Add nice formatting for notes in all pages

README.md

@@ -94,4 +94,4 @@ For general questions or issues, please open an issue on our
 [issues](https://github.com/datacommonsorg/docsite/issues) page. For all other
 questions, please [send us feedback](https://docs.google.com/forms/d/e/1FAIpQLScJTtNlIItT-uSPXI98WT6yNlavF-kf5JS0jMrCvJ9TPLmelg/viewform).
 
-**Note** - This is not an officially supported Google product.
+> **Note** - This is not an officially supported Google product.

api/index.md

@@ -19,7 +19,7 @@ Data Commons provides several different ways to access its resources:
 * A [REST API](/api/rest/v2) that can be used on the command line as well as in any language with an HTTP library.
 * [Python](/api/python) and [Pandas](/api/pandas) wrappers.
 
-**Note:** The Python and Pandas APIs wrap the [v1](/api/rest/v1) version of the REST APIs and have not yet been updated to v2.
+> **Note:** The Python and Pandas APIs wrap the [v1](/api/rest/v1) version of the REST APIs and have not yet been updated to v2.
 
 The endpoints can be roughly grouped into four categories:
 

api/pandas/index.md

@@ -15,7 +15,7 @@ the Pandas API, and supplemental functions help with directly creating
 objects using data from the Data Commons knowledge graph for common
 use cases. 
 
-**Note:** The Pandas API only supports [v1](/api/rest/v1/index.html) of the REST APIs. 
+> **Note:** The Pandas API only supports [v1](/api/rest/v1/index.html) of the REST APIs. 
 
 Before proceeding, make sure you have followed the setup instructions below.
 

api/python/index.md

@@ -13,7 +13,7 @@ programmatically access nodes in the Data Commons knowledge graph. This package
 allows users to explore the structure of the graph, integrate statistics from
 the graph into data analysis workflows and much more. 
 
-**Note:** The Python API only supports [v1](/api/rest/v1/index.html) of the REST APIs. 
+> **Note:** The Python API only supports [v1](/api/rest/v1/index.html) of the REST APIs. 
 
 Before proceeding, make sure you have followed the setup instructions below.
 

api/rest/v2/getting_started.md

@@ -80,7 +80,7 @@ curl -X POST \
 
 API keys are required in any REST API request. To obtain an API key, please see [Get API key](/api//rest/v2/index.html#get-key).
 
-**Note:** If you are sending API requests to a custom Data Commons instance, do _not_ include any API key in the requests.
+> **Note:** If you are sending API requests to a custom Data Commons instance, do _not_ include any API key in the requests.
 
 To include an API key, add your API key to the URL as a query parameter by appending <code>?key=<var>API_KEY</var></code>.
 

api/rest/v2/observation.md

@@ -174,7 +174,7 @@ With `select=date` and `select=value` specified, the response looks like:
 
 Specify `date=LATEST` to get the latest observations and values. In this example, we select the entity by its DCID using `entity.dcids`.
 
-Note: When sending a GET request, you need to use the following percent codes for reserved characters: 
+> Note: When sending a GET request, you need to use the following percent codes for reserved characters: 
 - `%2F` for `/`
 
 Parameters:
@@ -355,7 +355,7 @@ with date and value for each variable
 ([`Count_Person`](https://datacommons.org/tools/statvar#sv=Count_Person)) and
 entity (all counties in California).
 
-Note: When sending a GET request, you need to use the following escape codes for reserved characters:
+> Note: When sending a GET request, you need to use the following escape codes for reserved characters:
 - `%3C` for `<`
 - `%2B` for `+`
 - `%7B` for `{`

api/rest/v2/resolve.md

@@ -21,21 +21,16 @@ that its DCID is `geoId/0667000`. You can also provide the type of entity
 (country, city, state, etc.) to disambiguate (Georgia the country vs. Georgia
 the US state).
 
-<div markdown="span" class="alert alert-info" role="alert">
-   <span class="material-icons md-16">info </span><b>Note:</b><br />
-   Currently, this endpoint only supports [place](/glossary.html#place) entities.
-</div>
+> **Note**: Currently, this endpoint only supports [place](/glossary.html#place) entities.
 
 
-<div markdown="span" class="alert alert-danger" role="alert">
-   <span class="material-icons exclamation-icon">priority_high</span><b>IMPORTANT:</b><br />
+> **IMPORTANT:**
    This endpoint relies on name-based geocoding and is prone to inaccuracies.
    One common pattern is ambiguous place names that exist in different
    countries, states, etc. For example, there is at least one popular city
    called "Cambridge" in both the UK and USA. Thus, for more precise results,
    please provide as much context in the description as possible. For example,
    to resolve Cambridge in USA, pass "Cambridge, MA, USA" if you can.
-</div>
 
 ## Request
 
@@ -124,10 +119,8 @@ The response looks like:
 | dominantType | string | Optional field which, where present, disambiguates between multiple results. |
 {: .doc-table}
 
-<div markdown="span" class="alert alert-info" role="alert">
-  <span class="material-icons md-16">info </span><b>Note:</b><br />
+> **Note:**
   There is a deprecated field `resolvedIds` that is currently returned by the API. It will be removed soon. Examples below omit this redundant field.
-</div>
 
 ## Examples
 
@@ -174,7 +167,7 @@ Response:
 
 This queries for the DCID of "Mountain View" by its coordinates. This is most often represented by the [`latitude`](https://datacommons.org/browser/latitude) and [`longitude`](https://datacommons.org/browser/longitude) properties on a node. Since the API only supports querying a single property, use the synthetic `geoCoordinate` property. To specify the latitude and longitude, use the `#` sign to separate both values. This returns all the places in the graph that contains the coordinate.
 
-Note: If using a GET request, use the percent code `%23` for `#`.
+> Note: If using a GET request, use the percent code `%23` for `#`.
 
 Parameters:
 {: .example-box-title}
@@ -307,7 +300,7 @@ Response:
 This queries for the DCID of "Georgia". Unlike in the previous example, here
 we also specify its type using a filter and only get one place in the response.
 
-Note: When sending a GET request, you need to use the following percent codes for reserved characters:
+> Note: When sending a GET request, you need to use the following percent codes for reserved characters:
 - `%7B` for `{`
 - `%7D` for `}`
 
@@ -351,7 +344,7 @@ Response:
 
 This queries for the DCIDs of "Mountain View" and "New York City".
 
-Note: When sending a GET request, you need to use the following percent codes for reserved characters:
+> Note: When sending a GET request, you need to use the following percent codes for reserved characters:
 - `%20` for space
 - `%7B` for `{`
 - `%7D` for `}`

api/rest/v2/sparql.md

@@ -13,11 +13,11 @@ This endpoint makes it possible to query the Data Commons knowledge graph using
 [SPARQL](https://www.w3.org/TR/rdf-sparql-query/). SPARQL is a query language developed to retrieve data from [RDF graph](https://en.wikipedia.org/wiki/Resource_Description_Framework) content on the web. It leverages the graph structure innate in the data it 
 queries to return specific information.
 
-**Note:** Data Commons only supports a limited subset of SPARQL functionality at this time: specifically, only the keywords `WHERE`, `ORDER BY`, `DISTINCT`, and `LIMIT` are supported.
+> **Note:** Data Commons only supports a limited subset of SPARQL functionality at this time: specifically, only the keywords `WHERE`, `ORDER BY`, `DISTINCT`, and `LIMIT` are supported.
 
 ## Request
 
-Note: GET requests are not provided because they are inconvenient to use with SPARQL.
+> Note: GET requests are not provided because they are inconvenient to use with SPARQL.
 
 <p class="api-header">
 POST request

custom_dc/build_image.md

@@ -47,7 +47,7 @@ You will need to build a local image in any of the following cases:
 
 Rather than building from "head", that is, the very latest changes in Github, which may not have been tested, we recommend that you use the tested "release" equivalent of the stable Docker image. This release uses the tag `customdc_stable`, and is available at [https://github.com/datacommonsorg/website/releases/tag/customdc_stable](https://github.com/datacommonsorg/website/releases/tag/customdc_stable).
 
-Note: If you are working on a large-scale customization, we recommend that you use a version control system to manage your code. We provide procedures for Github, and assume the following:
+> **Note:** If you are working on a large-scale customization, we recommend that you use a version control system to manage your code. We provide procedures for Github, and assume the following:
 - You have a Github account and project.
 - You have created a fork off the base Data Commons `website` repo (https://github.com/datacommonsorg/website) and a remote that points to it, and that you will push to that fork. 
 

custom_dc/custom_data.md

@@ -56,7 +56,7 @@ San Jose,2023,400,400,300,0
 
 The _ENTITY_ is an existing property in the Data Commons knowledge graph that is used to describe an entity, most commonly a place. The best way to think of the entity type is as a key that could be used to join to other data sets. The column heading can be expressed as any existing place-related property; see [Place types](/place_types.html) for a full list. It may also be any of the special DCID prefixes listed in [Special place names](#special-names). 
 
-**Note:** The type of the entities in a single file should be unique; do not mix multiple entity types in the same CSV file. For example, if you have observations for cities and counties, put all the city data in one CSV file and all the county data in another one.
+> **Note:** The type of the entities in a single file should be unique; do not mix multiple entity types in the same CSV file. For example, if you have observations for cities and counties, put all the city data in one CSV file and all the county data in another one.
 
 The _DATE_ is the date of the observation and should be in the format _YYYY_, _YYYY_-_MM_, or _YYYY_-_MM_-_DD_. The heading can be anything, although as a best practice, we recommend using a corresponding identifier, such as `year`, `month` or `date`.
 
@@ -253,7 +253,7 @@ Edit the `env.list` file as follows:
 - Set the `INPUT_DIR` variable to the directory where your input files are stored. 
 - Set the `OUTPUT_DIR` variable to the directory where you would like the output files to be stored. This can be the same or different from the input directory. When you rerun the Docker data management container, it will create a `datacommons` subdirectory under this directory.
 
-**Notes:**
+> **Notes:**
 - NL support increases the startup time of your server and consumes more resources. If you don't want NL functionality, you can disable it by updating the `ENABLE_MODEL` flag from `true` to `false`.
 - If you are storing your source code in a public/open-source version control system, we recommend that you do not store the environment variables file containing secrets. Instead, store it locally only. If you are using git/Github, you can add the file name to the `.gitignore` file.
 

custom_dc/custom_ui.md

@@ -84,4 +84,4 @@ Alternatively, if you have existing existing CSS and Javascript files, put them
 
 See [`server/templates/custom_dc/custom/new.html`](https://github.com/datacommonsorg/website/blob/master/server/templates/custom_dc/custom/new.html) as an example.
 
-Note: Currently, making changes to any of the files in the `static/` directory, even if you're testing locally, requires that you rebuild a local version of the repo to pick up the changes, as described in [Build a local image](/custom_dc/build_image.html#build-repo). We plan to fix this in the near future.
+> **Note:** Currently, making changes to any of the files in the `static/` directory, even if you're testing locally, requires that you rebuild a local version of the repo to pick up the changes, as described in [Build a local image](/custom_dc/build_image.html#build-repo). We plan to fix this in the near future.

custom_dc/data_cloud.md

@@ -44,7 +44,7 @@ This stores the CSV and JSON files that you will upload whenever your data chang
 1. In the **Bucket Details** page, click **Create Folder** to create a new folder to hold your data and name it as desired.
 1. Optionally, create separate folders to hold input and output files, or just use the same one as for the input. 
 
-   Note: If you plan to run the data management container locally, you only need to create a single folder to hold the output files.
+   **Note:** If you plan to run the data management container locally, you only need to create a single folder to hold the output files.
 1. Record the folder path(s) as <code>gs://<var>BUCKET_NAME</var>/<var>FOLDER_PATH</var></code> for setting the `INPUT_DIR` and `OUTPUT_DIR` environment variables below. 
 
 ### Step 3: Create a Google Cloud SQL instance
@@ -120,7 +120,7 @@ Now set environment variables:
 1. Navigate to the folder you created in the earlier step.
 1. Click **Upload Files**, and select all your CSV files and `config.json`.
 
-Note: Do not upload the local `datacommons` subdirectory or its files.
+> **Note:** Do not upload the local `datacommons` subdirectory or its files.
 
 As you are iterating on changes to the source CSV and JSON files, you can re-upload them at any time, either overwriting existing files or creating new folders. To load them into Cloud SQL, you run the Cloud Run job you created above. 
 

custom_dc/index.md

@@ -73,7 +73,7 @@ A custom Data Commons site runs in a Docker container on Google Cloud Platform (
 - A [Docker](http://docker.com) account
 - If you will be customizing the site's UI, familiarity with the Python [Flask](https://flask.palletsprojects.com/en/3.0.x/#) web framework and [Jinja](https://jinja.palletsprojects.com/en/3.1.x/templates/) HTML templating
 
-    **Note:** Data Commons does not support local Windows development natively. If you wish to develop Data Commons on Windows, you will need to use the [Windows Subsystem for Linux](https://learn.microsoft.com/en-us/windows/wsl/about).
+> **Note:** Data Commons does not support local Windows development natively. If you wish to develop Data Commons on Windows, you will need to use the [Windows Subsystem for Linux](https://learn.microsoft.com/en-us/windows/wsl/about).
 
 If you already have an account with another cloud provider, we can provide a connector; please contact us if you are interested in this option.
 

custom_dc/quickstart.md

@@ -154,7 +154,7 @@ docker run -it \
 gcr.io/datcom-ci/datacommons-services:stable
 ```
 
-Note: If you are running on Linux, depending on whether you have created a ["sudoless" Docker group](https://docs.docker.com/engine/install/linux-postinstall/), you may need to preface every `docker` invocation with `sudo`.
+> Note: If you are running on Linux, depending on whether you have created a ["sudoless" Docker group](https://docs.docker.com/engine/install/linux-postinstall/), you may need to preface every `docker` invocation with `sudo`.
 
 This command does the following:
 
@@ -211,7 +211,7 @@ A custom instance can accept [REST API](/api/rest/v2/index.html) requests at the
 http://localhost:8080/core/api/v2/observation?entity.dcids=country%2FCAN&select=entity&select=variable&select=value&select=date&variable.dcids=average_annual_wage
 ```
 
-Note: You do not need to specify an API key as a [query parameter](/api/rest/v2/getting_started.html#query-param).
+> Note: You do not need to specify an API key as a [query parameter](/api/rest/v2/getting_started.html#query-param).
 
 If you select **Prettyprint**, you should see output like this:
 

glossary.md

@@ -21,10 +21,7 @@ This page contains a selection of key terms important to understanding the struc
 
 A group of entities sharing some characteristic. Interchangeably referred to in a Data Commons context as `Cohort` and `CohortSet`. Examples include [the CDC's list of the United States' 500 largest cities](https://datacommons.org/browser/CDC500_City).
 
-<div markdown="span" class="alert alert-info" role="alert">
-    <span class="material-icons md-16">info </span><b>Note:</b>
-    The type [`Cohort`](https://datacommons.org/browser/Cohort) is a legacy type not used by the Sheets method `DCCOHORTMEMBERS()`.
-</div>
+> The type [`Cohort`](https://datacommons.org/browser/Cohort) is a legacy type not used by the Sheets method [`DCCOHORTMEMBERS()`](/api/sheets/get_cohort_members.html).
 
 ### [Date](https://datacommons.org/browser/date)
 {: #date}

place_types.md

@@ -12,7 +12,7 @@ countries, states, and provinces to more granular classifications like counties,
 cities, and postal codes. This page provides the DCIDs and a description of
 place types available in our APIs and tools.
 
-**Note:** Not all data is available for all place types. Sources often don’t
+> **Note:** Not all data is available for all place types. Sources often don’t
 provide data at all levels of granularity. You can check which place types have
 data available for a specific variable using the
 [Statistical Variable Explorer](https://datacommons.org/tools/statvar).