How To Apply Hierarchy Or Multi-index To Pandas Columns

I have seen lots of examples on how to arrange dataframe row indexes hierarchically, but I am trying to do the same for columns and am not understanding the syntax: Given: df = pd.

Solution 1:

You can define MultiIndices using the from_arrays or from_tuples or from_product classmethods. Here is an example using from_arrays:

arrays = [[1, 2]*3, ['A', 'B', 'C']*2]
columns = pd.MultiIndex.from_arrays(arrays, names=['foo', 'bar'])

df = pd.DataFrame(np.random.randn(2,6),
                  columns=columns,
                  index= pd.date_range('20000103',periods=2))

yields

In[81]: dfOut[81]: 
foo121212barABCABC2000-01-031.277234-0.8995470.040337-0.878752-0.5243360.9224402000-01-04-1.7067970.4503791.510868-2.539827-1.909996-0.003851

Defining a MultiIndex for the index is done in exactly the same way as for columns.