Learning IPython for Interactive Computing and Data Visualization - Second Edition

Cover
Copyright
Credits
About the Author
About the Reviewers
www.PacktPub.com
Table of Contents
Preface
Chapter 1: Getting Started with IPython
	What are Python, IPython, and Jupyter?
		Jupyter and IPython
		What this book covers
		References
	Installing Python with Anaconda
		Downloading Anaconda
		Installing Anaconda
		Before you get started...
			Opening a terminal
			Finding your home directory
			Manipulating your system path
		Testing your installation
		Managing environments
		Common conda commands
		References
		Downloading the notebooks
	Introducing the Notebook
		Launching the IPython console
		Launching the Jupyter Notebook
		The Notebook dashboard
		The Notebook user interface
		Structure of a notebook cell
			Markdown cells
			Code cells
		The Notebook modal interface
			Keyboard shortcuts available in both modes
			Keyboard shortcuts available in the edit mode
			Keyboard shortcuts available in the command mode
		References
	A crash course on Python
		Hello world
		Variables
		String escaping
		Lists
		Loops
		Indentation
		Conditional branches
		Functions
		Positional and keyword arguments
		Passage by assignment
		Errors
		Object-oriented programming
		Functional programming
		Python 2 and 3
		Going beyond the basics
	Ten Jupyter/IPython essentials
		Using IPython as an extended shell
		Learning magic commands
		Mastering tab completion
		Writing interactive documents in the Notebook with Markdown
		Creating interactive widgets in the Notebook
		Running Python scripts from IPython
		Introspecting Python objects
		Debugging Python code
		Benchmarking Python code
		Profiling Python code
	Summary
Chapter 2: Interactive Data Analysis with pandas
	Exploring a dataset in the Notebook
		Provenance of the data
		Downloading and loading a dataset
		Making plots with matplotlib
		Descriptive statistics with pandas and seaborn
	Manipulating data
		Selecting data
			Selecting columns
			Selecting rows
			Filtering with boolean indexing
		Computing with numbers
		Working with text
		Working with dates and times
		Handling missing data
	Complex operations
		Group-by
		Joins
	Summary
Chapter 3: Numerical Computing with NumPy
	A primer to vector computing
		Multidimensional arrays
		The ndarray
		Vector operations on ndarrays
		How fast are vector computations in NumPy?
		How an ndarray is stored in memory
		Why operations on ndarrays are fast
	Creating and loading arrays
		Creating arrays
		Loading arrays from files
	Basic array manipulations
	Computing with NumPy arrays
		Selection and indexing
		Boolean operations on arrays
		Mathematical operations on arrays
		A density map with NumPy
		Other topics
	Summary
Chapter 4: Interactive Plotting and Graphical Interfaces
	Choosing a plotting backend
		Inline plots
		Exported figures
		GUI toolkits
		Dynamic inline plots
		Web-based visualization
	matplotlib and seaborn essentials
		Common plots with matplotlib
		Customizing matplotlib figures
		Interacting with matplotlib figures in the Notebook
		High-level plotting with seaborn
	Image processing
	Further plotting and visualization libraries
		High-level plotting
			Bokeh
			Vincent and Vega
			Plotly
		Maps and geometry
			The matplotlib Basemap toolkit
			GeoPandas
			Leaflet wrappers: folium and mplleaflet
		3D visualization
			Mayavi
			VisPy
	Summary
Chapter 5: High-Performance and Parallel Computing
	Accelerating Python code with Numba
		Random walk
		Universal functions
	Writing C in Python with Cython
		Installing Cython and a C compiler for Python
		Implementing the Eratosthenes Sieve in Python and Cython
	Distributing tasks on several cores with IPython.parallel
		Direct interface
		Load-balanced interface
	Further high-performance computing techniques
		MPI
		Distributed computing
		C/C++ with Python
		GPU computing
		PyPy
		Julia
	Summary
Chapter 6: Customizing IPython
	Creating a custom magic command in an IPython extension
	Writing a new Jupyter kernel
	Displaying rich HTML elements in the Notebook
		Displaying SVG in the Notebook
		JavaScript and D3 in the Notebook
	Customizing the Notebook interface with JavaScript
	Summary
Index