Also somewhat strangely, I've found Python output has remained bad, especially for me with dataframe tasks/data analysis. For remembering matplotlib syntax I still find most of them pretty good, but for handling datagframes, very bad and extremely counter productive.

Saying that, for typed languages like TypeScript and C#, they have gotten very good. I suspect this might be related to the semantic information can be found in typed languages, and hard to follow unstructured blobs like dataframes, and there for, not well repeated by LLMs.

Spark especially is brutal for some reason. Even databrick's AI is bad at spark, which is very funny.

It's probably because spark is so backwards compatible with pandas, but not fully.