rebalance-gender.py

def rebalance_gender(df, data_type):
   if data_type == 0:
       df_female_true = df[(df['Sex'] == 'Female') & (df['PINCP'] == True)]
       df_else = df[~((df['Sex'] == 'Female') & (df['PINCP'] == True))]
   else:
       df_female_true = df[(df['Sex_Female'] == 1) & (df['PINCP'] == True)]
       df_else = df[~((df['Sex_Female'] == 1) & (df['PINCP'] == True))]


   if data_type == 0:
       num_samples = len(df[(df['Sex'] == 'Male') & (df['PINCP'] == True)])
   else:
       num_samples = len(df[(df['Sex_Male'] == 1) & (df['PINCP'] == True)])
   # Resample female target segment so that they are the same size as male
   df_female_true_resampled = resample(
       df_female_true,
       replace=True,
       n_samples=num_samples,
       random_state=1 # include random seed so we can perform same sampling on each data set
       )
   return pd.concat([df_female_true_resampled, df_else])