I am trying to read a CSV file using pd.read_csv() in Python, but I keep hitting the UnicodeDecodeError: 'utf-8' codec can't decode byte at a specific position. I've tried changing the file extension and re-saving it, but the error persists. Is there a specific encoding parameter I should be using for Excel-generated CSVs or files containing special characters to make this work?
3 answers
This error occurs because the file you are trying to read was not saved using UTF-8 encoding. Most CSV files created in older versions of Excel use cp1252 or ISO-8859-1 (latin1). In your Python code, you can resolve this by adding the encoding parameter to your read function: df = pd.read_csv('file.csv', encoding='latin1') or encoding='cp1252'. If you are unsure of the encoding, you can use the chardet library to detect it automatically. For high-stakes Data Science projects, it is best practice to standardize all raw data into UTF-8 before processing to avoid these "invalid start byte" errors during production runs.
Have you tried opening the file in a text editor like Notepad++? It usually shows the encoding in the bottom right corner, which could save you a lot of guessing time with the Python parameters.
You can also use the errors='replace' or errors='ignore' arguments in your open function if you don't mind losing a few special characters.
While 'ignore' works in a pinch, I usually avoid it because it can strip out important data markers. Using the correct 'latin1' encoding as Elena suggested is much safer for data integrity.
Mark, that’s a great manual check! I used Notepad++ and saw it was actually encoded in UTF-16. I changed my Pandas code to encoding='utf-16' and the dataframe loaded perfectly. It seems my data source was using a different Unicode standard than I expected.