ebm.model.column_operations module
- explode_building_category_column(df: DataFrame, unique_columns: List[str]) DataFrame[source]
Explodes the ‘building_category’ column in the DataFrame into multiple columns based on residential and non-residential categories.
Parameters
- dfpd.DataFrame
The input DataFrame containing the ‘building_category’ column.
- unique_columnsList[str]
List of columns to use for de-duplication.
Returns
- pd.DataFrame
The DataFrame with exploded ‘building_category’ columns.
- explode_building_code_column(df: DataFrame, unique_columns: List[str], default_building_code: None | DataFrame = None) DataFrame[source]
Explodes the ‘building_code’ column in the DataFrame into multiple columns based on the provided building_codelist.
Parameters
- dfpd.DataFrame
The input DataFrame containing the ‘building_code’ column.
- unique_columnsList[str]
List of columns to use for de-duplication.
- default_building_codeOptional[pd.DataFrame], optional
DataFrame containing default building_codevalues. If not provided, building_codevalues are read from ‘input/building_codes.csv’.
Returns
- pd.DataFrame
The DataFrame with exploded ‘building_code’ columns.
- explode_unique_columns(df: DataFrame | DataFrameBase, unique_columns: List[str], default_building_code: List[str] | None = None) DataFrame[source]
Explodes ‘building_code’ and ‘building_category’ columns in df.
Parameters
- dfpd.DataFrame
The input DataFrame containing the columns to be exploded.
- unique_columnsList[str]
List of columns to use for de-duplication.
- default_building_codeList[str], optional
List of TEKs to replace default
Returns
- pd.DataFrame
The DataFrame with exploded columns.
- explode_column_alias(df, column, values: list | dict = None, alias='default', de_dup_by: list[str] = None)[source]
Explodes a specified column in the DataFrame into multiple rows based on provided values and alias.
Parameters
- dfpd.DataFrame
The input DataFrame containing the column to be exploded.
- columnstr
The name of the column to be exploded.
- valuesOptional[List[str], dict[str, list[str]], optional
List or dict of values to explode the column by. If not provided, unique values from the column excluding the alias are used.
- aliasstr, optional
The alias to be used for default values. Default is ‘default’. When values is a dict the parameter alias is ignored
- de_dup_byOptional[List[str]], optional
List of columns to use for de-duplication. If not provided, no de-duplication is performed.
Returns
- pd.DataFrame
The DataFrame with the exploded column.
Examples
>>> d_f = pd.DataFrame({'category': ['A', 'B', 'default']}) >>> explode_column_alias(d_f, column='category', values=['A', 'B'], alias='default') category 0 A 1 B 2 A 2 B