Source code for

Build a scaler normalized
``pandas.DataFrame`` from an existing ``pandas.DataFrame``

import sklearn.preprocessing as preproc
import analysis_engine.consts as ae_consts
import spylunking.log.setup_logging as log_utils

log = log_utils.build_colorized_logger(

[docs]def build_scaler_dataset_from_df( df, min_feature=-1, max_feature=1): """build_scaler_dataset_from_df Helper for building scaler datasets from an existing ``pandas.DataFrame`` returns a dictionary: .. code-block:: python return { 'status': status, # NOT_RUN | SUCCESS | ERR 'scaler': scaler, # MinMaxScaler 'df': df # scaled df from df arg } :param df: ``pandas.DataFrame`` to convert to scalers :param min_feature: min feature range for scaler normalization with default ``-1`` :param max_feature: max feature range for scaler normalization with default ``1`` """ status = ae_consts.NOT_RUN scaler = None output_df = None res = { 'status': status, 'scaler': scaler, 'df': output_df } try: log.debug( f'building scaler range=[{min_feature}, {max_feature}]') scaler = preproc.MinMaxScaler( feature_range=( min_feature, max_feature)) f'scaler.fit_transform(df) rows={len(df.index)}') output_df = scaler.fit_transform( df.values) status = ae_consts.SUCCESS except Exception as e: log.error( f'failed build_scaler_dataset_from_df ' f'with ex={e} ' f'range=[{min_feature}, {max_feature}]') status = ae_consts.ERR # end of try/ex res = { 'status': status, 'scaler': scaler, 'df': output_df } return res
# end of build_scaler_dataset_from_df