********************* Recommended Resources ********************* For an in-depth introduction, we highly recommend `Python Scientific Lecture Notes `_. Books We Like ------------- * `Effective Computation in Physics `_ (beginner) * `Python for Scientists `_ (beginner) * `Python for Data Analysis `_ (intermediate) * `Python and HDF5 `_ (intermediate) Scientific Python Packages We Use --------------------------------- * `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 ------------------------------- * `Git Cheat Sheet `_ * `Novice-level introduction to Git from Software Carpentry `_ * `Intermediate-Level explanation of the git workflow we use `_