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