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Python | Pandas MultiIndex.to_hierarchical()
  • Last Updated : 24 Dec, 2018

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.to_hierarchical() function return a MultiIndex reshaped to conform to the shapes given by n_repeat and n_shuffle. It is useful to replicate and rearrange a MultiIndex for combination with another Index with n_repeat items.

Syntax: MultiIndex.to_hierarchical(n_repeat, n_shuffle=1)

Parameters :
n_repeat : Number of times to repeat the labels on self
n_shuffle : Controls the reordering of the labels. If the result is going to be an inner level in a MultiIndex, n_shuffle will need to be greater than one. The size of each label must divisible by n_shuffle

Returns : MultiIndex



Example #1: Use MultiIndex.to_hierarchical() function to repeat the labels 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 repeat the labels of the MultiIndex 2 times.




# repeat the labels in the MultiIndex 2 times.
midx.to_hierarchical(n_repeat = 2)

Output :

As we can see in the output, the labels in the returned MultiIndex is repeated 2 times.
 
Example #2: Use MultiIndex.to_hierarchical() function to repeat as well as reshuffle the labels 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 repeat and reshuffle the labels of the MultiIndex 2 times.




# resetting the labels the MultiIndex
midx.to_hierarchical(n_repeat = 2, n_shuffle = 2)

Output :

As we can see in the output, the labels are repeated as well as reshuffled twice in the returned MultiIndex.

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