dataframe_metainformation.py

import pandas as pd



def dataframe_metainformation(df):
     """
   
    Returns Pandas data frame with metainformation 
    
    Parameters
    -----------
    df
        Pandas data frame with item data
   
   
    Returns
    -----------
    DataFrame, Series
        Pandas data frame with item data
    
    Examples
    -----------
    data = pd.read_csv("titanic.csv")
    
    meta = dataframe_metainformation(data)
    print_metainformation(meta)
    
   
   
   """ 
 
    
   
    meta = dict()
    descr = pd.DataFrame({'dtype': df.dtypes, 'NAs': df.isna().sum()})
    categorical_features = descr.loc[descr['dtype'] == 'object'].index.values.tolist()
    numerical_features = descr.loc[descr['dtype'] != 'object'].index.values.tolist()
    numerical_features_na = descr.loc[(descr['dtype'] != 'object') & (descr['NAs'] > 0)].index.values.tolist()
    categorical_features_na = descr.loc[(descr['dtype'] == 'object') & (descr['NAs'] > 0)].index.values.tolist()
    complete_features = descr.loc[descr['NAs'] == 0].index.values.tolist()
    meta['description'] = descr
    meta['categorical_features'] = categorical_features
    meta['categorical_features'] = categorical_features
    meta['categorical_features_na'] = categorical_features_na
    meta['numerical_features'] = numerical_features
    meta['numerical_features_na'] = numerical_features_na
    meta['complete_features'] = complete_features
    return meta

def print_metainformation(meta):
    print('Available types:', meta['description']['dtype'].unique())
    print('{} Features'.format(meta['description'].shape[0]))
    print('{} categorical features'.format(len(meta['categorical_features'])))
    print('{} numerical features'.format(len(meta['numerical_features'])))
    print('{} categorical features with NAs'.format(len(meta['categorical_features_na'])))
    print('{} numerical features with NAs'.format(len(meta['numerical_features_na'])))
    print('{} Complete features'.format(len(meta['complete_features'])))