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Popularity of Python Packages for Data Science

I was using pyodide. “Pyodide brings the Python 3.9 runtime to the browser via WebAssembly, along with the Python scientific stack including NumPy, Pandas, Matplotlib, SciPy, and scikit-learn. Over 75 packages are currently available. In addition it’s possible to install pure Python wheels from PyPi.”

I was curious to see, how popular are the packages that Pyodide supports. So, I went to PyPi and found a nice webpage on Analyzing PyPI package downloads

I had to get setup with Google’s Big Query, it was no big deal, but that required getting setup with an account and an API key.

Here are the exports for:

  • altair
  • astropy
  • beautifulsoup
  • bokeh
  • cryptography
  • ggplot
  • list.txt
  • matplotlib
  • numba
  • numpy
  • pandas
  • plotly
  • pytorch
  • regex
  • scikit-image
  • scikit-learn
  • scipy
  • seaborn
  • setuptools
  • sympy
  • tink

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