This repository contains all the code examples as IPython notebooks.

• 1.1. What is IPython?
• 1.2. What's new in IPython 3.0?
• 1.3. Installing Python with Anaconda
• 1.4. Introducing the notebook
• 1.5. A crash course on Python
• 1.6. Ten IPython essentials
• 1.7. Summary

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

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

• 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

• 5.1. 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

• 6.1. 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