假设我有两个具有不同索引的不同 pandas Dataframe 例如:
df1:
email | other_field
_________________________________________
<a href="https://stackoverflow.com/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="2b4e464a42471a6b4e464a424705484446" rel="noreferrer noopener nofollow">[email protected]</a> | 2
<a href="https://stackoverflow.com/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="fc99919d9590cebc99919d9590d29f9391" rel="noreferrer noopener nofollow">[email protected]</a> | 1
<a href="https://stackoverflow.com/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="9ffaf2fef6f3acdffaf2fef6f3b1fcf0f2" rel="noreferrer noopener nofollow">[email protected]</a> | 6
和 df2:
new_field
__________
1
7
4
两个数据帧具有相同的大小。 我怎样才能合并它们两个以获得类似的输出？
df3:
email | other_field | new_field
________________________________________________________________
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<a href="https://stackoverflow.com/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="0b6e666a6267394b6e666a626725686466" rel="noreferrer noopener nofollow">[email protected]</a> | 1 | 7
<a href="https://stackoverflow.com/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="aecbc3cfc7c29deecbc3cfc7c280cdc1c3" rel="noreferrer noopener nofollow">[email protected]</a> | 6 | 4
我尝试过这个:
df3 = pd.merge(df1, df2, left_index=True, right_index=True)
但是尽管 df1 和 df2 具有相同的大小，但 df3 的大小较小
最佳答案
在这种情况下，您可以concat:
In [70]:
pd.concat([df1,df2],axis=1)
Out[70]:
email other_field new_field
0 <a href="https://stackoverflow.com/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="56333b373f3a6716333b373f3a7835393b" rel="noreferrer noopener nofollow">[email protected]</a> 2 1
1 <a href="https://stackoverflow.com/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="ef8a828e8683ddaf8a828e8683c18c8082" rel="noreferrer noopener nofollow">[email protected]</a> 1 7
2 <a href="https://stackoverflow.com/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="b0d5ddd1d9dc83f0d5ddd1d9dc9ed3dfdd" rel="noreferrer noopener nofollow">[email protected]</a> 6 4
如果需要，您可以选择传递 ignore_index=True。
join 也可以:
In [71]:
df1.join(df2)
Out[71]:
email other_field new_field
0 <a href="https://stackoverflow.com/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="3e5b535f57520f7e5b535f5752105d5153" rel="noreferrer noopener nofollow">[email protected]</a> 2 1
1 <a href="https://stackoverflow.com/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="c8ada5a9a1a4fa88ada5a9a1a4e6aba7a5" rel="noreferrer noopener nofollow">[email protected]</a> 1 7
2 <a href="https://stackoverflow.com/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="c7a2aaa6aeabf487a2aaa6aeabe9a4a8aa" rel="noreferrer noopener nofollow">[email protected]</a> 6 4
此外，在索引匹配的情况下，直接赋值也可以:
In [72]:
df1['new_field'] = df2['new_field']
df1
Out[72]:
email other_field new_field
0 <a href="https://stackoverflow.com/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="650008040c0954250008040c094b060a08" rel="noreferrer noopener nofollow">[email protected]</a> 2 1
1 <a href="https://stackoverflow.com/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="d5b0b8b4bcb9e795b0b8b4bcb9fbb6bab8" rel="noreferrer noopener nofollow">[email protected]</a> 1 7
2 <a href="https://stackoverflow.com/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="dcb9b1bdb5b0ef9cb9b1bdb5b0f2bfb3b1" rel="noreferrer noopener nofollow">[email protected]</a> 6 4
关于Python，如何合并2个pandas DataFrame，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/26385843/