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_product() function make a MultiIndex from the cartesian product of multiple iterables.
Syntax: MultiIndex.from_product(iterables, sortorder=None, names=None)
Parameters :
iterables : Each iterable has unique labels for each level of the index.
sortorder : Level of sortedness (must be lexicographically sorted by that level).
names : Names for the levels in the index.Returns: index : MultiIndex
Example #1: Use MultiIndex.from_product() function to construct a MultiIndex from the cartesian product of multiple iterables.
# importing pandas as pd import pandas as pd # Create the first iterable Price =[20, 35, 60, 85] # Create the second iterable Name =['Vanilla', 'Strawberry'] # Print the first iterable print(Price) # Print the second iterable print("\n", Name) |
Output :
Now let’s create the MultiIndex using the above two iterables.
# Creating the MultiIndex midx = pd.MultiIndex.from_product([Name, Price], names =['Name', 'Price']) # Print the MultiIndex print(midx) |
Output :
As we can see in the output, the function has created a MultiIndex object using the cartesian product of these two iterables.
Example #2: Use MultiIndex.from_product() function to construct a MultiIndex from the cartesian product of multiple iterables.
# importing pandas as pd import pandas as pd # Create the first iterable Snake =['Viper', 'Cobra'] # Create the second iterable Variety =['Brown', 'Yellow', 'Black'] # Print the first iterable print(Snake) # Print the second iterable print("\n", Variety) |
Output :
Now let’s create the MultiIndex using the above two iterables.
# Creating the MultiIndex midx = pd.MultiIndex.from_product([Snake, Variety], names =['Snake', 'Variety']) # Print the MultiIndex print(midx) |
Output :
The function has created a MultiIndex using the two iterables.
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