Learning IPython for Interactive Computing and Data Visualization - (Paperback)

Cyrille Rossant

ISBN 10: 1783986980 / ISBN 13: 9781783986989

Published by Packt Publishing Limited, Birmingham, 2015

About this Item

Paperback. Get started with Python for data analysis and numerical computing in the Jupyter notebookAbout This Book Learn the basics of Python in the Jupyter Notebook Analyze and visualize data with pandas, NumPy, matplotlib, and seaborn Perform highly-efficient numerical computations with Numba, Cython, and ipyparallelWho This Book Is ForThis book targets students, teachers, researchers, engineers, analysts, journalists, hobbyists, and all data enthusiasts who are interested in analyzing and visualizing real-world 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 scikit-image Accelerate your code with Numba, Cython, and IPython.parallel Extend the Notebook interface with HTML, JavaScript, and D3In DetailPython 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.Style and approachThis is a hands-on beginner-friendly guide to analyze and visualize data on real-world examples with Python and the Jupyter Notebook. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9781783986989

Bibliographic Details

• Title: Learning IPython for Interactive Computing and Data Visualization - (Paperback)
• Publisher: Packt Publishing Limited, Birmingham
• Publication Date: 2015
• Language: English
• ISBN 10: 1783986980
• ISBN 13: 9781783986989
• Binding: Paperback
• Edition: 2nd Edition
• Condition: new

About this title

Synopsis

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 highly-efficient 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 real-world 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 scikit-image
• Accelerate your code with Numba, Cython, and IPython.parallel
• Extend the Notebook interface with HTML, JavaScript, and D3

In Detail

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.

Style and approach

This is a hands-on beginner-friendly guide to analyze and visualize data on real-world examples with Python and the Jupyter Notebook.

About the Author

Cyrille Rossant

Cyrille Rossant is a researcher in neuroinformatics, and is a graduate of Ecole Normale Superieure, Paris, where he studied mathematics and computer science. He has worked at Princeton University, University College London, and College de France. As part of his data science and software engineering projects, he gained experience in machine learning, high-performance computing, parallel computing, and big data visualization. He is one of the main developers of VisPy, a high-performance visualization package in Python. He is the author of the IPython Interactive Computing and Visualization Cookbook, Packt Publishing, an advanced-level guide to data science and numerical computing with Python, and the sequel of this book.