Pandas Series: droplevel() function

Last update on September 15 2022 12:55:36 (UTC/GMT +8 hours)

Series-droplevel() function

The droplevel() function is used to return DataFrame with requested index / column level(s) removed.

Syntax:

Series.droplevel(self, level, axis=0)

Parameters:

Name	Description	Type/Default Value	Required / Optional
level	If a string is given, must be the name of a level If list-like, elements must be names or positional indexes of levels.	int, str, or list-like	Required
axis		{0 or ‘index’, 1 or ‘columns’} Default Value: 0	Required

Returns: DataFrame.droplevel()

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
df = pd.DataFrame([
    [2, 3, 4, 5],
    [6, 7, 8, 9],
    [10, 11, 12, 13]
]).set_index([0, 1]).rename_axis(['p', 'q'])
df.columns = pd.MultiIndex.from_tuples([
   ('r', 't'), ('s', 'v')
], names=['level_1', 'level_2'])

df

Output:

 level_1	r	s
 level_2	t	v
p	q		
2	3	4	5
6	7	8	9
10	11	12	13

Python-Pandas Code:

import numpy as np
import pandas as pd
df = pd.DataFrame([
    [2, 3, 4, 5],
    [6, 7, 8, 9],
    [10, 11, 12, 13]
]).set_index([0, 1]).rename_axis(['p', 'q'])
df.columns = pd.MultiIndex.from_tuples([
   ('r', 't'), ('s', 'v')
], names=['level_1', 'level_2'])

df.droplevel('p')

Output:

level_1	r	s
level_2	t	v
q		
3	4	5
7	8	9
11	12	13

Python-Pandas Code:

import numpy as np
import pandas as pd
df = pd.DataFrame([
    [2, 3, 4, 5],
    [6, 7, 8, 9],
    [10, 11, 12, 13]
]).set_index([0, 1]).rename_axis(['p', 'q'])
df.columns = pd.MultiIndex.from_tuples([
   ('r', 't'), ('s', 'v')
], names=['level_1', 'level_2'])

df.droplevel('level_2', axis=1)

Output:

 level_1	r	s
p	 q		
2	 3	    4	5
6	 7	    8	9
10 11	   12	13

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