ruddyscent/minibook-2nd-code

Code of the IPython Minibook, 2nd edition (2015)

IPython minibook, second edition

This repository contains all the code examples as IPython notebooks.

Table of contents

1. Getting started with IPython

• 1.1. What are Python, IPython, and Jupyter?
• 1.2. Installing Python with Anaconda (Complete sample!)
• 1.3. Introducing the Notebook (Complete sample!)
• 1.4. A crash course on Python (Complete sample!)
• 1.5. Ten Jupyter/IPython essentials
• 1.6. Summary

2. Interactive data analysis with pandas

• 2.1. Exploring a dataset in the Notebook
• 2.2. Manipulating data
• 2.3. Complex operations
• 2.4. Summary

3. Numerical computing with NumPy

• 3.1. A primer to vector computing
• 3.2. Creating and loading arrays
• 3.3. Basic array manipulations
• 3.4. Computing with NumPy arrays (Complete sample!)
• 3.5. Summary

4. Interactive plotting and Graphical Interfaces

• 4.1. Choosing a plotting backend
• 4.2. matplotlib and seaborn essentials
• 4.3. Image processing
• 4.4. Further plotting and visualization libraries
• 4.5. Summary

5. High-performance and parallel computing

• 5.1. Accelerating Python code with Numba
• 5.2. Writing C in Python with Cython
• 5.3. Distributing tasks on several cores with IPython.parallel
• 5.4. Further high-performance computing techniques
• 5.5. Summary

6. Customizing IPython

• 6.1. Creating a custom magic command in an IPython extension
• 6.2. Writing a new Jupyter kernel
• 6.3. Displaying rich HTML elements in the Notebook
• 6.4. Customizing the Notebook interface with JavaScript
• 6.5. Summary