Python | Pandas MultiIndex.set_labels()
Last Updated :
22 Sep, 2021
Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.
Pandas MultiIndex.set_labels() function set new labels on MultiIndex. Defaults to returning new index.
Syntax: MultiIndex.set_labels(labels, level=None, inplace=False, verify_integrity=True)
Parameters :
labels : new labels to apply
level : level(s) to set (None for all levels)
inplace : if True, mutates in place
verify_integrity : if True, checks that levels and labels are compatible
Returns: new index (of same type and class…etc)
Example #1: Use MultiIndex.set_labels() function to reset the labels of the MultiIndex.
Python3
import pandas as pd
midx = pd.MultiIndex.from_tuples([( 10 , 'Ten' ), ( 10 , 'Twenty' ),
( 20 , 'Ten' ), ( 20 , 'Twenty' )],
names = [ 'Num' , 'Char' ])
print (midx)
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Output :
Now let’s reset the labels of the MultiIndex.
Python3
midx.set_labels([[ 1 , 1 , 0 , 0 ], [ 0 , 1 , 1 , 0 ]])
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Output :
As we can see in the output, the labels of the MultiIndex has been reset.
Example #2: Use MultiIndex.set_labels() function to reset any specific label only in the MultiIndex.
Python3
import pandas as pd
midx = pd.MultiIndex.from_tuples([( 10 , 'Ten' ), ( 10 , 'Twenty' ),
( 20 , 'Ten' ), ( 20 , 'Twenty' )],
names = [ 'Num' , 'Char' ])
print (midx)
|
Output :
Now let’s reset the ‘Char’ label of the MultiIndex.
Python3
midx.set_labels([ 0 , 1 , 1 , 0 ], level = 'Char' )
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Output :
As we can see in the output, the ‘Char’ label of the MultiIndex has been reset to the desired value.
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