将索引上的数据帧与pandas合并

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:

我有两个数据帧,每个数据帧有两个索引列。我想合并它们。例如,第一个数据帧如下:

                   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

The second dataframe is the following:

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

and as result I would like to get the following:

结果我想得到以下内容:

                   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

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

我使用pd.merge和.join方法尝试了几个版本,但似乎没有任何工作。你有什么建议吗?

2 个解决方案

#1

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.

您应该能够使用join,它默认连接索引。根据您所需的结果,您必须使用outer作为连接类型。

>>> 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

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.

签名:_. join(其他,on = None,how ='left',lsuffix ='',rsuffix ='',sort = False)Docstring:在索引或键列上与其他DataFrame连接列。通过传递列表,有效地通过索引连接多个DataFrame对象。

#2

You can do this with merge:

您可以通过合并执行此操作:

df_merged = df1.merge(df2, how='outer', left_index=True, right_index=True)

The keyword argument how='outer' keeps all indices from both frames, filling in missing indices with NaN. The left_index and right_index keyword arguments have the merge be done on the indices. If you get all NaN in a column after doing a merge, another troubleshooting step is to verify that your indices have the same dtypes.

关键字参数how ='outer'保留两个帧的所有索引,用NaN填充缺失的索引。 left_index和right_index关键字参数在索引上进行合并。如果在合并后在列中获得所有NaN,则另一个故障排除步骤是验证索引是否具有相同的dtypes。

The merge code above produces the following output for me:

上面的合并代码为我生成以下输出:

                V1    V2
A 2012-01-01  12.0  15.0
  2012-02-01  14.0   NaN
  2012-03-01   NaN  21.0
B 2012-01-01  15.0  24.0
  2012-02-01   8.0   9.0
C 2012-01-01  17.0   NaN
  2012-02-01   9.0   NaN
D 2012-01-01   NaN   7.0
  2012-02-01   NaN  16.0

#1