How to Fix CSV Encoding Issues in Excel: Two Simple Methods
This guide explains why CSV files appear garbled in Excel, then walks you through two practical solutions—opening the file with Notepad++ using UTF‑8 encoding and importing it via Excel’s “From Text/CSV” wizard—complete with screenshots and code examples.
Introduction
A fan asked why a CSV file shows unreadable characters when opened directly in Excel. The problem is caused by mismatched character encodings, and the solution is to ensure the file is read as UTF‑8.
Method 1: Open with Notepad++
Since a CSV is a plain‑text file, you can open it in Notepad++ and verify it is saved with UTF‑8 encoding. If your web‑scraping script writes the file using UTF‑8, the content will display correctly in Notepad++.
f = open('filename.csv', mode='a', encoding="utf-8")
csvwriter = csv.writer(f)When the file is saved in UTF‑8, Notepad++ shows the correct characters (the example uses Korean and Japanese text, which is not garbled).
Method 2: Import via Excel
Use Excel’s built‑in import wizard:
Open Excel and click Data → From Text/CSV .
Select the CSV file; a preview window appears.
Set the file’s original format to UTF‑8 , keep the delimiter as a comma, and let Excel detect data types.
Click Load and wait for the data to appear.
After loading, the characters display correctly, and you can further save the file as an Excel workbook or continue processing the data.
Conclusion
The article demonstrates two effective ways to resolve CSV encoding problems in Excel, helping beginners overcome a common obstacle when working with data scraped by Python.
Signed-in readers can open the original source through BestHub's protected redirect.
This article has been distilled and summarized from source material, then republished for learning and reference. If you believe it infringes your rights, please contactand we will review it promptly.
Python Crawling & Data Mining
Life's short, I code in Python. This channel shares Python web crawling, data mining, analysis, processing, visualization, automated testing, DevOps, big data, AI, cloud computing, machine learning tools, resources, news, technical articles, tutorial videos and learning materials. Join us!
How this landed with the community
Was this worth your time?
0 Comments
Thoughtful readers leave field notes, pushback, and hard-won operational detail here.
