This is a small collection of useful libraries apart from the well-known standards like pandas or requests.
- hypothesis allows you to use property based testing for your code. The test cases are generated automatically, covering corner cases you never might have thought of.
- holoviews is for plotting your data what CSS is for HTML. Reproducible research made easier, and a large reduction in boilerplate code. Integrates nicely with the iPython/Jupyter notebook. geoviews is a new library built on holoviews, which you can use to visualize geographical, meteorological, oceanographic, weather, and climate data.
- powerlaw is a library that allows you to test whether your data follows a power law - the right way.
- TPOT is a Python tool that automatically creates and optimizes machine learning pipelines using genetic programming.
- MLextend (machine learning extensions) is a library of useful tools for the day-to-day data science tasks.
- LIME - Local Interpretable Model-Agnostic Explanations helps you uncover what features your model actually uses for its predictions.
- pathlib - actually part of the standard library since Python 3.4.