用 pandas 合并索引上的数据框 [英] Merging dataframes on index with pandas

问题描述

我有两个数据框，每个数据框都有两个索引列.我想将它们合并.例如，第一个数据帧如下:

I have two dataframes and each one has two index columns. I would like to merge them. For example, the first dataframe is the following:

                   V1

A      1/1/2012    12
       2/1/2012    14
B      1/1/2012    15
       2/1/2012    8
C      1/1/2012    17
       2/1/2012    9

第二个数据帧如下:

                   V2

A      1/1/2012    15
       3/1/2012    21             
B      1/1/2012    24
       2/1/2012    9
D      1/1/2012    7
       2/1/2012    16

因此，我想得到以下信息:

and as result I would like to get the following:

                   V1   V2

A      1/1/2012    12   15
       2/1/2012    14   N/A
       3/1/2012    N/A  21           
B      1/1/2012    15   24
       2/1/2012    8    9
C      1/1/2012    7    N/A
       2/1/2012    16   N/A
D      1/1/2012    N/A  7
       2/1/2012    N/A  16

我已经尝试过使用pd.merge和.join方法的一些版本，但是似乎没有任何效果.你有什么建议吗?

I have tried a few versions using the pd.merge and .join methods, but nothing seems to work. Do you have any suggestions?

推荐答案

您应该能够使用join，默认情况下，它会连接到索引.给定您想要的结果，您必须使用outer作为联接类型.

You should be able to use join, which joins on the index as default. Given your desired result, you must use outer as the join type.

>>> df1.join(df2, how='outer')
            V1  V2
A 1/1/2012  12  15
  2/1/2012  14 NaN
  3/1/2012 NaN  21
B 1/1/2012  15  24
  2/1/2012   8   9
C 1/1/2012  17 NaN
  2/1/2012   9 NaN
D 1/1/2012 NaN   7
  2/1/2012 NaN  16

签名:_.join(其他，on =无，how ='左'，lsuffix =''，rsuffix =''，sort = False) Docstring: 在索引或键上将列与其他DataFrame连接起来 柱子.通过索引一次有效地连接多个DataFrame对象 传递列表.

Signature: _.join(other, on=None, how='left', lsuffix='', rsuffix='', sort=False) Docstring: Join columns with other DataFrame either on index or on a key column. Efficiently Join multiple DataFrame objects by index at once by passing a list.

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