ss1 = df['y_bad'].groupby(df['applied_from']).count().reset_index().rename(columns ={'y_bad':'y_bad_count'})
ss2= df.groupby('applied_from')['y_bad'].apply(lambda x:x.count()).reset_index()
ss3 =df.groupby('applied_from')['y_bad'].agg(['sum','count'])
