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Python Pandas CategoricalIndex - Map values using input correspondence like a dict
To Map values using input correspondence like a dict, use the CategoricalIndex.map() method in Pandas. At first, import the required libraries −
import pandas as pd
Set the categories for the categorical using the "categories" parameter. Treat the categorical as ordered using the "ordered" parameter −
catIndex = pd.CategoricalIndex(["P", "Q", "R", "S","P", "Q", "R", "S"], ordered=True, categories=["P", "Q", "R", "S"])
Display the CategoricalIndex −
print("CategoricalIndex...\n",catIndex)
Map categories −
print("\nCategoricalIndex after mapping...\n",catIndex.map({'P': 5, 'Q': 10, 'R': 15, 'S': 20}))Example
Following is the code −
import pandas as pd
# Set the categories for the categorical using the "categories" parameter
# Treat the categorical as ordered using the "ordered" parameter
catIndex = pd.CategoricalIndex(["P", "Q", "R", "S","P", "Q", "R", "S"], ordered=True, categories=["P", "Q", "R", "S"])
# Display the CategoricalIndex
print("CategoricalIndex...\n",catIndex)
# Get the categories
print("\nDisplayingCategories from CategoricalIndex...\n",catIndex.categories)
# Map categories
print("\nCategoricalIndex after mapping...\n",catIndex.map({'P': 5, 'Q': 10, 'R': 15, 'S': 20}))Output
This will produce the following output −
CategoricalIndex... CategoricalIndex(['P', 'Q', 'R', 'S', 'P', 'Q', 'R', 'S'], categories=['P', 'Q', 'R', 'S'], ordered=True, dtype='category') DisplayingCategories from CategoricalIndex... Index(['P', 'Q', 'R', 'S'], dtype='object') CategoricalIndex after mapping... CategoricalIndex([5, 10, 15, 20, 5, 10, 15, 20], categories=[5, 10, 15, 20], ordered=True, dtype='category')
Updated on: 18-Oct-2021
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