How to Compare Two CSV Files in Python and Flag the Differences

Learn how to effectively compare two CSV files in Python using Pandas, identifying changes, additions, and deletions in an easy-to-understand manner.
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How to Compare Two CSV Files in Python and Flag the Differences

As data becomes more abundant, the ability to compare and identify differences between datasets is crucial. If you've ever found yourself with two CSV files and wondered how to flag changes, additions, and deletions between them, you're not alone! This common challenge can be easily tackled using Python, specifically through the Pandas library. In this guide, we'll walk through step-by-step instructions on how to compare two CSV files and highlight those differences effectively.

Understanding the Problem

Imagine you have two CSV files: the first file contains a list of students with their subjects and marks, while the second file includes updates to that list – some subjects have changed, new students have been added, and perhaps one or two have been removed. You seek a way to seamlessly identify:

Changed items: Where the current details have been modified.

Added items: New entries in the updated file.

Deleted items: Entries no longer present in the updated file.

Example CSV Files

File 1:

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File 2:

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Desired Output:

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Step-by-Step Solution

Let’s dive into the code! We will be using the Pandas library to handle our CSV files, so make sure you have it installed. You can install it using pip if you haven’t already.

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1. Load the CSV Files

First, we need to load both CSV files into Pandas DataFrames.

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2. Flatten the DataFrames

We'll flatten the DataFrames to compare each value individually. This involves transforming the DataFrames so we can easily evaluate differences between related entries.

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3. Flag Changes

Now, we can create a logic to flag the state of each item. We'll define conditions for what constitutes changes, additions, and deletions.

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4. View the Output

Finally, we can display the resulting DataFrame which indicates the changes.

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The output will show all of the differences between the two files, clearly laid out in a structured format for easy analysis. Each item's state will indicate whether it has been changed, added, deleted, or remains unchanged.

Example Output

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Conclusion

Comparing CSV files in Python can seem daunting at first, but with Pandas, the process is fluent and manageable. This guide walked you through identifying changed, added, and deleted items between two CSV datasets, equipping you with the knowledge to effectively analyze your data. Happy coding!

If you have any further questions or need additional assistance, feel free to ask in the comments below!