eflow.data_pipeline_segments.feature_transformer

Functions

check_if_feature_exists(df, feature_name)	Checks if feature exists in the dataframe.
get_parameters(f)	Get a the parameters of a given function definition

Classes

DataPipelineSegment(object_type[, …])	Holds the function name’s and arguments to be pushed to a json file.
FeatureTransformer([segment_id, create_file])	Combines, removes, scales, etc features of a pandas dataframe.

class FeatureTransformer(segment_id=None, create_file=True)

Combines, removes, scales, etc features of a pandas dataframe.

remove_features(df, df_features, feature_names, _add_to_que=True)

Removes unwanted features from the dataframe and saves them to the pipeline segment structure if _add_to_que is set to True.

Args:

df:

Pandas Dataframe to update.

df_features:

DataFrameTypes object to update.

feature_names:

Features to remove

_add_to_que:

Pushes the function to pipeline segment parent if set to ‘True’.