将多索引列追加到DataFrame的索引

Question

I have generated a initial dataframe called df and then an adjusted dataframe called df_new.

I wish to get from df to df_new using a set_index() operation. My problem is how to negotiate the hierarchical index on columns

import pandas as pd
import numpy as np

df = pd.DataFrame(np.ones((5,5)))
col_idx = pd.MultiIndex.from_tuples([('X','a'),('X','b'),('Y','c'),('Y','d'),('Y','e')])
row_idx = ['a1','a2','a3','a4','a5']
df.columns = col_idx
df.index = row_idx
idx = pd.IndexSlice
df.loc[:,idx['Y','d']] = 99
print df.head()


    X     Y       
    a  b  c   d  e
a1  1  1  1  99  1
a2  1  1  1  99  1
a3  1  1  1  99  1
a4  1  1  1  99  1
a5  1  1  1  99  1

#------------------------------------------------------------------------------------------


df_new = pd.DataFrame(np.ones((5,4)))
col_idx = pd.MultiIndex.from_tuples([('X','a'),('X','b'),('Y','c'),('Y','e')])
row_idx = pd.MultiIndex.from_tuples([('a1',99),('a2',99),('a3',99),('a4',99),('a5',99)])

df_new.columns = col_idx
df_new.index = row_idx
print df_new.head()

# this is what df_new should look like.
# ('Y','d') got appended to the row index.

       X     Y   
       a  b  c  e
a1 99  1  1  1  1
a2 99  1  1  1  1
a3 99  1  1  1  1
a4 99  1  1  1  1
a5 99  1  1  1  1

Answer 1

You can use a tuple notation to indicate a column of the multi-indexed columns (and you need append=True to not replace the existing index):

In [34]: df.set_index(('Y', 'd'), append=True)
Out[34]:
           X     Y
           a  b  c  e
   (Y, d)
a1 99      1  1  1  1
a2 99      1  1  1  1
a3 99      1  1  1  1
a4 99      1  1  1  1
a5 99      1  1  1  1

If you want to remove the index name, you can do:

In [42]: df2 = df.set_index(('Y', 'd'), append=True)

In [43]: df2.index.names = [None, None]

In [44]: df2
Out[44]:
       X     Y
       a  b  c  e
a1 99  1  1  1  1
a2 99  1  1  1  1
a3 99  1  1  1  1
a4 99  1  1  1  1
a5 99  1  1  1  1

When you want to add multiple columns to the index, you have to use a list of columns names (in this case tuples):

df.set_index([('Y', 'd'), ('Y', 'e')], append=True)

Answer 2

The DataFrame.set_index method takes an append keyword argument, so you can simply do like this:

df_new = df.set_index(("Y", "d"), append=True)

If you want to add multiple columns, just provide them as a list:

df_new = df.set_index([("Y", "d"), ("Y", "e")], append=True)