Pandas DataFrame set_axis() Method – Be on the Right Side of Change

Preparation

Before any data manipulation can occur, two (2) new libraries will require installation.

The Pandas library enables access to/from a DataFrame.
The NumPy library supports multi-dimensional arrays and matrices in addition to a collection of mathematical functions.

To install these libraries, navigate to an IDE terminal. At the command prompt ($), execute the code below. For the terminal used in this example, the command prompt is a dollar sign ($). Your terminal prompt may be different.

$ pip install pandas

Hit the <Enter> key on the keyboard to start the installation process.

$ pip install numpy

Hit the <Enter> key on the keyboard to start the installation process.

If the installations were successful, a message displays in the terminal indicating the same.

Feel free to view the PyCharm installation guide for the required libraries.

Add the following code to the top of each code snippet. This snippet will allow the code in this article to run error-free.

import pandas as pd
import numpy as np

DataFrame set_axis()

The set_axis() method assigns index(es) to the selected axis.

The syntax for this method is as follows:

DataFrame.set_axis(labels, axis=0, inplace=False)

Parameter	Description
`labels`	This parameter is a list or a list-like object containing index labels.
`axis`	If zero (0) or index is selected, apply to each column. Default 0. If one (1) apply to each row.
`inplace`	If `False`, a copy of the original DataFrame/Series is updated. This parameter is `None`, by default.

For these examples, the index saves to the selected axis.

In this example, we set the axis to the row index.

Code – Example 1

df = pd.DataFrame({'Micah': [123, 120, 144], 
                   'Paula': [129, 125, 90],
                   'Chloe': [101, 95,  124]})
print(df)
				   
result = df.set_axis(['Day-1', 'Day-2', 'Day-3'], axis='index')
print(result)

Line [1] creates a dictionary of lists and saves it to df.
Line [2] outputs the DataFrame (df) to the terminal.
Line [3] sets the new axis for the DataFrame and saves it to the result variable.
Line [4] outputs the result to the terminal.

Output

df

	Micah	Paula	Chloe
0	123	129	101
1	120	125	95
2	144	90	124

result

	Micah	Paula	Chloe
Day-1	123	129	101
Day-2	120	125	95
Day-3	144	90	124

In this example, we set the axis to the column index.

Code – Example 2

df = pd.DataFrame({'Micah': [123, 120, 144], 
                   'Paula': [129, 125, 90],
                   'Chloe': [101, 95,  124]})
print(df)
				   
result = df.set_axis(['Micah M', 'Paula D', 'Chloe J'], axis='columns')
print(result)

Line [1] creates a dictionary of lists and saves it to df.
Line [2] outputs the DataFrame (df) to the terminal.
Line [3] sets the new axis for the DataFrame and saves it to the result variable.
Line [4] outputs the result to the terminal.

Output

df

	Micah	Paula	Chloe
0	123	129	101
1	120	125	95
2	144	90	124

result

	Micah M	Paula D	Chloe J
0	123	129	101
1	120	125	95
2	144	90	124

More Pandas DataFrame Methods

Feel free to learn more about the previous and next pandas DataFrame methods (alphabetically) here:

👈 df.sample()

df.set_index() 👉

Also, check out the full cheat sheet overview of all Pandas DataFrame methods.