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.reorder_levels() function is used to rearrange levels using input order. It may not drop or duplicate levels. The function take list as an input which contains the desired order of the levels of the MultiIndex.
Syntax: MultiIndex.reorder_levels(order)
Parameters :
order : list containing the order of levelsReturns : A new MultiIndex
Example #1: Use MultiIndex.reorder_levels() function to reorder the levels of the MultiIndex.
# importing pandas as pd import pandas as pd # Create the MultiIndex midx = pd.MultiIndex.from_arrays([['Networking', 'Cryptography', 'Anthropology', 'Science'], [88, 84, 98, 95]]) # Print the MultiIndex print(midx) |
Output :
Now let’s reorder the level of the MultiIndex.
# reorder the levels such that # 1st level appears before the 0th midx.reorder_levels([1, 0]) |
Output :
As we can see in the output, the function has returned a new MultiIndex having the levels set in the passed order.
Example #2: Use MultiIndex.reorder_levels() function to reorder the levels of the MultiIndex.
# importing pandas as pd import pandas as pd # Create the MultiIndex midx = pd.MultiIndex.from_arrays([['Beagle', 'Sephard', 'Labrador', 'Retriever'], [8, 4, 11, 3], ['A1', 'B1', 'A2', 'C1']]) # Print the MultiIndex print(midx) |
Output :
Now let’s reorder the levels of the MultiIndex.
# reorder the levels midx.reorder_levels([0, 2, 1]) |
Output :
As we can see in the output, the function has returned a new MultiIndex having the levels set in the passed order.
