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PavelGrigoryevDS/awesome-data-analysis
🚀 500+ curated resources for Data Analysis & Data Science: Python, SQL, Statistics, ML, AI, Visualization, Cheatsheets, Roadmaps, Interview Prep. For beginners and experts.
A large link collection for data analysis and data science, covering Python, SQL, ML, visualization, and career prep. It's an aggregator of other resources, not a tool or library itself. Aimed at beginners breaking in and practitioners who want a single bookmark to send juniors.
Breadth is genuine — the SQL section alone covers engines, ORMs, GUI clients, linters, and AI query tools without obvious gaps. The structure is navigable: a detailed TOC with anchor links and a companion web version. Tool entries are consistently brief and accurate, not padded with marketing copy. The link checker CI workflow and active maintenance (last push June 2026) mean dead links get caught.
It's a list of lists — most top-level sections just point to other awesome-* repos, which themselves point elsewhere, so the actual information density is low. No curation signal: a toy single-author repo and a major Apache project sit side-by-side with equal weight. The 'Awesome Data Science Repositories' section at the top is just... more lists, which is recursive in an unhelpful way. Zero opinion on when to use one tool over another — Polars vs Dask vs Modin are listed back-to-back with no guidance on which to reach for.