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  • Learning IPython for Interactive Computing and Data Visualization, Second Edition
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Learning IPython for Interactive Computing and Data Visualization, Second Edition

Learning IPython for Interactive Computing and Data Visualization, Second Edition

By : Cyrille Rossant
4.5 (12)
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Learning IPython for Interactive Computing and Data Visualization, Second Edition

Learning IPython for Interactive Computing and Data Visualization, Second Edition

4.5 (12)
By: Cyrille Rossant

Overview of this book

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 (8 chapters)
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Chapter 6. Customizing IPython

The Jupyter Notebook is a highly-customizable platform. You can configure many aspects of the software in your configuration files. You can also extend the backend (kernels) and the frontend (HTML-based Notebook). This allows you to create highly-personalized user experiences based on the Notebook.

In this chapter, we will cover the following topics:

  • 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
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