从索引交换一级到列级(Pandas Multiindex Dataframe) [英] Swap level-one from index with column level (Pandas Multiindex Dataframe)

问题描述

我有一个多索引的pandas.Dataframe，就像这样:

I have a multiindexed pandas.Dataframe which is something like this:

          BAZ    PAL
Foo  Bar          
124   1    A     B
      2    C     D
134   1    E     F
      2    G     H

我需要以适当的方式将索引的一级交换为列.我需要结束这样的事情:

I need to swap level-one from index with columns in appropriate way. I need to end up with something like this:

         124 134
Coo Bar
BAZ 1    A   E
    2    C   G
PAL 1    B   F
    2    D   H

推荐答案

您需要取消堆叠现有的索引级别Foo，堆叠所需的列'Coo'，然后重新排列索引级别.交换索引级别后，您可能希望对其进行排序.最后，您可能要删除所有值的列名(val).

You need to unstack your existing index level Foo, stack your desired column 'Coo', and then rearrange the index levels. After swapping your index levels, you probably want to sort it. As a final touch, you may want to drop the column name of all the values (val).

df = (pd.DataFrame({'Foo': [124, 124, 134, 134] * 2, 
                    'Bar': [1, 2, 1, 2] * 2, 
                    'Coo': ['BAZ'] * 4 + ['PAL'] * 4, 
                    'val': list('ACEGBDFH')})
      .set_index(['Foo', 'Bar', 'Coo'])
      .unstack('Coo'))

>>> df
        val    
Coo     BAZ PAL
Foo Bar        
124 1     A   B
    2     C   D
134 1     E   F
    2     G   H

df = df.unstack('Foo').stack('Coo')
df.index = df.index.swaplevel(0, 1)

>>> df
        val    
Foo     124 134
Coo Bar        
BAZ 1     A   E
PAL 1     B   F
BAZ 2     C   G
PAL 2     D   H

df.sort_index(inplace=True)

>>> df
        val    
Foo     124 134
Coo Bar        
BAZ 1     A   E
    2     C   G
PAL 1     B   F
    2     D   H

df.columns = df.columns.droplevel()

>>> df
Foo     124 134
Coo Bar        
BAZ 1     A   E
    2     C   G
PAL 1     B   F
    2     D   H

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