Pandas Add Keys While Concatenating Dataframes At Column Level

As per Pandas 0.19.2 documentation, I can provide keys argument to create a resulting multi-index DataFrame. An example (from pandas documents ) is : result = pd.concat(frames, key

Solution 1:

This is supported by keys parameter of pd.concat when specifying axis=1:

df1 = pd.DataFrame(np.random.random((4, 4)), columns=list('ABCD'))
df2 = pd.DataFrame(np.random.random((4, 3)), columns=list('BDF'), index=[2, 3, 6, 7])

df = pd.concat([df1, df2], keys=['X', 'Y'], axis=1)

The resulting output:

          X                                       Y                    
          A         B         C         D         B         D         F00.6544060.4959060.6011000.309276NaNNaNNaN10.0205270.8140650.9075900.924307NaNNaNNaN20.2395980.0892700.0335850.8708290.8820280.6266500.62285630.9839420.1035730.3701210.0704420.9864870.8482030.0898746NaNNaNNaNNaN0.6645070.3197890.8681337NaNNaNNaNNaN0.3411450.3084690.884074