Karpathy dropped a 200-line GPT, so I used the math to turn pandas DataFrames into searchable context windows and open sourced it (and automated my stats pipeline). [P]

TL;DR: I got tired of manually running Shapiro-Wilk tests and copy-pasting p-values at 2 AM. I built an open-source, async Python pipeline called StatForge that automates the statistical decision layer, writes APA methods, and lets you chat with your dataset using a microgpt -inspired retrieval system. Hey everyone, The hardest part of data analysis isn't the computation (we all have scipy and statsmodels ). It's the plumbing - the sequence of choices between loading a CSV and having a defensible result. I built StatForge to handle the plumbing.