Insights about Python packages.

  • The Commonly used together section comes from scanning all of GitHub for files named requirements.txt, and building a recommender system based on matrix factorization.
  • Download counts are based on server logs of PyPI for each package, published by PSF.
  • Both of these datasets are published on BigQuery, which made compiling the information extremely easy.

I did all my data exploration and model building in Deepnote, which is a lovely new way to work with data science notebooks, with real-time collaboration and beautiful interface.

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