Once you have that, it's trivial to do any kind of statistical analysis. In R, a regression is simply lm(y ~ x1 + x2 + ... + xn).
You can always look up how an API works, but thinking about data in terms of structures is what hinders effective analysis in most cases.
The data set I used for the demo has strings for income categories and a mix of categorical variables that the LLM had to transform, which is incredibly promising.
The insights that Claude generated also imply that it can do follow-up analysis.
This is less of a “hey write my regression code for me” and more of a “suggest the analysis, do it, find insights, and run follow up analyses”. That’s way more powerful and interesting.
I'm simply skeptical that someone who can make use of Claude (or any LLM) for data analysis is in need of making use of it. Let's hope I'm too pessimistic here.
I have seen her use Python. She uses it like a research notebook. Sequential pipeline like analysis steps. Any little change to a step, and she will run the whole thing :-)