👀 Views: 0 💬 Answers: 1 📅 Created: 2025-08-08

python pandas csv Python

I tried several approaches but none seem to work. I've been working on this all day and I'm working with an scenario where my code using pandas to read a CSV file is returning an empty DataFrame, even though the file is not empty. I'm using pandas version 1.3.0 on macOS Big Sur. Here's a snippet of my code: ```python import pandas as pd file_path = 'data/sample.csv' df = pd.read_csv(file_path) print(df) ``` The output of `print(df)` shows `Empty DataFrame\nColumns: []\nIndex: []`. I've double-checked the CSV file, and it does contain rows of data. When I open the file with Excel, it looks fine. I've tried the following troubleshooting steps: 1. **Checked the file path:** I confirmed that the file path is correct and the file exists with `os.path.exists(file_path)` which returned `True`. 2. **Read CSV with different parameters:** I attempted to specify different separators like `sep=';'` or `sep='\t'`, and also specified `header=None`, but none worked. 3. **File encoding:** I tried setting the encoding to `utf-8` and `ISO-8859-1` using the `encoding` parameter in `pd.read_csv()`, but still only got the empty DataFrame. 4. **Print raw content:** I opened the file in binary mode and printed its content: ```python with open(file_path, 'rb') as f: print(f.read()) ``` The output looked normal. I suspect it might be an scenario with how macOS handles line endings or some hidden metadata in the CSV. Is there a particular setting in pandas that I might be overlooking, or any other methods to troubleshoot this scenario effectively? Am I missing something obvious? I'm working with Python in a Docker container on Debian.