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Python – Drop a level from a multi-level column index in Pandas dataframe
To drop a level from a multi-level column index, use the columns.droplevel(). We have used the Multiindex.from_tuples() is used to create indexes column-wise.
At first, create indexes column-wise −
items = pd.MultiIndex.from_tuples([("Col 1", "Col 1", "Col 1"),("Col 2", "Col 2", "Col 2"),("Col 3", "Col 3", "Col 3")])Next, create a multiindex array and form a multiindex dataframe
arr = [np.array(['car', 'car', 'car','bike','bike', 'bike', 'truck', 'truck', 'truck']), np.array(['valueA', 'valueB', 'valueC','valueA', 'valueB', 'valueC','valueA', 'valueB', 'valueC'])] # forming multiindex dataframe dataFrame = pd.DataFrame(np.random.randn(9, 3), index=arr,columns=items)
Label the index −
dataFrame.index.names = ['level 0', 'level 1']
Drop a level at index 0 −
dataFrame.columns = dataFrame.columns.droplevel(0)
Example
Following is the code
import numpy as np
import pandas as pd
items = pd.MultiIndex.from_tuples([("Col 1", "Col 1", "Col 1"),("Col 2", "Col 2", "Col 2"),("Col 3", "Col 3", "Col 3")])
# multiindex array
arr = [np.array(['car', 'car', 'car','bike','bike', 'bike', 'truck', 'truck', 'truck']),
np.array(['valueA', 'valueB', 'valueC','valueA', 'valueB', 'valueC','valueA', 'valueB', 'valueC'])]
# forming multiindex dataframe
dataFrame = pd.DataFrame(np.random.randn(9, 3), index=arr,columns=items)
# labelling index
dataFrame.index.names = ['level 0', 'level 1']
print"DataFrame...\n",dataFrame
print"\nDropping a level...\n";
dataFrame.columns = dataFrame.columns.droplevel(0)
print"Updated DataFrame..\n",dataFrameOutput
This will produce the following output
DataFrame... Col 1 Col 2 Col 3 Col 1 Col 2 Col 3 Col 1 Col 2 Col 3 level 0 level 1 car valueA 1.691127 0.315145 -0.695925 valueB -2.077182 -2.027643 -0.523965 valueC 1.021402 -0.384421 0.640215 bike valueA -2.271217 0.197185 0.304847 valueB 0.119615 -0.520491 -0.746547 valueC 1.856888 -0.491540 -1.754604 truck valueA 0.829854 -0.204102 -1.130511 valueB 0.310692 0.119087 -0.244919 valueC -0.245934 -2.141639 -1.298278 Dropping a level... Updated DataFrame.. Col 1 Col 2 Col 3 Col 1 Col 2 Col 3 level 0 level 1 car valueA 1.691127 0.315145 -0.695925 valueB -2.077182 -2.027643 -0.523965 valueC 1.021402 -0.384421 0.640215 bike valueA -2.271217 0.197185 0.304847 valueB 0.119615 -0.520491 -0.746547 valueC 1.856888 -0.491540 -1.754604 truck valueA 0.829854 -0.204102 -1.130511 valueB 0.310692 0.119087 -0.244919 valueC -0.245934 -2.141639 -1.298278
Updated on: 13-Sep-2021
3K+ Views
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