alt Hacker NewsThe article uses pandas as a demo example for LLM failures, but for some reason, even the latest LLMs are bad at data science code which is extremely counterintuitive. Opus 4.5 can write a EDA backbone but it's often too verbose for code that's intended for a Jupyter Notebook.
The issues have been less egregious than hallucinating an "index_value" column, though, so I'm suspect. Opus 4.5 still has been useful for data preprocessing, especially in cases where the input data is poorly structured/JSON.
This is not my experience. Claude Code has been fine for data science for a while. It has many issues and someone at the wheel who knows what they're doing is very much required, but for many common cases I'm not writing code by hand anymore, especially when the code would have been throwaway anyway. I'd be extremely surprised if a frontier model doesn't immediately get the problem the author is pointing out.