Learning IPython for Interactive Computing and Data Visualization - Second Edition

Get started with Python for data analysis and numerical computing in the Jupyter notebook

Learning IPython for Interactive Computing and Data Visualization - Second Edition

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Cyrille Rossant

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Get started with Python for data analysis and numerical computing in the Jupyter notebook
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Book Details

ISBN 139781783986989
Paperback200 pages

Book Description

Python is a user-friendly and powerful programming language. IPython offers a convenient interface to the language and its analysis libraries, while the Jupyter Notebook is a rich environment well-adapted to data science and visualization. Together, these open source tools are widely used by beginners and experts around the world, and in a huge variety of fields and endeavors.

This book is a beginner-friendly guide to the Python data analysis platform. After an introduction to the Python language, IPython, and the Jupyter Notebook, you will learn how to analyze and visualize data on real-world examples, how to create graphical user interfaces for image processing in the Notebook, and how to perform fast numerical computations for scientific simulations with NumPy, Numba, Cython, and ipyparallel. By the end of this book, you will be able to perform in-depth analyses of all sorts of data.

Table of Contents

Chapter 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
Chapter 2: Interactive Data Analysis with pandas
Exploring a dataset in the Notebook
Manipulating data
Complex operations
Summary
Chapter 3: Numerical Computing with NumPy
A primer to vector computing
Creating and loading arrays
Basic array manipulations
Computing with NumPy arrays
Summary
Chapter 4: Interactive Plotting and Graphical Interfaces
Choosing a plotting backend
matplotlib and seaborn essentials
Image processing
Further plotting and visualization libraries
Summary
Chapter 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
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
Customizing the Notebook interface with JavaScript
Summary

What You Will Learn

  • Install Anaconda and code in Python in the Jupyter Notebook
  • Load and explore datasets interactively
  • Perform complex data manipulations effectively with pandas
  • Create engaging data visualizations with matplotlib and seaborn
  • Simulate mathematical models with NumPy
  • Visualize and process images interactively in the Jupyter Notebook with scikit-image
  • Accelerate your code with Numba, Cython, and IPython.parallel
  • Extend the Notebook interface with HTML, JavaScript, and D3

Authors

Table of Contents

Chapter 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
Chapter 2: Interactive Data Analysis with pandas
Exploring a dataset in the Notebook
Manipulating data
Complex operations
Summary
Chapter 3: Numerical Computing with NumPy
A primer to vector computing
Creating and loading arrays
Basic array manipulations
Computing with NumPy arrays
Summary
Chapter 4: Interactive Plotting and Graphical Interfaces
Choosing a plotting backend
matplotlib and seaborn essentials
Image processing
Further plotting and visualization libraries
Summary
Chapter 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
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
Customizing the Notebook interface with JavaScript
Summary

Book Details

ISBN 139781783986989
Paperback200 pages
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