在 Pandas 中组合具有不同索引的数据帧

Combine Dataframes With Different Indexes in Pandas

提问by jojo

I have two dataframes:

我有两个数据框：

df1 : here index is ip

            accountname      name
ip
192.168.1.1        aaaa  john doe
192.168.1.2        bbbb  jane doe

df2 : index is accountname

             gsm
accountname
aaaa         850
bbbb         860
cccc         870

I have to combine two dataframe and add gsm column to df1.

我必须组合两个数据框并将 gsm 列添加到 df1。

            ip accountname      name  gsm
0  192.168.1.1        aaaa  john doe  850
1  192.168.1.2        bbbb  jane doe  860

These dataframes has different indexes and I couldnt reach right data. any advice would be appreciated.

这些数据帧具有不同的索引，我无法获得正确的数据。任何意见，将不胜感激。

回答by Zero

You could use mergewith indexas well.

你也可以使用mergewith index。

In [2313]: df1.merge(df2, left_on='accountname', right_index=True).reset_index()
Out[2313]:
            ip accountname      name  gsm
0  192.168.1.1        aaaa  john doe  850
1  192.168.1.2        bbbb  jane doe  860

回答by jezrael

Use join:

使用join：

df = df1.join(df2, on='accountname', how='inner').reset_index()
print (df)
            ip accountname      name  gsm
0  192.168.1.1        aaaa  john doe  850
1  192.168.1.2        bbbb  jane doe  860