldBank/GFDD_OI_01 +GFDD.OI.02,,worldBank/GFDD_OI_02 +GFDD.OI.06,,worldBank/GFDD_OI_06 +GFDD.OI.07,,worldBank/GFDD_OI_07 +GFDD.OI.08,,worldBank/GFDD_OI_08 +GFDD.OI.09,,worldBank/GFDD_OI_09 +GFDD.OI.10,,worldBank/GFDD_OI_10 +GFDD.OI.11,,worldBank/GFDD_OI_11 +GFDD.OI.12,,worldBank/GFDD_OI_12 +GFDD.OI.13,,worldBank/GFDD_OI_13 +GFDD.OI.14,,worldBank/GFDD_OI_14 +GFDD.OI.15,,worldBank/GFDD_OI_15 +GFDD.OI.16,,worldBank/GFDD_OI_16 +GFDD.OI.16a,,worldBank/GFDD_OI_16a +GFDD.OI.17,,worldBank/GFDD_OI_17 +GFDD.OI.18,,worldBank/GFDD_OI_18 +GFDD.OI.19,,worldBank/GFDD_OI_19 +GFDD.OI.20a,,worldBank/GFDD_OI_20a +GFDD.OM.01,,worldBank/GFDD_OM_01 +GFDD.OM.02,,worldBank/GFDD_OM_02 +GFDD.SI.01,,worldBank/GFDD_SI_01 +GFDD.SI.02,,worldBank/GFDD_SI_02 +GFDD.SI.03,,worldBank/GFDD_SI_03 +GFDD.SI.04,,worldBank/GFDD_SI_04 +GFDD.SI.05,,worldBank/GFDD_SI_05 +GFDD.SI.06,,worldBank/GFDD_SI_06 +GFDD.SI.07,,worldBank/GFDD_SI_07 +GFDD.SM.01,,worldBank/GFDD_SM_01 +GPFI4,,worldBank/GPFI4 +HD.HCI.AMRT,,worldBank/HD_HCI_AMRT +HD.HCI.AMRT.FE,,worldBank/HD_HCI_AMRT_FE +HD.HCI.AMRT.MA,,worldBank/HD_HCI_AMRT_MA +HD.HCI.EYRS,,worldBank/HD_HCI_EYRS +HD.HCI.EYRS.FE,,worldBank/HD_HCI_EYRS_FE +HD.HCI.EYRS.MA,,worldBank/HD_HCI_EYRS_MA +HD.HCI.HLOS,,worldBank/HD_HCI_HLOS +HD.HCI.HLOS.FE,,worldBank/HD_HCI_HLOS_FE +HD.HCI.HLOS.MA,,worldBank/HD_HCI_HLOS_MA +HD.HCI.LAYS,,worldBank/HD_HCI_LAYS +HD.HCI.LAYS.FE,,worldBank/HD_HCI_LAYS_FE +HD.HCI.LAYS.MA,,worldBank/HD_HCI_LAYS_MA +HD.HCI.MORT,,worldBank/HD_HCI_MORT +HD.HCI.MORT.FE,,worldBank/HD_HCI_MORT_FE +HD.HCI.MORT.MA,,worldBank/HD_HCI_MORT_MA +HD.HCI.OVRL,,worldBank/HD_HCI_OVRL +HD.HCI.OVRL.FE,,worldBank/HD_HCI_OVRL_FE +HD.HCI.OVRL.LB,,worldBank/HD_HCI_OVRL_LB +HD.HCI.OVRL.LB.FE,,worldBank/HD_HCI_OVRL_LB_FE +HD.HCI.OVRL.LB.MA,,worldBank/HD_HCI_OVRL_LB_MA +HD.HCI.OVRL.MA,,worldBank/HD_HCI_OVRL_MA +HD.HCI.OVRL.UB,,worldBank/HD_HCI_OVRL_UB +HD.HCI.OVRL.UB.FE,,worldBank/HD_HCI_OVRL_UB_FE +HD.HCI.OVRL.UB.MA,,worldBank/HD_HCI_OVRL_UB_MA +HF.UHC.CONS.ZS,dcs:Percent,worldBank/HF_UHC_CONS_ZS +HF.UHC.NOP1.CG,,worldBank/HF_UHC_NOP1_CG +HF.UHC.NOP1.ZS,dcs:Percent,worldBank/HF_UHC_NOP1_ZS +HF.UHC.NOP2.CG,,worldBank/HF_UHC_NOP2_CG +HF.UHC.NOP2.ZS,dcs:Percent,worldBank/HF_UHC_NOP2_ZS +HF.UHC.NOP3.CG,,worldBank/HF_UHC_NOP3_CG +HF.UHC.NOP3.ZS,dcs:Percent,worldBank/HF_UHC_NOP3_ZS +HF.UHC.NOP4.CG,,worldBank/HF_UHC_NOP4_CG +HF.UHC.NOP4.ZS,dcs:Percent,worldBank/HF_UHC_NOP4_ZS +HF.UHC.NOPX.ZS,dcs:Percent,worldBank/HF_UHC_NOPX_ZS +HF.UHC.OOP.CG,,worldBank/HF_UHC_OOP_CG +HF.UHC.OOP.ZS,dcs:Percent,worldBank/HF_UHC_OOP_ZS +HF.UHC.OOPC.10.ZS,dcs:Percent,worldBank/HF_UHC_OOPC_10_ZS +HF.UHC.OOPC.25.ZS,dcs:Percent,worldBank/HF_UHC_OOPC_25_ZS +i_ATMs_pop,,worldBank/i_ATMs_pop +i_branches_A1_pop,,worldBank/i_branches_A1_pop +i_deposit_acc_A1_pop,,worldBank/i_deposit_acc_A1_pop +IC.FRM.FEMM.ZS,dcs:Percent,worldBank/IC_FRM_FEMM_ZS +IC.FRM.FEMO.ZS,dcs:Percent,worldBank/IC_FRM_FEMO_ZS +IC.IMP.CSBC.CD,dcs:USDollar,worldBank/IC_IMP_CSBC_CD +IC.IMP.CSDC.CD,dcs:USDollar,worldBank/IC_IMP_CSDC_CD +IC.REG.COST.PC.FE.ZS,dcs:Percent,worldBank/IC_REG_COST_PC_FE_ZS +IC.REG.COST.PC.MA.ZS,dcs:Percent,worldBank/IC_REG_COST_PC_MA_ZS +IC.REG.COST.PC.ZS,dcs:Percent,worldBank/IC_REG_COST_PC_ZS +IC.REG.DURS,,worldBank/IC_REG_DURS +IC.REG.DURS.FE,,worldBank/IC_REG_DURS_FE +IC.REG.DURS.MA,,worldBank/IC_REG_DURS_MA +IC.TAX.PAYM,,worldBank/IC_TAX_PAYM +IC.TAX.PRFT.CP.ZS,dcs:Percent,worldBank/IC_TAX_PRFT_CP_ZS +IC.TAX.TOTL.CP.ZS,dcs:Percent,worldBank/IC_TAX_TOTL_CP_ZS +IE.PPI.ENGY.CD,dcs:USDollar,worldBank/IE_PPI_ENGY_CD +IE.PPI.TELE.CD,dcs:USDollar,worldBank/IE_PPI_TELE_CD +IE.PPI.TRAN.CD,dcs:USDollar,worldBank/IE_PPI_TRAN_CD +IE.PPI.WATR.CD,dcs:USDollar,worldBank/IE_PPI_WATR_CD +IE.PPN.ENGY.CD,dcs:USDollar,worldBank/IE_PPN_ENGY_CD +IE.PPN.TRAN.CD,dcs:USDollar,worldBank/IE_PPN_TRAN_CD +IP.PAT.NRES,,worldBank/IP_PAT_NRES +IP.PAT.RESD,,worldBank/IP_PAT_RESD +IP.TMK.NRCT,,worldBank/IP_TMK_NRCT +IP.TMK.RSCT,,worldBank/IP_TMK_RSCT +IS.AIR.DPRT,,worldBank/IS_AIR_DPRT +IS.AIR.GOOD.MT.K1,,worldBank/IS_AIR_GOOD_MT_K1 +IS.AIR.PSGR,,worldBank/IS_AIR_PSGR +IS.RRS.GOOD.MT.K6,,worldBank/IS_RRS_GOOD_MT_K6 +IS.RRS.PASG.KM,,worldBank/IS_RRS_PASG_KM +IS.RRS.TOTL.KM,,worldBank/IS_RRS_TOTL_KM +IS.SHP.GOOD.TU,,worldBank/IS_SHP_GOOD_TU +IT.CEL.SETS,,worldBank/IT_CEL_SETS +IT.CEL.SETS.P2,,worldBank/IT_CEL_SETS_P2 +IT.CMP.PCMP.P2,,worldBank/IT_CMP_PCMP_P2 +IT.MLT.MAIN,,worldBank/IT_MLT_MAIN +IT.MLT.MAIN.P2,,worldBank/IT_MLT_MAIN_P2 +IT.NET.BBND,,worldBank/IT_NET_BBND +IT.NET.BBND.P2,,worldBank/IT_NET_BBND_P2 +IT.NET.SECR,,worldBank/IT_NET_SECR +IT.NET.SECR.P6,,worldBank/IT_NET_SECR_P6 +IT.NET.USER.P2,,worldBank/IT_NET_USER_P2 +IT.NET.USER.ZS,dcs:Percent,worldBank/IT_NET_USER_ZS +LP.EXP.DURS.MD,,worldBank/LP_EXP_DURS_MD +mobileaccount.t.d,,worldBank/mobileaccount_t_d +mobileaccount.t.d.1,,worldBank/mobileaccount_t_d_1 +mobileaccount.t.d.2,,worldBank/mobileaccount_t_d_2 +MS.MIL.MPRT.KD,,worldBank/MS_MIL_MPRT_KD +MS.MIL.TOTL.P1,,worldBank/MS_MIL_TOTL_P1 +MS.MIL.TOTL.TF.ZS,dcs:Percent,worldBank/MS_MIL_TOTL_TF_ZS +MS.MIL.XPRT.KD,,worldBank/MS_MIL_XPRT_KD +NE.CON.GOVT.CD,dcs:USDollar,worldBank/NE_CON_GOVT_CD +NE.CON.GOVT.CN,,worldBank/NE_CON_GOVT_CN +NE.CON.GOVT.KD,,worldBank/NE_CON_GOVT_KD +NE.CON.GOVT.KD.ZG,,worldBank/NE_CON_GOVT_KD_ZG +NE.CON.GOVT.KN,,worldBank/NE_CON_GOVT_KN +NE.CON.GOVT.ZS,dcs:Percent,worldBank/NE_CON_GOVT_ZS +NE.CON.PRVT.CD,dcs:USDollar,worldBank/NE_CON_PRVT_CD +NE.CON.PRVT.CN,,worldBank/NE_CON_PRVT_CN +NE.CON.PRVT.CN.AD,,worldBank/NE_CON_PRVT_CN_AD +NE.CON.PRVT.KD,,worldBank/NE_CON_PRVT_KD +NE.CON.PRVT.KD.ZG,,worldBank/NE_CON_PRVT_KD_ZG +NE.CON.PRVT.KN,,worldBank/NE_CON_PRVT_KN +NE.CON.PRVT.PC.KD,,worldBank/NE_CON_PRVT_PC_KD +NE.CON.PRVT.PC.KD.ZG,,worldBank/NE_CON_PRVT_PC_KD_ZG +NE.CON.PRVT.PP.CD,dcs:USDollar,worldBank/NE_CON_PRVT_PP_CD +NE.CON.PRVT.PP.KD,,worldBank/NE_CON_PRVT_PP_KD +NE.CON.PRVT.ZS,dcs:Percent,worldBank/NE_CON_PRVT_ZS +NE.CON.TOTL.CD,dcs:USDollar,worldBank/NE_CON_TOTL_CD +NE.CON.TOTL.CN,,worldBank/NE_CON_TOTL_CN +NE.CON.TOTL.KD,,worldBank/NE_CON_TOTL_KD +NE.CON.TOTL.KD.ZG,,worldBank/NE_CON_TOTL_KD_ZG +NE.CON.TOTL.KN,,worldBank/NE_CON_TOTL_KN +NE.CON.TOTL.ZS,dcs:Percent,worldBank/NE_CON_TOTL_ZS +NE.DAB.DEFL.ZS,dcs:Percent,worldBank/NE_DAB_DEFL_ZS +NE.DAB.TOTL.CD,dcs:USDollar,worldBank/NE_DAB_TOTL_CD +NE.DAB.TOTL.CN,,worldBank/NE_DAB_TOTL_CN +NE.DAB.TOTL.KD,,worldBank/NE_DAB_TOTL_KD +NE.DAB.TOTL.KN,,worldBank/NE_DAB_TOTL_KN +NE.DAB.TOTL.ZS,dcs:Percent,worldBank/NE_DAB_TOTL_ZS +NE.EXP.GNFS.CD,dcs:USDollar,worldBank/NE_EXP_GNFS_CD +NE.EXP.GNFS.CN,,worldBank/NE_EXP_GNFS_CN +NE.EXP.GNFS.KD,,worldBank/NE_EXP_GNFS_KD +NE.EXP.GNFS.KD.ZG,,worldBank/NE_EXP_GNFS_KD_ZG +NE.EXP.GNFS.KN,,worldBank/NE_EXP_GNFS_KN +NE.EXP.GNFS.ZS,dcs:Percent,worldBank/NE_EXP_GNFS_ZS +NE.GDI.FPRV.CN,,worldBank/NE_GDI_FPRV_CN +NE.GDI.FPRV.ZS,dcs:Percent,worldBank/NE_GDI_FPRV_ZS +NE.GDI.FTOT.CD,dcs:USDollar,worldBank/NE_GDI_FTOT_CD +NE.GDI.FTOT.CN,,worldBank/NE_GDI_FTOT_CN +NE.GDI.FTOT.KD,,worldBank/NE_GDI_FTOT_KD +NE.GDI.FTOT.KD.ZG,,worldBank/NE_GDI_FTOT_KD_ZG +NE.GDI.FTOT.KN,,worldBank/NE_GDI_FTOT_KN +NE.GDI.FTOT.ZS,dcs:Percent,worldBank/NE_GDI_FTOT_ZS +NE.GDI.STKB.CD,dcs:USDollar,worldBank/NE_GDI_STKB_CD +NE.GDI.STKB.CN,,worldBank/NE_GDI_STKB_CN +NE.GDI.STKB.KN,,worldBank/NE_GDI_STKB_KN +NE.GDI.TOTL.CD,dcs:USDollar,worldBank/NE_GDI_TOTL_CD +NE.GDI.TOTL.CN,,worldBank/NE_GDI_TOTL_CN +NE.GDI.TOTL.KD,,worldBank/NE_GDI_TOTL_KD +NE.GDI.TOTL.KD.ZG,,worldBank/NE_GDI_TOTL_KD_ZG +NE.GDI.TOTL.KN,,worldBank/NE_GDI_TOTL_KN +NE.GDI.TOTL.ZS,dcs:Percent,worldBank/NE_GDI_TOTL_ZS +NE.IMP.GNFS.CD,dcs:USDollar,worldBank/NE_IMP_GNFS_CD +NE.IMP.GNFS.CN,,worldBank/NE_IMP_GNFS_CN +NE.IMP.GNFS.KD,,worldBank/NE_IMP_GNFS_KD +NE.IMP.GNFS.KD.ZG,,worldBank/NE_IMP_GNFS_KD_ZG +NE.IMP.GNFS.KN,,worldBank/NE_IMP_GNFS_KN +NE.IMP.GNFS.ZS,dcs:Percent,worldBank/NE_IMP_GNFS_ZS +NE.RSB.GNFS.CD,dcs:USDollar,worldBank/NE_RSB_GNFS_CD +NE.RSB.GNFS.CN,,worldBank/NE_RSB_GNFS_CN +NE.RSB.GNFS.KN,,worldBank/NE_RSB_GNFS_KN +NE.RSB.GNFS.ZS,dcs:Percent,worldBank/NE_RSB_GNFS_ZS +NE.TRD.GNFS.ZS,dcs:Percent,worldBank/NE_TRD_GNFS_ZS +NV.AGR.EMPL.KD,,worldBank/NV_AGR_EMPL_KD +NV.AGR.TOTL.CD,dcs:USDollar,worldBank/NV_AGR_TOTL_CD +NV.AGR.TOTL.CN,,worldBank/NV_AGR_TOTL_CN +NV.AGR.TOTL.KD,,worldBank/NV_AGR_TOTL_KD +NV.AGR.TOTL.KD.ZG,,worldBank/NV_AGR_TOTL_KD_ZG +NV.AGR.TOTL.KN,,worldBank/NV_AGR_TOTL_KN +NV.AGR.TOTL.ZS,dcs:Percent,worldBank/NV_AGR_TOTL_ZS 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+UIS.T.2,,worldBank/UIS_T_2 +UIS.T.2.F,,worldBank/UIS_T_2_F +UIS.T.23.GPV,,worldBank/UIS_T_23_GPV +UIS.T.23.GPV.F,,worldBank/UIS_T_23_GPV_F +UIS.T.23.V,,worldBank/UIS_T_23_V +UIS.T.23.V.F,,worldBank/UIS_T_23_V_F +UIS.T.3,,worldBank/UIS_T_3 +UIS.T.3.F,,worldBank/UIS_T_3_F +UIS.T.4,,worldBank/UIS_T_4 +UIS.T.4.F,,worldBank/UIS_T_4_F +UIS.T.5.B,,worldBank/UIS_T_5_B +UIS.T.5.B.F,,worldBank/UIS_T_5_B_F +UIS.TE_100000.56,,worldBank/UIS_TE_100000_56 +UIS.TE_100000.56.F,,worldBank/UIS_TE_100000_56_F +UIS.TE_100000.56.M,,worldBank/UIS_TE_100000_56_M +UIS.TEP.5.B,,worldBank/UIS_TEP_5_B +UIS.TEP.5.B.F,,worldBank/UIS_TEP_5_B_F +UIS.TEP.5.B.M,,worldBank/UIS_TEP_5_B_M +UIS.TEP.8,,worldBank/UIS_TEP_8 +UIS.TEP.8.F,,worldBank/UIS_TEP_8_F +UIS.TEP.8.M,,worldBank/UIS_TEP_8_M +UIS.TRTP.0,,worldBank/UIS_TRTP_0 +UIS.TRTP.0.F,,worldBank/UIS_TRTP_0_F +UIS.TRTP.0.M,,worldBank/UIS_TRTP_0_M +UIS.TRTP.1.GPI,,worldBank/UIS_TRTP_1_GPI +UIS.TRTP.2,,worldBank/UIS_TRTP_2 +UIS.TRTP.2.F,,worldBank/UIS_TRTP_2_F +UIS.TRTP.2.M,,worldBank/UIS_TRTP_2_M +UIS.TRTP.23.GPI,,worldBank/UIS_TRTP_23_GPI +UIS.TRTP.3,,worldBank/UIS_TRTP_3 +UIS.UAEP.1,,worldBank/UIS_UAEP_1 +UIS.UAEP.1.F,,worldBank/UIS_UAEP_1_F +UIS.UAEP.1.M,,worldBank/UIS_UAEP_1_M +UIS.UAPP.1,,worldBank/UIS_UAPP_1 +UIS.UAPP.1.F,,worldBank/UIS_UAPP_1_F +UIS.UAPP.1.M,,worldBank/UIS_UAPP_1_M +UIS.UAPP.23,,worldBank/UIS_UAPP_23 +UIS.UAPP.23.F,,worldBank/UIS_UAPP_23_F +UIS.UAPP.23.M,,worldBank/UIS_UAPP_23_M +UIS.XGDP.0.FSGOV,,worldBank/UIS_XGDP_0_FSGOV +UIS.XGDP.1.FSGOV,,worldBank/UIS_XGDP_1_FSGOV +UIS.XGDP.23.FSGOV,,worldBank/UIS_XGDP_23_FSGOV +UIS.XGDP.4.FSGOV,,worldBank/UIS_XGDP_4_FSGOV +UIS.XGDP.4.FSGOV.FDINSTADM.FFD,,worldBank/UIS_XGDP_4_FSGOV_FDINSTADM_FFD +UIS.XGDP.56.FSGOV,,worldBank/UIS_XGDP_56_FSGOV +UIS.XGOVEXP.IMF.0,,worldBank/UIS_XGOVEXP_IMF_0 +UIS.XGOVEXP.IMF.1,,worldBank/UIS_XGOVEXP_IMF_1 +UIS.XGOVEXP.IMF.2,,worldBank/UIS_XGOVEXP_IMF_2 +UIS.XGOVEXP.IMF.23,,worldBank/UIS_XGOVEXP_IMF_23 +UIS.XGOVEXP.IMF.3,,worldBank/UIS_XGOVEXP_IMF_3 +UIS.XGOVEXP.IMF.4,,worldBank/UIS_XGOVEXP_IMF_4 +UIS.XGOVEXP.IMF.56,,worldBank/UIS_XGOVEXP_IMF_56 +UIS.XPUBP.2,,worldBank/UIS_XPUBP_2 +UIS.XPUBP.3,,worldBank/UIS_XPUBP_3 +UIS.XPUBP.UK,,worldBank/UIS_XPUBP_UK +UIS.XSPENDP.0.FDPUB.FNCAP,,worldBank/UIS_XSPENDP_0_FDPUB_FNCAP +UIS.XSPENDP.0.FDPUB.FNCUR,,worldBank/UIS_XSPENDP_0_FDPUB_FNCUR +UIS.XSPENDP.0.FDPUB.FNNONS,,worldBank/UIS_XSPENDP_0_FDPUB_FNNONS +UIS.XSPENDP.0.FDPUB.FNS,,worldBank/UIS_XSPENDP_0_FDPUB_FNS +UIS.XSPENDP.1.FDPUB.FNCAP,,worldBank/UIS_XSPENDP_1_FDPUB_FNCAP +UIS.XSPENDP.1.FDPUB.FNCUR,,worldBank/UIS_XSPENDP_1_FDPUB_FNCUR +UIS.XSPENDP.1.FDPUB.FNNONS,,worldBank/UIS_XSPENDP_1_FDPUB_FNNONS +UIS.XSPENDP.1.FDPUB.FNS,,worldBank/UIS_XSPENDP_1_FDPUB_FNS +UIS.XSPENDP.2.FDPUB.FNCAP,,worldBank/UIS_XSPENDP_2_FDPUB_FNCAP +UIS.XSPENDP.2.FDPUB.FNCUR,,worldBank/UIS_XSPENDP_2_FDPUB_FNCUR +UIS.XSPENDP.2.FDPUB.FNNONS,,worldBank/UIS_XSPENDP_2_FDPUB_FNNONS +UIS.XSPENDP.2.FDPUB.FNS,,worldBank/UIS_XSPENDP_2_FDPUB_FNS +UIS.XSPENDP.23.FDPUB.FNCAP,,worldBank/UIS_XSPENDP_23_FDPUB_FNCAP +UIS.XSPENDP.23.FDPUB.FNCUR,,worldBank/UIS_XSPENDP_23_FDPUB_FNCUR +UIS.XSPENDP.23.FDPUB.FNNONS,,worldBank/UIS_XSPENDP_23_FDPUB_FNNONS +UIS.XSPENDP.23.FDPUB.FNS,,worldBank/UIS_XSPENDP_23_FDPUB_FNS +UIS.XSPENDP.3.FDPUB.FNCAP,,worldBank/UIS_XSPENDP_3_FDPUB_FNCAP +UIS.XSPENDP.3.FDPUB.FNCUR,,worldBank/UIS_XSPENDP_3_FDPUB_FNCUR +UIS.XSPENDP.3.FDPUB.FNNONS,,worldBank/UIS_XSPENDP_3_FDPUB_FNNONS +UIS.XSPENDP.3.FDPUB.FNS,,worldBank/UIS_XSPENDP_3_FDPUB_FNS +UIS.XSPENDP.4.FDPUB.FNCUR,,worldBank/UIS_XSPENDP_4_FDPUB_FNCUR +UIS.XSPENDP.56.FDPUB.FNCUR,,worldBank/UIS_XSPENDP_56_FDPUB_FNCUR +UIS.XSPENDP.56.FDPUB.FNS,,worldBank/UIS_XSPENDP_56_FDPUB_FNS +UIS.XSPENDP.FDPUB.FNCAP,,worldBank/UIS_XSPENDP_FDPUB_FNCAP +UIS.XSPENDP.FDPUB.FNNONS,,worldBank/UIS_XSPENDP_FDPUB_FNNONS +UIS.XSPENDP.FDPUB.FNS,,worldBank/UIS_XSPENDP_FDPUB_FNS +UIS.XUNIT.GDPCAP.2.FSGOV,,worldBank/UIS_XUNIT_GDPCAP_2_FSGOV +UIS.XUNIT.GDPCAP.3.FSGOV,,worldBank/UIS_XUNIT_GDPCAP_3_FSGOV +UIS.XUNIT.GDPCAP.4.FSGOV,,worldBank/UIS_XUNIT_GDPCAP_4_FSGOV +UIS.XUNIT.PPP.1.FSGOV,,worldBank/UIS_XUNIT_PPP_1_FSGOV +UIS.XUNIT.PPP.2.FSGOV,,worldBank/UIS_XUNIT_PPP_2_FSGOV +UIS.XUNIT.PPP.23.FSGOV,,worldBank/UIS_XUNIT_PPP_23_FSGOV +UIS.XUNIT.PPP.3.FSGOV,,worldBank/UIS_XUNIT_PPP_3_FSGOV +UIS.XUNIT.PPP.56.FSGOV,,worldBank/UIS_XUNIT_PPP_56_FSGOV +UIS.XUNIT.PPPCONST.1.FSGOV,,worldBank/UIS_XUNIT_PPPCONST_1_FSGOV +UIS.XUNIT.PPPCONST.2.FSGOV,,worldBank/UIS_XUNIT_PPPCONST_2_FSGOV +UIS.XUNIT.PPPCONST.23.FSGOV,,worldBank/UIS_XUNIT_PPPCONST_23_FSGOV +UIS.XUNIT.PPPCONST.3.FSGOV,,worldBank/UIS_XUNIT_PPPCONST_3_FSGOV +UIS.XUNIT.PPPCONST.56.FSGOV,,worldBank/UIS_XUNIT_PPPCONST_56_FSGOV +UIS.XUNIT.US.1.FSGOV,,worldBank/UIS_XUNIT_US_1_FSGOV +UIS.XUNIT.US.2.FSGOV,,worldBank/UIS_XUNIT_US_2_FSGOV +UIS.XUNIT.US.23.FSGOV,,worldBank/UIS_XUNIT_US_23_FSGOV +UIS.XUNIT.US.3.FSGOV,,worldBank/UIS_XUNIT_US_3_FSGOV +UIS.XUNIT.US.4.FSGOV,,worldBank/UIS_XUNIT_US_4_FSGOV +UIS.XUNIT.US.56.FSGOV,,worldBank/UIS_XUNIT_US_56_FSGOV +UIS.XUNIT.USCONST.1.FSGOV,,worldBank/UIS_XUNIT_USCONST_1_FSGOV +UIS.XUNIT.USCONST.2.FSGOV,,worldBank/UIS_XUNIT_USCONST_2_FSGOV +UIS.XUNIT.USCONST.23.FSGOV,,worldBank/UIS_XUNIT_USCONST_23_FSGOV +UIS.XUNIT.USCONST.3.FSGOV,,worldBank/UIS_XUNIT_USCONST_3_FSGOV +UIS.XUNIT.USCONST.56.FSGOV,,worldBank/UIS_XUNIT_USCONST_56_FSGOV +VA.EST,,worldBank/VA_EST +VA.NO.SRC,,worldBank/VA_NO_SRC +VA.PER.RNK,,worldBank/VA_PER_RNK +VA.PER.RNK.LOWER,,worldBank/VA_PER_RNK_LOWER +VA.PER.RNK.UPPER,,worldBank/VA_PER_RNK_UPPER +VA.STD.ERR,,worldBank/VA_STD_ERR +VC.BTL.DETH,,worldBank/VC_BTL_DETH +VC.IDP.NWCV,,worldBank/VC_IDP_NWCV +VC.IDP.NWDS,,worldBank/VC_IDP_NWDS +VC.IDP.TOCV,,worldBank/VC_IDP_TOCV +VC.IHR.PSRC.FE.P5,,worldBank/VC_IHR_PSRC_FE_P5 +VC.IHR.PSRC.MA.P5,,worldBank/VC_IHR_PSRC_MA_P5 +VC.IHR.PSRC.P5,,worldBank/VC_IHR_PSRC_P5 +XGDP.23.FSGOV.FDINSTADM.FFD,,worldBank/XGDP_23_FSGOV_FDINSTADM_FFD +XGDP.56.FSGOV.FDINSTADM.FFD,,worldBank/XGDP_56_FSGOV_FDINSTADM_FFD \ No newline at end of file diff --git a/scripts/world_bank/datasets/wb.tmcf b/scripts/world_bank/datasets/wb.tmcf new file mode 100644 index 0000000000..c1c41823ac --- /dev/null +++ b/scripts/world_bank/datasets/wb.tmcf @@ -0,0 +1,8 @@ +Node: E:World_Bank_Temp->E0 +typeOf: dcs:StatVarObservation +variableMeasured: C:World_Bank_Temp->statvar +measurementMethod: C:World_Bank_Temp->measurementmethod +observationDate: C:World_Bank_Temp->observationdate +observationPeriod: "P1Y" +observationAbout: C:World_Bank_Temp->observationabout +value: C:World_Bank_Temp->observationvalue \ No newline at end of file diff --git a/util/file_util.py b/util/file_util.py index d5622f0bfd..9393a7ea3a 100644 --- a/util/file_util.py +++ b/util/file_util.py @@ -810,7 +810,7 @@ def file_get_gspread_worksheet( def file_copy_from_spreadsheet(url: str, worksheet_title: str = None, - dst_filename: str = '') -> list[str]: + dst_filename: str = '') -> list: '''Copies the spreadsheet to a local file and returns the filename. Args: diff --git a/util/latlng_recon_geojson.py b/util/latlng_recon_geojson.py index 4731d16295..9a301e543e 100644 --- a/util/latlng_recon_geojson.py +++ b/util/latlng_recon_geojson.py @@ -16,10 +16,11 @@ See latlng_recon_geojson_test.py for usage example. """ +from shapely import geometry import datacommons as dc import json import logging -from shapely import geometry +import time import urllib _WORLD = 'Earth' diff --git a/util/latlng_recon_service_test.py b/util/latlng_recon_service_test.py index d03e104508..83c42375d1 100644 --- a/util/latlng_recon_service_test.py +++ b/util/latlng_recon_service_test.py @@ -36,8 +36,8 @@ def test_basic(self): self.assertEqual(idmap_out['cascal_mtv'], [ 'zip/94041', 'ipcc_50/37.25_-122.25_USA', 'geoId/sch0626310', 'geoId/sch0626280', 'geoId/0649670', 'geoId/0618', - 'geoId/0608592830', 'geoId/06085509600', 'geoId/06085', 'geoId/06', - 'country/USA' + 'geoId/0608592830', 'geoId/060855096001', 'geoId/06085509600', + 'geoId/06085', 'geoId/06', 'country/USA' ]) self.assertEqual(idmap_out['besant_beach_chennai'], [ 'wikidataId/Q15116', 'wikidataId/Q1445', 'ipcc_50/12.75_80.25_IND',