Pandas DataFrame swapaxes() 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 swapaxes()

The swapaxes() method swap axis 1 with axis 2. This parameter returns the called DataFrame/Series.

The syntax for this method is as follows:

DataFrame.swapaxes(axis1, axis2, copy=True)

`axis1`, `axis2`	If zero (0) or index is selected, apply to each column. Default is 0 (column). If zero (1) or columns, apply to each row.
`copy`	If `True`, a copy of the original DataFrame/Series creates. `True`, by default. If `False`, the updates occur on the original DataFrame/Series.

We have six (6) book titles and associated details that save to a DataFrame. The np.random.randint() method retrieves the number of books sold.

index = [('Mystery', 'Sharp Objects', 1982), ('Mystery', 'A Murder', 1973), ('Mystery', 'Wanted', 1990),
         ('Fiction', 'Thirst', 1992), ('Fiction', 'The Time Keeper', 2014), ('Fiction', 'Eligible', 1997)]
m_index = pd.MultiIndex.from_tuples(index)
num_sold = np.random.randint(5,250,size=6)

df = pd.DataFrame({'Sold': num_sold}, index=m_index)
print(df)

result = df.swapaxes(1, 0)
print(result)

Line [1] creates a List of tuples. Each tuple contains three (3) values. The output saves to the index.
Line [2] creates a MultiIndex from the list of tuples created on line [1] and saves it to m_index.
Line [3] generates five (5) random integers between the specified range and saves them to num_sold.
Line [4] creates a DataFrame from the variables created on lines [1-3] and saves to df.
Line [5] outputs the DataFrame to the terminal.
Line [6] swaps out the axes as specified. The output saves to result.
Line [7] outputs the result to the terminal.

Output

df

			Sold
Mystery	Sharp Objects	1982	76
	A Murder	1973	114
	Wanted	1990	244
Fiction	Thirst	1992	153
	The Time Keeper	2014	207
	Eligible	1997	175

result

	Mystery	Fiction
	Sharp Objects	A Murder	Wanted	Thirst	The Time Keeper	Eligible
	1982	1973	1990	1992	2014	1997
Sold	76	114	244	153	207	175

More Pandas DataFrame Methods

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

👈 df.stack()

df.swap_level() 👉

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