👀 Views: 0 💬 Answers: 1 📅 Created: 2025-06-14

pandas csv encoding data-cleaning Python

This might be a silly question, but I'm stuck trying to Hey everyone, I'm running into an issue that's driving me crazy... I'm stuck on something that should probably be simple. After trying multiple solutions online, I still can't figure this out. I tried several approaches but none seem to work... I'm working with an scenario with reading a CSV file that contains special characters using Pandas in Python 3.8. The CSV file is encoded in ISO-8859-1, but when I try to read it using `pd.read_csv()`, I'm getting unexpected characters like `�` in place of the actual data. Here’s the code snippet I'm using: ```python import pandas as pd file_path = 'data.csv' df = pd.read_csv(file_path) print(df.head()) ``` I've attempted explicitly specifying the encoding like this: ```python df = pd.read_csv(file_path, encoding='ISO-8859-1') ``` However, I still see garbled text in the output. Additionally, I've checked the file and confirmed that it does contain special characters (like accented letters). I also tried using `encoding='utf-8'` and `encoding='latin1'` but the results were still the same. I suspect this might be due to mixed encoding in the CSV file or perhaps some data corruption, but I'm unsure how to diagnose the question further. Does anyone have suggestions on how to correctly read this CSV file to avoid these unexpected characters? Any help would be appreciated! I'm working on a service that needs to handle this. How would you solve this? I'm working on a application that needs to handle this. Has anyone else encountered this? The project is a CLI tool built with Python. What's the best practice here?