Reputation: 3009
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
Upvotes: 0
Views: 118
Reputation: 139142
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)
Upvotes: 1
Reputation: 32204
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)
Upvotes: 1