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Learning IPython for Interactive Computing and Data Visualization, Second Edition

You're reading from Learning IPython for Interactive Computing and Data Visualization, Second Edition Get started with Python for data analysis and numerical computing in the Jupyter notebook

Product type Paperback

Published in Oct 2015

Publisher

ISBN-13 9781783986989

Length 200 pages

Edition 1st Edition

Languages

Python

Concepts

Scientific Computing

Author (1):

Cyrille Rossant

View More author details

Table of Contents (8) Chapters

Preface

1. Getting Started with IPython FREE CHAPTER

2. Interactive Data Analysis with pandas

3. Numerical Computing with NumPy

4. Interactive Plotting and Graphical Interfaces

5. High-Performance and Parallel Computing

6. Customizing IPython

Index

What this book covers

Chapter 1, Getting Started with IPython, is a thorough and beginner-friendly introduction to Anaconda (a popular Python distribution), the Python language, the Jupyter Notebook, and IPython.

Chapter 2, Interactive Data Analysis with pandas, is a hands-on introduction to interactive data analysis and visualization in the Notebook with pandas, matplotlib, and seaborn.

Chapter 3, Numerical Computing with NumPy, details how to use NumPy for efficient computing on multidimensional numerical arrays.

Chapter 4, Interactive Plotting and Graphical Interfaces, explores many capabilities of Python for interactive plotting, graphics, image processing, and interactive graphical interfaces in the Jupyter Notebook.

Chapter 5, High-Performance and Parallel Computing, introduces the various techniques you can employ to accelerate your numerical computing code, namely parallel computing and compilation of Python code.

Chapter 6, Customizing IPython, shows how IPython and the Jupyter Notebook can be extended for customized use-cases.

The rest of the chapter is locked

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Authors (1)

Cyrille Rossant

Cyrille Rossant

Cyrille Rossant, PhD, is a neuroscience researcher and software engineer at University College London. He is a graduate of École Normale Supérieure, Paris, where he studied mathematics and computer science. He has also worked at Princeton University and Collège de France. While working on data science and software engineering projects, he gained experience in numerical computing, parallel computing, and high-performance data visualization. He is the author of Learning IPython for Interactive Computing and Data Visualization, Second Edition, Packt Publishing.

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