Learning IPython for Interactive Computing and Data Visualization, 2/Ed > PACKT 원서리스트

1: Getting Started with IPython
What are Python, IPython, and Jupyter?
Installing Python with Anaconda
Introducing the Notebook
A crash course on Python
Ten Jupyter/IPython essentials
Summary

2: Interactive Data Analysis with pandas
Exploring a dataset in the Notebook
Manipulating data
Complex operations
Summary

3: Numerical Computing with NumPy
A primer to vector computing
Creating and loading arrays
Basic array manipulations
Computing with NumPy arrays
Summary

4: Interactive Plotting and Graphical Interfaces
Choosing a plotting backend
matplotlib and seaborn essentials
Image processing
Further plotting and visualization libraries
Summary

5: High-Performance and Parallel Computing
Accelerating Python code with Numba
Writing C in Python with Cython
Distributing tasks on several cores with IPython.parallel
Further high-performance computing techniques
Summary

6: Customizing IPython
Creating a custom magic command in an IPython extension
Writing a new Jupyter kernel
Displaying rich HTML elements in the Notebook
Customizing the Notebook interface with JavaScript
Summary

Appendix A: Index