使用 groupby Pandas 从两个数据框中连接分类和数字列答案

【问题标题】：Joining columns categorical and numerical from two dataframes using groupby Pandas使用 groupby Pandas 从两个数据框中连接分类和数字列
【发布时间】：2019-10-30 14:12:01
【问题描述】：

以下是我从 CSV 文件生成报告所需的格式

User_Name Disposition_Code   Call_Received Calls Abandoned
0   person1           Solved      2            4
1   person2           Solved      1            4
2   person1           Solved      2            3
3   person2       Not_Solved      1            1
4   person3           Solved      11           0


total_record = test.groupby("User Name").agg({"Calls_Received": ['sum']
                                                 , "Calls Abandoned": ['sum']
                                                 , "Total Served In Target %": ['mean']
                                                 , "Total Served After Target": ['sum']})```

结果是


User_Name Calls_Received Calls Abandoned
person 1      4                 7
person 2      2                 5
person 3      11                0

现在我要添加


User_Name Calls_Received Calls Abandoned Solved Not_Solved
person 1      4                 7           2       0
person 2      2                 5           1       1
person 3      11                0           1       0

请帮忙

【问题讨论】：

标签： pandas dataframe group-by

【解决方案1】：

将DataFrame.join 与crosstab 一起使用：

total_record = total_record.join(pd.crosstab(test['User_Name'], test['isposition_Code']))

【讨论】：