How to Efficiently Update a DataFrame with Another DataFrame in Python Pandas

Discover how to effectively update a DataFrame in Python's Pandas library by combining it with another DataFrame. Learn step-by-step guidelines to handle new columns, rows, and data.
---
This video is based on the question https://stackoverflow.com/q/68912866/ asked by the user 'Help needed' ( https://stackoverflow.com/u/13131680/ ) and on the answer https://stackoverflow.com/a/68912989/ provided by the user 'Scott Boston' ( https://stackoverflow.com/u/6361531/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Updating dataframe with new dataframe, overwritting

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/licensing
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/by-sa/4.0/ ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/by-sa/4.0/ ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Efficiently Update a DataFrame with Another DataFrame in Python Pandas

In the world of data manipulation with Python, Pandas is a powerhouse library that allows users to handle data structures like DataFrames seamlessly. However, tasks such as updating one DataFrame with another can sometimes be confusing, especially for beginners. If you've found yourself grappling with how to update a DataFrame (df1) using another DataFrame (df2), you're in the right place! This guide will guide you through the process step by step, making it clear and simple.

The Problem

You're looking to update an existing DataFrame (df1) with data from another DataFrame (df2). The challenge arises because df2 may contain new columns, new rows, or updated/blank entries that need to be reflected in the resulting DataFrame (df). Here's the situation in detail:

Existing DataFrame (df1):

[[See Video to Reveal this Text or Code Snippet]]

New DataFrame (df2):

[[See Video to Reveal this Text or Code Snippet]]

The desired outcome is to obtain a DataFrame that reflects the updates correctly:

[[See Video to Reveal this Text or Code Snippet]]

The Solution

To achieve the desired result, we will follow a systematic approach using the Pandas library. Here’s a breakdown of the steps you need to follow:

Step 1: Set Up Your DataFrames

First, we need to import the necessary library and create the two DataFrames (df1 and df2).

[[See Video to Reveal this Text or Code Snippet]]

Step 2: Prepare the DataFrames

Next, to facilitate the update process, we'll set the index of both DataFrames to the ID column and replace any blank data with NaN for better handling.

[[See Video to Reveal this Text or Code Snippet]]

Step 3: Combine the Two DataFrames

We will now utilize the combine_first() method to update df1 with values from df2. This method fills NaN values in df1 with the corresponding non-null values from df2.

[[See Video to Reveal this Text or Code Snippet]]

Step 4: Display the Result

Finally, print the updated DataFrame to see the results:

[[See Video to Reveal this Text or Code Snippet]]

Output:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

You've successfully updated a DataFrame (df1) using another DataFrame (df2) in Python's Pandas library! This approach is efficient and allows you to seamlessly manage updates, whether it involves new columns, rows, or data discrepancies. Remember, mastering data manipulation in Pandas opens up a world of possibilities in data analysis and management.

In summary, use the following key steps to update your DataFrames effectively:

Set proper indices and handle blanks.

Utilize the combine_first() method to merge DataFrames.

Enjoy your new, updated DataFrame!

With this knowledge, you're ready to tackle more complex data manipulation tasks in your projects. Happy coding!

Видео How to Efficiently Update a DataFrame with Another DataFrame in Python Pandas канала vlogize