Python | Pandas MultiIndex.set_labels()

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.
 

# importing pandas as pd
import pandas as pd

# Create the MultiIndex
midx = pd.MultiIndex.from_tuples([(10, 'Ten'), (10, 'Twenty'),
                                  (20, 'Ten'), (20, 'Twenty')],
                                       names =['Num', 'Char'])

# Print the MultiIndex
print(midx)

Output : 
 

Now let's reset the labels of the MultiIndex. 
 

# resetting the labels the MultiIndex
midx.set_labels([[1, 1, 0, 0], [0, 1, 1, 0]])

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.
 

# importing pandas as pd
import pandas as pd

# Create the MultiIndex
midx = pd.MultiIndex.from_tuples([(10, 'Ten'), (10, 'Twenty'), 
                                  (20, 'Ten'), (20, 'Twenty')],
                                        names =['Num', 'Char'])

# Print the MultiIndex
print(midx)

Output : 
 

Now let's reset the 'Char' label of the MultiIndex. 
 

# resetting the labels the MultiIndex
midx.set_labels([0, 1, 1, 0], level ='Char')

Output : 
 

As we can see in the output, the 'Char' label of the MultiIndex has been reset to the desired value.