src.hersteller.data_processing.pipeline_operations.py¶
- class ColumnDropper(target: list)¶
Bases:
BaseEstimator,TransformerMixinDrop the specified columns from the DataFrame.
- Parameters:
target (list) – List of columns to drop
- fit(target)¶
Return self.
- transform(x: DataFrame) DataFrame¶
Drop the specified columns from the DataFrame.
- Parameters:
x (pd.DataFrame) – The Dataframe to transform
- Returns:
The transformed Dataframe
- Return type:
pd.DataFrame
- class ColumnTypeSetter(target: list)¶
Bases:
BaseEstimator,TransformerMixinSet the specified columns to type float in the DataFrame.
- Parameters:
target (list) – List of columns to set
- fit(target)¶
Return self.
- transform(x: DataFrame) DataFrame¶
Set the specified columns to type float in the DataFrame.
- Parameters:
x (pd.DataFrame) – The Dataframe to transform
- Returns:
The transformed Dataframe
- Return type:
pd.DataFrame
- class OneHotEncodePd(target: str, prefix: str, sep: str, required_columns=None)¶
Bases:
BaseEstimator,TransformerMixinOne-hot encode the specified column.
- Parameters:
target (list) – The column to one-hot encode.
prefix (str) – The prefix to use for the one-hot encoded columns.
sep (str) – The separator to use for the one-hot encoded columns.
required_columns (list) – A list of columns that should be present in the DataFrame after one-hot encoding.
- fit(target)¶
Return self.
- transform(x: DataFrame) DataFrame¶
One-hot encode the specified column.
- Parameters:
x (pd.DataFrame) – The Dataframe to transform
- Returns:
The transformed Dataframe
- Return type:
pd.DataFrame
- class MultiOneHotEncodePd(target: str, prefix: str, sep: str, required_columns=None)¶
Bases:
BaseEstimator,TransformerMixinOne-hot encode the specified column into multiple categorical values.
- Parameters:
target (list) – The column to one-hot encode.
prefix (str) – The prefix to use for the one-hot encoded columns.
sep (str) – The separator to use for the one-hot encoded columns.
required_columns (list) – A list of columns that should be present in the DataFrame after one-hot encoding.
- fit(target)¶
Return self.
- transform(x: DataFrame) DataFrame¶
One-hot encode the specified column containing lists of categorical values.
- Parameters:
x (pd.DataFrame) – The Dataframe to transform
- Returns:
The transformed Dataframe
- Return type:
pd.DataFrame
- class NormalizeCols(target: str, feature_range: tuple, column_range: tuple)¶
Bases:
BaseEstimator,TransformerMixinNormalize the specified column to the specified feature range using provided column range.
- Parameters:
target (str) – The column to normalize.
feature_range (tuple) – The desired range of the transformed data.
column_range (tuple) – The actual range of the column data.
- fit(target)¶
Return self.
- transform(x: DataFrame) DataFrame¶
Normalize the specified column to the specified feature range using provided column range.
- Parameters:
x (pd.DataFrame) – The Dataframe to transform
- Returns:
The transformed Dataframe
- Return type:
pd.DataFrame