Book description
Get started with Python for data analysis and numerical computing in the Jupyter notebook
About This Book
 Learn the basics of Python in the Jupyter Notebook
 Analyze and visualize data with pandas, NumPy, matplotlib, and seaborn
 Perform highlyefficient numerical computations with Numba, Cython, and ipyparallel
Who This Book Is For
This book targets students, teachers, researchers, engineers, analysts, journalists, hobbyists, and all data enthusiasts who are interested in analyzing and visualizing realworld datasets. If you are new to programming and data analysis, this book is exactly for you. If you're already familiar with another language or analysis software, you will also appreciate this introduction to the Python data analysis platform. Finally, there are more technical topics for advanced readers. No prior experience is required; this book contains everything you need to know.
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 scikitimage
 Accelerate your code with Numba, Cython, and IPython.parallel
 Extend the Notebook interface with HTML, JavaScript, and D3
In Detail
Python is a userfriendly and powerful programming language. IPython offers a convenient interface to the language and its analysis libraries, while the Jupyter Notebook is a rich environment welladapted 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 beginnerfriendly 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 realworld 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 indepth analyses of all sorts of data.
Style and approach
This is a handson beginnerfriendly guide to analyze and visualize data on realworld examples with Python and the Jupyter Notebook.
Publisher resources
Table of contents

Learning IPython for Interactive Computing and Data Visualization Second Edition
 Table of Contents
 Learning IPython for Interactive Computing and Data Visualization Second Edition
 Credits
 About the Author
 About the Reviewers
 www.PacktPub.com
 Preface

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
 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
 2. Interactive Data Analysis with pandas
 3. Numerical Computing with NumPy
 4. Interactive Plotting and Graphical Interfaces
 5. HighPerformance and Parallel Computing
 6. Customizing IPython
 Index
Product information
 Title: Learning IPython for Interactive Computing and Data Visualization  Second Edition
 Author(s):
 Release date: October 2015
 Publisher(s): Packt Publishing
 ISBN: 9781783986989
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