To return MultiIndex with requested level removed using the level name, use the MultiIndex.droplevel() method and set the level (level name) to be removed as an argument.
At first, import the required libraries −
import pandas as pd
MultiIndex is a multi-level, or hierarchical, index object for pandas objects. Create arrays −
arrays = [[2, 4, 3, 1], ['Peter', 'Chris', 'Andy', 'Jacob']]
The "names" parameter sets the names for each of the index levels. The from_arrays() is used to create a MultiIndex −
multiIndex = pd.MultiIndex.from_arrays(arrays, names=('ranks', 'student'))
Drop a specific level from MultiIndex. The level to be dropped is set as the level name in parameter i.e.
# level name 'student' gets dropped −
print("\nMulti-index after dropping a level...\n",multiIndex.droplevel('student'))
Example
Following is the code −
import pandas as pd # MultiIndex is a multi-level, or hierarchical, index object for pandas objects # Create arrays arrays = [[2, 4, 3, 1], ['Peter', 'Chris', 'Andy', 'Jacob']] # The "names" parameter sets the names for each of the index levels # The from_arrays() is used to create a MultiIndex multiIndex = pd.MultiIndex.from_arrays(arrays, names=('ranks', 'student')) # display the MultiIndex print("The Multi-index...\n",multiIndex) # get the levels in MultiIndex print("\nThe levels in Multi-index...\n",multiIndex.levels) # Drop a specific level from MultiIndex # The level to be dropped is set as the level name in parameter i.e. # level name 'student' gets dropped print("\nMulti-index after dropping a level...\n",multiIndex.droplevel('student'))
Output
This will produce the following output −
The Multi-index... MultiIndex([(2, 'Peter'), (4, 'Chris'), (3, 'Andy'), (1, 'Jacob')], names=['ranks', 'student']) The levels in Multi-index... [[1, 2, 3, 4], ['Andy', 'Chris', 'Jacob', 'Peter']] Multi-index after dropping a level... Int64Index([2, 4, 3, 1], dtype='int64', name='ranks')