如何基于 pandas 中的列合并两个数据框 [英] how to merge two dataframes based on a column in pandas

问题描述

我有两个数据帧，

 df1=pd.DataFrame({"Req":["Req 1","Req 2","Req 3"],"Count":[1,2,1]})        
    Req     Count
0   Req 1   1
1   Req 2   2
2   Req 3   1

df2 = pd.DataFrame（{ Req： [需求1，需求2]，计数：[0,1]}）

    Req    Count
0   Req 1   0
1   Req 2   1

我正在尝试根据要求列合并这些df

I am trying to merge these df's based on "Req" column

我想要的输出是

    Req    total  from_1 from_2
    Req 1   1       1     0
    Req 2   3       2     1
    Req 3   1       1     0

我尝试了 pd.merge（df1，df2，on = Req，）但是没有提供我想要的输出，请帮助，谢谢！！

I tried pd.merge(df1, df2, on = "Req", ) but it is not giving my desired output, please help, thanks in advance!

推荐答案

您可以使用 合并 左联接，替换 NaN s，重命名列，最后添加新列分配：

You can use merge with left join, replace NaNs, rename columns and last add new column with assign:

df = (pd.merge(df1, df2, on = "Req", how='left')
        .fillna(0)
        .rename(columns={'Count_x':'from_1','Count_y':'from_2'})
        .assign(total=lambda x: x['from_1'] + x['from_2'])
      )
print (df)
   from_1    Req  from_2  total
0       1  Req 1     0.0    1.0
1       2  Req 2     1.0    3.0
2       1  Req 3     0.0    1.0

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