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.from_arrays() function is used to convert arrays into MultiIndex. It is one of the several ways in which we construct a MultiIndex.
Syntax: MultiIndex.from_arrays(arrays, sortorder=None, names=None)
Parameters :
arrays : Each array-like gives one level’s value for each data point. len(arrays) is the number of levels
sortorder : Level of sortedness (must be lexicographically sorted by that level)Returns: index : MultiIndex
Example #1: Use MultiIndex.from_arrays() function to construct a MultiIndex from arrays.
# 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 :
As we can see in the output, the function has created a MultiIndex object using the arrays.
Example #2: Use MultiIndex.from_arrays() function to construct a MultiIndex from arrays.
# 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 :
As we can see in the output, the function has created a MultiIndex using the passed arrays.
