Скачать или смотреть How to Fix Appending Issues in Pandas DataFrames: Solve the Empty DataFrame Problem

Are you struggling with appending data into a DataFrame in Pandas and ending up with an empty DataFrame? Learn how to resolve this issue effectively and save your data for future use!
---
This video is based on the question https://stackoverflow.com/q/72125518/ asked by the user 'FredyJames21' ( https://stackoverflow.com/u/19041954/ ) and on the answer https://stackoverflow.com/a/72125874/ provided by the user 'micro5' ( https://stackoverflow.com/u/17839894/ ) 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: I am trying to append two dataframes but its giving an empty dataframes

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

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
How to Fix Appending Issues in Pandas DataFrames: Solve the Empty DataFrame Problem

When working with data in Python, particularly using the Pandas library, you might encounter a common problem: appending data to a DataFrame and ending up with an empty DataFrame. This issue can be frustrating, especially when you're trying to combine datasets or store results for future analysis.

The Problem at Hand

You may have written code that looks something like this, where you're trying to append descriptive statistics (obtained using describe()) to an existing DataFrame:

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

However, when you run the code, you notice that p_deddf still remains empty, which can leave you scratching your head. Here's the hypothesis: the method append() does not modify the DataFrame in place; instead, it returns a new DataFrame with the added rows.

Example Code

Here's the snippet of code that illustrates this issue clearly:

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

Why Is This Happening?

Understanding the append Method

The confusion arises from how the append() function behaves:

Doesn't Modify In-Place: By default, the append method does not change the DataFrame you are calling it on. Instead, it generates a new DataFrame containing the rows from the original one, along with the appended rows, which you need to assign to a variable.

Returns a New DataFrame: Since p_deddf.append(p_des) generates a new DataFrame, you need to save this result back to a variable to store the appended data.

How to Fix It

To effectively append your descriptive statistics to the DataFrame and avoid ending up with empty DataFrames, simply assign the result of the append() method back to your DataFrame. Here’s how you can do it:

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

Revised Code Example

Putting everything into context, your updated code should look like this:

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

Conclusion

Appending data to DataFrames in Pandas can cause confusion if you don't understand the behavior of the append() method. Remember that it doesn't modify the original DataFrame in place – it creates and returns a new one. By ensuring you assign the results correctly, you'll be able to combine your data successfully and avoid dealing with empty DataFrames.

Next Steps

Now that you know how to properly append data to your DataFrames, you can continue working on various data files, appending necessary statistics, and saving them into Excel files for your future analyses. Happy coding!