Скачать или смотреть How to Effectively Read from Two CSV Files in Python

Learn how to resolve common issues when reading multiple CSV files in Python. This guide explains the `for-else` loop technique for efficiently iterating over CSV data.
---
This video is based on the question https://stackoverflow.com/q/62898808/ asked by the user 'Prab' ( https://stackoverflow.com/u/7564449/ ) and on the answer https://stackoverflow.com/a/62905011/ provided by the user 'H. pap' ( https://stackoverflow.com/u/11110084/ ) 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: Reading from two CSV files

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.
---
Introduction: The Challenge of Reading Two CSV Files in Python

Reading data from multiple CSV files in Python can sometimes lead to unexpected behaviors, especially if you're not accustomed to how file pointers work. In this post, we'll address a specific issue one of our readers encountered when trying to check for matches between two CSV files using Python's csv module. Understanding and resolving this problem is crucial for anyone looking to work with CSV data effectively.

The Code Problem

In the code shared by our reader, the intent was to read data from firstfile.csv containing several entries, iterate through a second file secondfile.csv, and print out certain information. However, the output the reader received wasn't as expected. Here’s a brief overview of the scenario:

Input files:

firstfile.csv

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

secondfile.csv

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

Expected Output:

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

Actual Output:

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

The main issue arises from how the second file is being read. Once the CSV file is read, the file pointer reaches the end, and subsequent reads yield no new data unless explicitly reset.

Understanding the Solution

To resolve this issue, we can use a combination of Python's file handling capabilities and a loop structure known as the for-else construct. The solution involves resetting the file pointer back to the beginning of the second file after completing a read.

The Modified Code

Here's the modified code that incorporates the file.seek(0) method along with the for-else loop structure:

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

How it Works

CSV Reading: We read from firstfile.csv using csv.DictReader, which returns each row as a dictionary.

Checking for Matches: For each entry in firstfile.csv, the code checks for matches in secondfile.csv.

Using file.seek(0): The seek(0) method resets the position of the file pointer back to the start, allowing us to read through secondfile.csv again when required.

Understanding the for-else Loop: If the inner loop doesn't break (i.e., no match was found), the else block gets executed, invoking seek(0) to prepare for the next entry from the first file.

Resulting Output

When the modified code is run, the expected output is achieved:

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

Conclusion

Reading from multiple CSV files doesn't have to be a daunting task. By simply understanding how Python handles file pointers and utilizing structures like for-else in your loops, you can simplify your data processing tasks. Whether you're managing large datasets or just looking to execute simple scripts, these techniques will enhance your efficiency in handling CSV files in Python.

If you have any more questions on working with CSVs in Python, feel free to reach out in the comments below!