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.
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 repeat the labels of the MultiIndex 2 times.
midx.to_hierarchical(n_repeat = 2 )
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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.
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 repeat and reshuffle the labels of the MultiIndex 2 times.
midx.to_hierarchical(n_repeat = 2 , n_shuffle = 2 )
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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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