如何使用Python将两个数据集进行关联并执行join或merge操作？

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Python代码简化如下：

python合并两个数据集并计算特定字段result=pd.merge(t3, t2, on=['user_id', 'coupon_id'], how='left')result['this_month_user_receive_same_coupon_lastone']=result['date_received'] - result['max_date_received'] + result['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)