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Recommended Resources
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For an in-depth introduction, we highly recommend
`Python Scientific Lecture Notes `_.
Books We Like
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* `Effective Computation in Physics `_ (beginner)
* `Python for Scientists `_ (beginner)
* `Python for Data Analysis `_ (intermediate)
* `Python and HDF5 `_ (intermediate)
Scientific Python Packages We Use
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* `numpy tutorial `_ -- core package for fast array computation in Python
* `pandas `_ -- practical data analysis tools (e.g., IO in many formats, handling missing data)
* `scikit-image `_ -- image analysis tools
* `scipy `_ --
miscellaneous functions and algorithms (special functions,
linear algebra, etc.)
* `matplotlib `_ -- powerful, publication-quality
plotting
* `conda `_ -- a package manager for the
scientific Python community
Good Scientific Software Habits
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* `Git Cheat Sheet `_
* `Novice-level introduction to Git from Software Carpentry `_
* `Intermediate-Level explanation of the git workflow we use `_