INNER CODE UNIT · Python
result
ashishpatel26/Amazing-Feature-Engineering · feature_cleaning/missing_data.py:14
result = pd.concat([data.isnull().sum(),data.isnull().mean()],axis=1)
result = result.rename(index=str,columns={0:'total missing',1:'proportion'})
if output_path is not None:
result.to_csv(output_path+'missing.csv')
print('result saved at', output_path, 'missing.csv')
return result
def drop_missing(data,axis=0):
"""
Listwise deletion:
excluding all cases (listwise) that have missing values
Parameters
----------
axis: drop cases(0)/columns(1),default 0
Returns