To return MultiIndex with requested level removed, use the MultiIndex.droplevel() method in Pandas. Set the level 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. The level is 1 i.e. level 1 gets dropped” −
print("\nMulti-index after dropping a level...\n",multiIndex.droplevel(1))
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
# The level is 1 i.e. level 1 gets dropped
print("\nMulti-index after dropping a level...\n",multiIndex.droplevel(1))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')