如何仅基于外部索引转置多级熊猫数据帧

Question

the below is my dataframe with two level indexing. I want 'only' the outer index to be transposed as columns. My desired output would be 2X2 dataframe instead of a 4X1 dataframe as is the case now. Can any of you please help?

        0
0    0  232

     1  3453

1    0  443

     1  3241

Answer 1

Given you have the multi index you can use unstack() on level 0.

import pandas as pd
import numpy as np

index = pd.MultiIndex.from_tuples([(0,0),(0,1),(1,0),(1,1)])
df = pd.DataFrame([[1],[2],[3],[4]] , index=index, columns=[0])

print df.unstack(level=[0])


   0   
   0  1
0  1  3
1  2  4

Answer 2

One way to do this would be to reset the index and then pivot the table indexing on the level_1 of the index, and using level_0 as the columns and 0 as the values. Example -

df.reset_index().pivot(index='level_1',columns='level_0',values=0)

Demo -

In [66]: index = pd.MultiIndex.from_tuples([(0,0),(0,1),(1,0),(1,1)])

In [67]: df = pd.DataFrame([[1],[2],[3],[4]] , index=index, columns=[0])

In [68]: df
Out[68]:
     0
0 0  1
  1  2
1 0  3
  1  4

In [69]: df.reset_index().pivot(index='level_1',columns='level_0',values=0)
Out[69]:
level_0  0  1
level_1
0        1  3
1        2  4

Later on, if you want you can set the .name attribute for the index as well as the columns to empty string or whatever you want , if you don't want the level_* there.