Skip to content

Instantly share code, notes, and snippets.

@dhananjaychaudhari26
Last active February 2, 2021 16:17
Show Gist options
  • Save dhananjaychaudhari26/ad53be2ac50cf8d23e5d6dd2838777f4 to your computer and use it in GitHub Desktop.
Save dhananjaychaudhari26/ad53be2ac50cf8d23e5d6dd2838777f4 to your computer and use it in GitHub Desktop.
df['card_id_total'] = df['new_card_id_size']+df['hist_card_id_size'] df['card_id_cnt_total'] = df['new_card_id_count']+df['hist_card_id_count'] df['card_id_cnt_ratio'] = df['new_card_id_count']/df['hist_card_id_count'] df['purchase_amount_total'] = df['new_purchase_amount_sum']+df['hist_purchase_amount_sum']
 df['purchase_amount_mean'] = df['new_purchase_amount_mean']+df['hist_purchase_amount_mean']
 df['purchase_amount_max'] = df['new_purchase_amount_max']+df['hist_purchase_amount_max']
 df['purchase_amount_min'] = df['new_purchase_amount_min']+df['hist_purchase_amount_min']
 df['purchase_amount_ratio'] = df['new_purchase_amount_sum']/df['hist_purchase_amount_sum']
 df['month_diff_mean'] = df['new_month_diff_mean']+df['hist_month_diff_mean']
 df['month_diff_ratio'] = df['new_month_diff_mean']/df['hist_month_diff_mean']
 df['month_lag_mean'] = df['new_month_lag_mean']+df['hist_month_lag_mean']
 df['month_lag_max'] = df['new_month_lag_max']+df['hist_month_lag_max']
 df['month_lag_min'] = df['new_month_lag_min']+df['hist_month_lag_min']
 df['category_1_mean'] = df['new_category_1_mean']+df['hist_category_1_mean']
 df['installments_total'] = df['new_installments_sum']+df['hist_installments_sum']
 df['installments_mean'] = df['new_installments_mean']+df['hist_installments_mean']
 df['installments_max'] = df['new_installments_max']+df['hist_installments_max']
 df['installments_ratio'] = df['new_installments_sum']/df['hist_installments_sum']
 df['price_total'] = df['purchase_amount_total'] / df['installments_total']
 df['price_mean'] = df['purchase_amount_mean'] / df['installments_mean']
 df['price_max'] = df['purchase_amount_max'] / df['installments_max']
 df['duration_mean'] = df['new_duration_mean']+df['hist_duration_mean']
 df['duration_min'] = df['new_duration_min']+df['hist_duration_min']
 df['duration_max'] = df['new_duration_max']+df['hist_duration_max']
 df['amount_month_ratio_mean']=df['new_amount_month_ratio_mean']+df['hist_amount_month_ratio_mean']
 df['amount_month_ratio_min']=df['new_amount_month_ratio_min']+df['hist_amount_month_ratio_min']
 df['amount_month_ratio_max']=df['new_amount_month_ratio_max']+df['hist_amount_month_ratio_max']
 df['new_CLV'] = df['new_card_id_count'] * df['new_purchase_amount_sum'] / df['new_month_diff_mean']
 df['hist_CLV'] = df['hist_card_id_count'] * df['hist_purchase_amount_sum'] / df['hist_month_diff_mean']
 df['CLV_ratio'] = df['new_CLV'] / df['hist_CLV']
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment