Pandas DataFrame Multiply Method

Introduction

In this lab, you will learn how to use the Pandas DataFrame multiply() method in Python. The multiply() method is used to get the element-wise multiplication of a DataFrame and another, and it returns a new DataFrame with the result of the multiplication.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

Skills Graph

Import the pandas library

First, you need to import the pandas library in order to use the DataFrame multiply() method. You can use the following code:

import pandas as pd

Create a DataFrame

Next, you need to create a DataFrame that you will use for the multiplication operations. You can create a DataFrame with the desired data using the pd.DataFrame() function. Here's an example:

df = pd.DataFrame({'a': [1, 2, 3], 'b': [4, 5, 6], 'c': [7, 8, 9]})

Multiply the DataFrame with a scalar

Now, you can use the multiply() method to multiply the DataFrame with a scalar value. This will multiply each element of the DataFrame by the scalar value. Here's an example:

result = df.multiply(2)
print(result)

Multiply the DataFrame with another DataFrame

You can also use the multiply() method to multiply the DataFrame with another DataFrame. This will perform element-wise multiplication between corresponding elements of the two DataFrames. Here's an example:

df2 = pd.DataFrame({'a': [2, 3, 4], 'b': [5, 6, 7], 'c': [8, 9, 10]})
result = df.multiply(df2)
print(result)

Handle missing values

If the two DataFrames have different shapes, the multiply() method will return a new DataFrame with NaN (missing) values in the places where the two DataFrames do not align. You can handle these missing values by using the fill_value parameter. Here's an example:

df2 = pd.DataFrame({'a': [2, 3, 4], 'b': [5, 6, 7]})
result = df.multiply(df2, fill_value=1)
print(result)

Summary

In this lab, you learned how to use the Pandas DataFrame multiply() method to perform element-wise multiplication between a DataFrame and another DataFrame or scalar value. You also learned how to handle missing values using the fill_value parameter. This method is useful for performing mathematical operations on DataFrames in a convenient way. Have fun exploring and experimenting with the multiply() method!