powerplant/users/ml/data_prep/data_utils.py
def missing_data_analisis(self, df):
        """Analisis of missing data if any"""
        df_na = (df.isnull().sum() / len(df)) * 100
        df_na = df_na.drop(df_na[df_na == 0].index).sort_values(ascending=False)[:30]
        missing_data = pd.DataFrame({'Missing Ratio' :df_na})
        print(missing_data.head(20))
Analisis of missing data if any
Analisis of missing data if any
Analisis of missing data if any
def missing_data_analisis(self, df):
        df_na = (df.isnull().sum() / len(df)) * 100
        df_na = df_na.drop(df_na[df_na == 0].index).sort_values(ascending=False)[:30]
        missing_data = pd.DataFrame({'Missing Ratio' :df_na})
        print(missing_data.head(20))
def missing_data_analisis ( self , df ) : df_na = ( df . isnull ( ) . sum ( ) / len ( df ) ) * 100 df_na = df_na . drop ( df_na [ df_na == 0 ] . index ) . sort_values ( ascending = False ) [ : 30 ] missing_data = pd . DataFrame ( { 'Missing Ratio' : df_na } ) print ( missing_data . head ( 20 ) )
Analisis of missing data if any
Analisis of missing data if any
"""Analisis of missing data if any"""
self
df