Скачать или смотреть How to Avoid ZeroDivisionError When Dividing Two DataFrame Columns in Python's Pandas

Learn how to effectively divide two columns in a Pandas DataFrame while avoiding errors like `ZeroDivisionError` and `KeyError`. This guide provides a step-by-step solution.
---
This video is based on the question https://stackoverflow.com/q/73322724/ asked by the user 'MKJ' ( https://stackoverflow.com/u/19556055/ ) and on the answer https://stackoverflow.com/a/73323264/ provided by the user 'sierra_papa' ( https://stackoverflow.com/u/13227420/ ) 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: Dividing two dataframe columns by each other, avoiding ZeroDivisionError

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.
---
Understanding the Division Issue in Pandas DataFrames

When working with a Pandas DataFrame, you may encounter a situation where you need to divide the values of one column by another. A common scenario arises when you want to calculate ratios or percentages, such as dividing "Aerial duels won" by "Aerial duels" to find the win percentage. However, this task can lead to errors, specifically ZeroDivisionError, if any of the denominator values are zero.

In this guide, we will explore how to handle this problem effectively by dividing two DataFrame columns while avoiding errors.

The Problem at Hand

Scenario

You have a DataFrame with two columns:

Aerial duels: The total number of aerial duels.

Aerial duels won: The number of aerial duels won.

You want to compute the win percentage but are running into the following issues:

ZeroDivisionError: Occurs when trying to divide by zero.

KeyError: Arises when the DataFrame can't find the specified column name.

Example Code

You might have used code like this:

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

Upon running it, you receive a KeyError for "Aerial duels".

The Solution

To avoid both ZeroDivisionError and KeyError, let's follow these steps to modify your code.

Step 1: Specify the Axis Parameter

The root cause of the KeyError is related to not specifying the correct axis parameter in the apply function. By default, apply operates on columns (axis=0). Since you want to operate row-wise, you should set the axis parameter to 1.

Step 2: Revised Code Example

Here’s the modified code that includes the axis parameter:

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

How It Works

Lambda Function: The function checks if the value in the denominator (Aerial duels) is zero:

If it is not zero, it proceeds with the division, calculating the win percentage.

If it is zero, it defaults to 0 to prevent division errors.

Correct Axis: Specifying axis=1 allows the function to apply to each row rather than each column, thus accessing the correct columns correctly.

Potential Output

Executing the corrected code will yield the percentage of aerial duels won without running into errors. Instead of raising exceptions, you'll get:

A list of calculated win percentages, with zeroes where applicable.

Conclusion

By carefully managing your DataFrame operations and setting the right parameters, you can effectively calculate ratios while avoiding common pitfalls like ZeroDivisionError and KeyError. This approach ensures your data analysis is both accurate and robust.

Happy coding!