Unexpected extra columns when using Pandas read_csv with complex CSV structure
Quick question that's been bugging me - I keep running into I'm stuck on something that should probably be simple. Quick question that's been bugging me - Hey everyone, I'm running into an issue that's driving me crazy..... I'm working with an scenario when trying to read a complex CSV file using Pandas. The file has a seemingly irregular structure where some rows contain extra columns, especially in the case of quoted fields with commas. For instance, here's a snippet of my CSV: ``` "Name","Age","Location" "Alice",30,"New York, NY" "Bob",25,"Los Angeles" "Charlie",35,"San Francisco, CA" "David",28,"Miami, FL, USA" ``` When I attempt to read this CSV using the following command: ```python import pandas as pd df = pd.read_csv('data.csv') ``` I get an behavior stating that the number of columns does not match the header. It looks like the row with "David" has an unexpected extra column due to the comma in the location field. I've tried specifying the `quotechar` and `escapechar` options, but I'm still getting this behavior: ``` behavior: behavior tokenizing data. C behavior: Expected 3 fields in line 4, saw 4 ``` I also attempted using the `error_bad_lines=False` option, but that just skips the problematic row, which isn't a solution for my case since I need all the data. Is there a way to properly handle such irregularities in the CSV structure while reading it into a DataFrame? I would appreciate any guidance or best practices for this scenario! I'm working on a API that needs to handle this. Has anyone else encountered this? For context: I'm using Python on Windows. Any help would be greatly appreciated! Could this be a known issue? This is part of a larger REST API I'm building. I'm working in a Windows 11 environment.