Pandas DataFrame Combine_first Method

Introduction

In this lab, we will learn how to use the combine_first() method in the Pandas DataFrame. This method allows us to combine two DataFrame objects by filling null values in one DataFrame with non-null values from another DataFrame. It can be useful when we have missing data in one DataFrame and want to fill it with data from another DataFrame.

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 necessary libraries

import pandas as pd

Create two DataFrames with missing values

df1 = pd.DataFrame({'A': [None, 0], 'B': [None, 4]})
df2 = pd.DataFrame({'A': [1, 1], 'B': [3, 3]})

Combine the DataFrames using the combine_first() method

combined_df = df1.combine_first(df2)

Print the combined DataFrame

print(combined_df)

Add a new row to one of the DataFrames

df2.loc[2] = [2, 2]

Combine the DataFrames again

combined_df = df1.combine_first(df2)

Print the combined DataFrame again

print(combined_df)

Combine DataFrames with None values

df1 = pd.DataFrame({'A': [None, 0], 'B': [None, 4]})
df2 = pd.DataFrame({'A': [None, 1], 'B': [None, 3]})
combined_df = df1.combine_first(df2)
print(combined_df)

Combine DataFrames with different indexes

df1 = pd.DataFrame({'A': [None, 0], 'B': [4, None]})
df2 = pd.DataFrame({'B': [3, 3], 'C': [1, 1]}, index=[1, 2])
combined_df = df1.combine_first(df2)
print(combined_df)

Summary

In this lab, we learned how to use the combine_first() method in the Pandas DataFrame. We saw that this method allows us to fill null values in one DataFrame with non-null values from another DataFrame. We also saw how it can handle cases where both DataFrames have null values or when the DataFrames have different indexes. The combine_first() method is a useful tool for combining and filling missing data in DataFrames.