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IPython Interactive Computing and Visualization Cookbook

You're reading from IPython Interactive Computing and Visualization Cookbook Harness IPython for powerful scientific computing and Python data visualization with this collection of more than 100 practical data science recipes

Product type Paperback

Published in Sep 2014

Publisher

ISBN-13 9781783284818

Length 512 pages

Edition 1st Edition

Languages

Python

Tools

NumPy

Concepts

Data Visualization

Author (1):

Cyrille Rossant

View More author details

Table of Contents (17) Chapters

Preface

1. A Tour of Interactive Computing with IPython FREE CHAPTER

2. Best Practices in Interactive Computing

3. Mastering the Notebook

4. Profiling and Optimization

5. High-performance Computing

6. Advanced Visualization

7. Statistical Data Analysis

8. Machine Learning

9. Numerical Optimization

10. Signal Processing

11. Image and Audio Processing

12. Deterministic Dynamical Systems

13. Stochastic Dynamical Systems

14. Graphs, Geometry, and Geographic Information Systems

15. Symbolic and Numerical Mathematics

Index

Chapter 3. Mastering the Notebook

In this chapter, we will cover the following topics:

Teaching programming in the notebook with IPython blocks
Converting an IPython notebook to other formats with nbconvert
Adding custom controls in the notebook toolbar
Customizing the CSS style in the notebook
Using interactive widgets – a piano in the notebook
Creating a custom JavaScript widget in the notebook – a spreadsheet editor for pandas
Processing webcam images in real time from the notebook

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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