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candle.data_utils.drop_impute_and_scale_dataframe

candle.data_utils.drop_impute_and_scale_dataframe#

candle.data_utils.drop_impute_and_scale_dataframe(df, scaling='std', imputing='mean', dropna='all')#

Impute missing values with mean and scale data included in pandas dataframe.

Parameters:

  • df (pandas dataframe) – dataframe to process

  • scaling (string) – String describing type of scaling to apply. ‘maxabs’ [-1,1], ‘minmax’ [0,1], ‘std’, or None, optional (Default ‘std’)

  • imputing (string) – String describing type of imputation to apply. ‘mean’ replace missing values with mean value along the column, ‘median’ replace missing values with median value along the column, ‘most_frequent’ replace missing values with most frequent value along column (Default: ‘mean’).

  • dropna (string) – String describing strategy for handling missing values. ‘all’ if all values are NA, drop that column. ‘any’ if any NA values are present, dropt that column. (Default: ‘all’).

Return type:

Returns the data frame after handling missing values and scaling.

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