Pandas Series: set_axis() function

Series-set_axis() function

The set_axis() function is used to assign desired index to given axis.
Indexes for column or row labels can be changed by assigning a list-like or Index.
Changed in version 0.21.0: The signature is now labels and axis, consistent with the rest of pandas API. Previously, the axis and labels arguments were respectively the first and second positional arguments.

Syntax:

Series.set_axis(self, labels, axis=0, inplace=None)

Parameters:

Returns: renamed - %(klass)s or None An object of same type as caller if inplace=False, None otherwise.

Example - Series:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series([2, 3, 4])
s

Output:

0    2
1    3
2    4
dtype: int64

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series([2, 3, 4])
s.set_axis(['p', 'q', 'r'], axis=0, inplace=False)

Output:

p    2
q    3
r    4
dtype: int64

Example - The original object is not modified:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series([2, 3, 4])
s

Output:

0    2
1    3
2    4
dtype: int64

DataFrame

Example - Change the row labels:

Python-Pandas Code:

import numpy as np
import pandas as pd
df = pd.DataFrame({"X": [2, 3, 4], "Y": [5, 6, 7]})
df.set_axis(['p', 'q', 'r'], axis='index', inplace=False)

Output:

  X	  Y
p	 2	  5
q	 3	  6
r	 4	  7

Example - Change the column labels:

Python-Pandas Code:

import numpy as np
import pandas as pd
df = pd.DataFrame({"X": [2, 3, 4], "Y": [5, 6, 7]})
df.set_axis(['I', 'II'], axis='columns', inplace=False)

Output:

  I	 II
0	2	5
1	3	6
2	4	7

Example - Now, update the labels inplace:

Python-Pandas Code:

import numpy as np
import pandas as pd
df = pd.DataFrame({"X": [2, 3, 4], "Y": [5, 6, 7]})
df.set_axis(['i', 'ii'], axis='columns', inplace=True)
df

Output:

   i  ii
0  2   5
1  3   6
2  4   7

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