Advanced pandas—Going Beyond the Basics/

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Further Reshaping Capabilities

Further Reshaping Capabilities

Discover further reshaping and manipulation capabilities of pandas.

We'll cover the following...

Overview

While we've covered the essential pandas functions for reshaping and manipulating data, there are several others that also deserve a mention. These methods may be used less often, but they are still highly useful for our data preparation efforts.

The transpose() method

Transposing a DataFrame means flipping (or rotating) the rows and columns so that the rows become columns and the columns become rows. This operation can be performed with the transpose() or T method.

Note: Both transpose() and T return the same result. While transpose() is more verbose and easy to understand, data practitioners often use T because of its brevity.

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# Display original DataFrame

print(df)



print('=' * 75)



# Display transposed DataFrame

df_transposed = df.T

print(df_transposed)

A powerful use of the transpose operation is to remove duplicate columns where the values are exactly the same. For example, let’s say we have the following fruits dataset with two columns (unit_price and unit_p) containing the same corresponding unit prices.

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# Display DataFrame with duplicate columns

print(df)

To keep only one of these duplicate columns, the simplest way ...