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.levshape attribute outputs a tuple containing the length of each level in the MultiIndex.
Syntax: MultiIndex.levshape
Example #1: Use MultiIndex.levshape attribute to find the length of each levels in the MultiIndex.
# importing pandas as pd import pandas as pd # Creating the array array =[[1, 2, 3], ['Sharon', 'Nick', 'Bailey']] # Print the array print(array) |
Output :
Now let’s create the MultiIndex using this array
# Creating the MultiIndex midx = pd.MultiIndex.from_arrays(array, names =('Number', 'Names')) # Print the MultiIndex print(midx) |
Output :
Now we will find the length of each levels in the MultiIndex.
# Print the length of each level in MultiIndex midx.levshape |
Output :
As we can see in the output, the length of each levels in the midx MultiIndex is (3, 3).
Example #2: Use MultiIndex.levshape attribute to find the length of each levels in the given MultiIndex.
# importing pandas as pd import pandas as pd # Creating the array array = [[1, 2, 3], ['Sharon', 'Nick', 'Bailey'], ['Doctor', 'Scientist', 'Physicist']] # Print the array print(array) |
Output :
Now let’s create the MultiIndex using this array
# Creating the MultiIndex midx = pd.MultiIndex.from_arrays(array, names = ('Ranking', 'Names', 'Profession')) # Print the MultiIndex print(midx) |
Output :
Now we will find the length of each levels in the MultiIndex.
# Print the length of each levels in MultiIndex midx.levshape |
Output :
As we can see in the output, the length of each level in the midx is 3.
