How to Read and Compare Two CSV Files in Python

Discover how to efficiently compare one column from two CSV files using Python and Pandas, and create a new CSV with matching entries.
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How to Read and Compare Two CSV Files in Python: A Step-by-Step Guide

When working with data, you may often find yourself needing to compare two sets of records. If you have two CSV files and want to identify the common names between them, this guide is for you!

In this guide, we'll explore how to read two CSV files, compare a specific column from both, and output a new CSV containing the matching entries. Let's dive right in!

The Problem: Comparing Two CSV Files

You have two CSV files containing names, and you want to find the names that are present in both files. Here’s a quick summary of what your CSV files look like:

CSV 1

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CSV 2

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The goal is to identify that "Bill" appears in both CSV files and create a new CSV that lists this name.

The Solution: Using Pandas to Find Common Entries

We will utilize the Pandas library in Python, which provides powerful tools for data manipulation and analysis. Pandas allows you to easily read CSV files and perform operations like merging and comparing data.

Step 1: Install Pandas

Before you get started, ensure you have Pandas installed in your Python environment. You can install it using pip:

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Step 2: Read the CSV Files

Next, you’ll need to load your CSV files into Pandas DataFrames. Here’s how to read the two CSVs:

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Step 3: Merge the DataFrames

To find the common names, use the merge function, specifying the "Names" column as the basis for the comparison. Here's the code for that:

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Step 4: Save the Results to a New CSV

Once you have the matching entries, you can export the result to a new CSV file. Here’s how to do that:

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Full Code Example

Putting it all together, your complete script would look like this:

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Conclusion

You now have a straightforward method to compare columns in two CSV files and generate a new one with the same names. This technique can save time and enhance your data processing capabilities. By leveraging the power of Pandas, you can easily manipulate and analyze your data without needing complex coding.

Give this a try next time you need to compare datasets, and streamline your data management tasks!