Pandas Series: xs() function

Last update on September 15 2022 12:58:10 (UTC/GMT +8 hours)

Cross-section from the Series/DataFrame in Pandas

The xs() function is used to get cross-section from the Series/DataFrame.

This method takes a key argument to select data at a particular level of a MultiIndex.

Syntax:

Series.xs(self, key, axis=0, level=None, drop_level=True)

Parameters:

Name	Description	Type/Default Value	Required / Optional
key	Label contained in the index, or partially in a MultiIndex.	label or tuple of label	Required
axis	Axis to retrieve cross-section on.	{0 or ‘index’, 1 or ‘columns’} Default Value: 0	Required
level	In case of a key partially contained in a MultiIndex, indicate which levels are used. Levels can be referred by label or position.	object Default Value: defaults to first n levels (n=1 or len(key))	Required
drop_level	If False, returns object with same levels as self.	bool Default Value: True	Required

Returns: Series or DataFrame
Cross-section from the original Series or DataFrame corresponding to the selected index levels.

Notes:

xs can not be used to set values.

MultiIndex Slicers is a generic way to get/set values on any level or levels.

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
d = {'num_legs': [4, 4, 4, 2, 2],
     'num_wings': [0, 0, 0, 2, 2],
     'class': ['mammal', 'mammal', 'mammal', 'bird', 'bird'],
     'animal': ['tiger', 'lion', 'fox', 'eagle', 'penguin'],
     'locomotion': ['walks', 'walks', 'walks', 'flies', 'walks']}
df = pd.DataFrame(data=d)
df = df.set_index(['class', 'animal', 'locomotion'])
df

Output:

                                num_legs  num_wings
class  animal  locomotion                     
mammal tiger   walks              4          0
       lion    walks              4          0
       fox     walks              4          0
bird   eagle   flies              2          2
       penguin walks              2          2

Example - Get values at specified index:

Python-Pandas Code:

import numpy as np
import pandas as pd
d = {'num_legs': [4, 4, 4, 2, 2],
     'num_wings': [0, 0, 0, 2, 2],
     'class': ['mammal', 'mammal', 'mammal', 'bird', 'bird'],
     'animal': ['tiger', 'lion', 'fox', 'eagle', 'penguin'],
     'locomotion': ['walks', 'walks', 'walks', 'flies', 'walks']}
df = pd.DataFrame(data=d)
df = df.set_index(['class', 'animal', 'locomotion'])
df.xs('mammal')

Output:

                                num_legs	num_wings
animal	locomotion		
tiger	      walks	                        4	0
lion	      walks	                        4	0
fox	      walks	                        4	0

Example - Get values at several indexes:

Python-Pandas Code:

import numpy as np
import pandas as pd
d = {'num_legs': [4, 4, 4, 2, 2],
     'num_wings': [0, 0, 0, 2, 2],
     'class': ['mammal', 'mammal', 'mammal', 'bird', 'bird'],
     'animal': ['tiger', 'lion', 'fox', 'eagle', 'penguin'],
     'locomotion': ['walks', 'walks', 'walks', 'flies', 'walks']}
df = pd.DataFrame(data=d)
df = df.set_index(['class', 'animal', 'locomotion'])
df.xs(('mammal', 'fox'))

Output:

                   num_legs	num_wings
locomotion		
walks	                   4	0

Example - Get values at specified index and level:

Python-Pandas Code:

import numpy as np
import pandas as pd
d = {'num_legs': [4, 4, 4, 2, 2],
     'num_wings': [0, 0, 0, 2, 2],
     'class': ['mammal', 'mammal', 'mammal', 'bird', 'bird'],
     'animal': ['tiger', 'lion', 'fox', 'eagle', 'penguin'],
     'locomotion': ['walks', 'walks', 'walks', 'flies', 'walks']}
df = pd.DataFrame(data=d)
df = df.set_index(['class', 'animal', 'locomotion'])
df.xs('lion', level=1)

Output:

                   num_legs	num_wings
class	locomotion		
mammal	walks	       4	0

Example - Get values at several indexes and levels:

Python-Pandas Code:

import numpy as np
import pandas as pd
d = {'num_legs': [4, 4, 4, 2, 2],
     'num_wings': [0, 0, 0, 2, 2],
     'class': ['mammal', 'mammal', 'mammal', 'bird', 'bird'],
     'animal': ['tiger', 'lion', 'fox', 'eagle', 'penguin'],
     'locomotion': ['walks', 'walks', 'walks', 'flies', 'walks']}
df = pd.DataFrame(data=d)
df = df.set_index(['class', 'animal', 'locomotion'])
df.xs(('bird', 'walks'),
      level=[0, 'locomotion'])

Output:

                   num_legs  num_wings
animal                      
penguin               2          2

Example - Get values at specified column and axis:

Python-Pandas Code:

import numpy as np
import pandas as pd
d = {'num_legs': [4, 4, 4, 2, 2],
     'num_wings': [0, 0, 0, 2, 2],
     'class': ['mammal', 'mammal', 'mammal', 'bird', 'bird'],
     'animal': ['tiger', 'lion', 'fox', 'eagle', 'penguin'],
     'locomotion': ['walks', 'walks', 'walks', 'flies', 'walks']}
df = pd.DataFrame(data=d)
df = df.set_index(['class', 'animal', 'locomotion'])
df.xs('num_wings', axis=1)

Output:

class   animal   locomotion
mammal  tiger    walks         0
        lion     walks         0
        fox      walks         0
bird    eagle    flies         2
        penguin  walks         2
Name: num_wings, dtype: int64

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