diff --git a/dataprep/clean/clean_duplication.py b/dataprep/clean/clean_duplication.py index 0a7a0da4d..c58ec14ad 100644 --- a/dataprep/clean/clean_duplication.py +++ b/dataprep/clean/clean_duplication.py @@ -7,6 +7,7 @@ from ipywidgets.widgets import Label, Dropdown, Checkbox, Button, HBox, VBox, Box, Layout, Text import pandas as pd import dask.dataframe as dd +from varname import argname from .clean_duplication_utils import Clusterer @@ -16,10 +17,13 @@ def clean_duplication( - df: Union[pd.DataFrame, dd.DataFrame], column: str, df_var_name: str = "df", page_size: int = 5 + df: Union[pd.DataFrame, dd.DataFrame], + column: str, + df_var_name: str = "default", + page_size: int = 5, ) -> Box: """ - Cleans and standardized duplicate values in a DataFrame. + Cleans and standardizes duplicate values in a DataFrame. Read more in the :ref:`User Guide `. @@ -30,11 +34,11 @@ def clean_duplication( column The name of the column containing duplicate values. df_var_name - The variable name of the DataFrame being cleaned. - This is only needed for creating exported code snippets with - the correct variable name. + Optional parameter containing the variable name of the DataFrame being cleaned. + This is only needed for legacy compatibility with the original veraion of this + function, which needed it to produce correct exported code. - (default: 'df') + (default: 'default') page_size The number of clusters to display on each page. @@ -53,6 +57,8 @@ def clean_duplication( 0 New York 1 New York """ + if df_var_name == "default": + df_var_name = argname(df) return UserInterface(df, column, df_var_name, page_size).display() diff --git a/dataprep/clean/clean_duplication_utils.py b/dataprep/clean/clean_duplication_utils.py index bd9f263ea..98c15e2ea 100644 --- a/dataprep/clean/clean_duplication_utils.py +++ b/dataprep/clean/clean_duplication_utils.py @@ -277,18 +277,18 @@ def final_df(self) -> None: Writes the final dataframe to a pickle file then reads the file from inside the IPython kernel. """ - code = "# dataframe with cleaned string values\ndf_clean" + code = f"# dataframe with cleaned string values\n{self._df_name}_clean" encoded_code = (b64encode(str.encode(code))).decode() final_df = self._df.compute() # create a temporary directory for the dataframe file - tmp_dir = mkdtemp() - df_file = path.join(tmp_dir, "clean_duplication_output.pkl") + tmp_dir = mkdtemp().replace("\\", "/") + df_file = path.join(tmp_dir, "clean_duplication_output.pkl").replace("\\", "/") final_df.to_pickle(df_file) # code to read the file and delete the temporary directory afterwards execute_code = ( "import pandas as pd\n" "import shutil\n" - f"df_clean = pd.read_pickle('{df_file}')\n" + f"{self._df_name}_clean = pd.read_pickle('{df_file}')\n" f"shutil.rmtree('{tmp_dir}')" ) encoded_execute = (b64encode(str.encode(execute_code))).decode() diff --git a/poetry.lock b/poetry.lock index 67e8161ad..0214b598c 100644 --- a/poetry.lock +++ b/poetry.lock @@ -77,7 +77,7 @@ description = "An abstract syntax tree for Python with inference support." name = "astroid" optional = false python-versions = ">=3.6" -version = "2.5.2" +version = "2.5" [package.dependencies] lazy-object-proxy = ">=1.4.0" @@ -87,6 +87,20 @@ wrapt = ">=1.11,<1.13" python = "<3.8" version = ">=1.4.0,<1.5" +[[package]] +category = "main" +description = "Annotate AST trees with source code positions" +name = "asttokens" +optional = false +python-versions = "*" +version = "2.0.5" + +[package.dependencies] +six = "*" + +[package.extras] +test = ["astroid", "pytest"] + [[package]] category = "main" description = "Async generators and context managers for Python 3.5+" @@ -436,6 +450,14 @@ optional = false python-versions = ">=2.7" version = "0.3" +[[package]] +category = "main" +description = "Get the currently executing AST node of a frame, and other information" +name = "executing" +optional = false +python-versions = "*" +version = "0.6.0" + [[package]] category = "main" description = "File-system specification" @@ 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