Welcome to Scientific Python and its community! With this practical book, you'll learn the fundamental parts of SciPy and related libraries, and get a taste of beautiful, easy-to-read code that you can use in practice. More and more scientists are programming, and the SciPy library is here to help.
Finding useful functions and using them correctly, efficiently, and in easily readable code are two very different things. You'll learn by example with some of the best code available, selected to cover a wide range of SciPy and related libraries—including scikit-learn, scikit-image, toolz, and pandas.
The examples highlight clever, elegant uses of advanced features of NumPy, SciPy, and related libraries. Beginners will learn not the functionality of the library, but its application to real world problems. This book starts from first principles and provides all of the necessary background to understand each example, including idioms, libraries, and scientific concepts.
Table of Contents
Chapter 1. Elegant NumPy: The Foundation of Scientific Python
Chapter 2. Quantile normalization with NumPy and SciPy
Chapter 3. Networks of Image Regions with ndimage
Chapter 4. Frequency and the fast Fourier transform
Chapter 5. Contingency tables using sparse coordinate matrices
Chapter 6. Linear algebra in SciPy
Chapter 7. Function optimization in SciPy
Chapter 8. Big Data in Little Laptop with Toolz