如何将两个数据集通过长尾词实现关联与拼接join操作或merge改写？
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本文共计185个文字，预计阅读时间需要1分钟。
python合并两个数据集merged_dataset=pd.merge(dataset3[[user_id, coupon_id, date_received]], t2, on=[user_id, coupon_id], how='left')
计算本月中用户收到相同优惠券的最后一次接收日期merged_dataset['this_month_user_receive_same_coupon_lastone']=merged_dataset.groupby(['user_id', 'coupon_id'])['date_received'].transform('max')
更新日期字段merged_dataset['max_date_received']=merged_dataset['date_received']merged_dataset.loc[merged_dataset['this_month_user_receive_same_coupon_lastone'] !=merged_dataset['date_received'], 'max_date_received']=merged_dataset['this_month_user_receive_same_coupon_lastone']
计算日期差merged_dataset['date_received_diff']=merged_dataset['max_date_received'] - merged_dataset['date_received']
python_两个数据集拼接 dataset3[[user_id,coupon_id,date_received]]t3 pd.merge(t3,t2,on[user_id,coupon_id],howleft)t3[this_month_user_receive_same_coupon_lastone] t3.max_date_received - t3.date_receivedt3[this_month_user_receive_same_coupon_firstone] t3.date_received - t3.min_date_received#根据多个字段就进行mergeother_feature3 pd.merge(t1,t,onuser_id)other_feature3 pd.merge(other_feature3,t3,on[user_id,coupon_id])other_feature3 pd.merge(other_feature3,t4,on[user_id,date_received])other_feature3 pd.merge(other_feature3,t5,on[user_id,coupon_id,date_received])other_feature3 pd.merge(other_feature3,t7,on[user_id,coupon_id,date_received])other_feature3.to_csv(data/other_feature3.csv,indexNone)#拼接数据集#两个数据框合并为一个df_train_stmt pd.concat([df_train_stmt,df_train_stmt_test],axis 0)本文共计185个文字，预计阅读时间需要1分钟。
python合并两个数据集merged_dataset=pd.merge(dataset3[[user_id, coupon_id, date_received]], t2, on=[user_id, coupon_id], how='left')
计算本月中用户收到相同优惠券的最后一次接收日期merged_dataset['this_month_user_receive_same_coupon_lastone']=merged_dataset.groupby(['user_id', 'coupon_id'])['date_received'].transform('max')
更新日期字段merged_dataset['max_date_received']=merged_dataset['date_received']merged_dataset.loc[merged_dataset['this_month_user_receive_same_coupon_lastone'] !=merged_dataset['date_received'], 'max_date_received']=merged_dataset['this_month_user_receive_same_coupon_lastone']
计算日期差merged_dataset['date_received_diff']=merged_dataset['max_date_received'] - merged_dataset['date_received']
python_两个数据集拼接 dataset3[[user_id,coupon_id,date_received]]t3 pd.merge(t3,t2,on[user_id,coupon_id],howleft)t3[this_month_user_receive_same_coupon_lastone] t3.max_date_received - t3.date_receivedt3[this_month_user_receive_same_coupon_firstone] t3.date_received - t3.min_date_received#根据多个字段就进行mergeother_feature3 pd.merge(t1,t,onuser_id)other_feature3 pd.merge(other_feature3,t3,on[user_id,coupon_id])other_feature3 pd.merge(other_feature3,t4,on[user_id,date_received])other_feature3 pd.merge(other_feature3,t5,on[user_id,coupon_id,date_received])other_feature3 pd.merge(other_feature3,t7,on[user_id,coupon_id,date_received])other_feature3.to_csv(data/other_feature3.csv,indexNone)#拼接数据集#两个数据框合并为一个df_train_stmt pd.concat([df_train_stmt,df_train_stmt_test],axis 0)