Pandas DataFrame Div Method

Introduction

This guide will walk you through the usage of the div() method in the Pandas library for Python. The div() method is used to perform element-wise division between a DataFrame and another scalar, sequence, Series, or DataFrame. It returns a new DataFrame with the result of the arithmetic operation.

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Import the necessary libraries and create a DataFrame

import pandas as pd

df1 = pd.DataFrame({'a': [2, 5, 6],
                    'b': [8, 10, 12],
                    'c': [14, 16, 18]})

Here, we import the Pandas library and create a DataFrame df1 with three columns 'a', 'b', and 'c'.

Divide the DataFrame by a scalar value

df_divided = df1.div(3)
print(df_divided)

In this step, we use the div() method to divide each element of the DataFrame df1 by the scalar value 3. The resulting DataFrame df_divided is then printed.

Divide the DataFrame by another DataFrame

df2 = pd.DataFrame({'a': [2, 2, 2],
                    'b': [2, 2, 2],
                    'c': [2, 2, 2]})

df_divided = df1.div(df2)
print(df_divided)

Here, we create another DataFrame df2 with the same shape as df1. We then use the div() method to divide each corresponding element of df1 by the corresponding element in df2. The resulting DataFrame df_divided is then printed.

Divide the DataFrame by another DataFrame and fill missing values

df2 = pd.DataFrame({'a': [2, 2, 2],
                    'b': [2, 2, 2]})

df_divided = df1.div(df2, fill_value=1)
print(df_divided)

In this step, we create a DataFrame df2 with two columns, missing the 'c' column. We then use the div() method to divide each corresponding element of df1 by the corresponding element in df2. We also specify fill_value=1 to fill any missing values in df2 with the value 1 before performing the division. The resulting DataFrame df_divided is then printed.

Summary

In this guide, we learned how to use the div() method in the Pandas library to perform element-wise division on a DataFrame. We explored dividing a DataFrame by a scalar value, another DataFrame, and filling missing values before performing the division. This method is useful for performing arithmetic operations in a vectorized way on DataFrame columns.