IPython Notebook Essentials

Compute scientific data and execute code interactively with NumPy and SciPy

IPython Notebook Essentials

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L. Felipe Martins

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Compute scientific data and execute code interactively with NumPy and SciPy
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Book Details

ISBN 139781783988341
Paperback190 pages

Book Description

In data science, it is difficult to present interesting visual or technical content, as it involves scientific notations that are not easy to type in a normal document format. IPython provides a web-based UI called Notebook, which creates a working environment for interactive computing that combines code execution with computational documents. IPython Notebook makes the task simpler as it was developed for scientific programming to solve larger problems through a series of smaller programs. IPython Notebook is used to learn Python in a fun and interactive way and to do some serious parallel / technical computing.

The book begins with an introduction to the efficient use of IPython Notebook for interactive computation. The book then focuses on the integration of technologies such as matplotlib, pandas, and SciPy. The book is aimed at empowering you to work with IPython Notebook for interactive computing, configuring it, creating your own notebooks / research documents. You will learn how IPython lets you perform efficient computations through examples with NumPy, data analysis with pandas, and visualization with matplotlib.

Table of Contents

Chapter 1: A Tour of the IPython Notebook
Getting started with Anaconda or Wakari
Running the notebook
Example – the coffee cooling problem
Exercises
Summary
Chapter 2: The Notebook Interface
Editing and navigating a notebook
IPython magics
Interacting with the operating system
Running scripts, loading data, and saving data
The rich display system
Summary
Chapter 3: Graphics with matplotlib
The plot function
Three-dimensional plots
Animations
Summary
Chapter 4: Handling Data with pandas
The Series class
The DataFrame class
Computational and graphics tools
An example with a realistic dataset
Summary
Chapter 5: Advanced Computing with SciPy, Numba, and NumbaPro
Overview of SciPy
Advanced mathematical algorithms with SciPy
Accelerating computations with Numba and NumbaPro
Summary

What You Will Learn

  • Quickly install and get started with IPython Notebook
  • Create interactive widgets in the Notebook
  • Master the Notebook's interface and navigation features
  • Create publication-quality graphs and displays of data with matplotlib
  • Add media to the Notebook with IPython's Rich Display System
  • Accelerate code using NumbaPro and concurrent computing
  • Perform advanced scientific computations with SciPy
  • Work with data in the Notebook with pandas

Authors

Table of Contents

Chapter 1: A Tour of the IPython Notebook
Getting started with Anaconda or Wakari
Running the notebook
Example – the coffee cooling problem
Exercises
Summary
Chapter 2: The Notebook Interface
Editing and navigating a notebook
IPython magics
Interacting with the operating system
Running scripts, loading data, and saving data
The rich display system
Summary
Chapter 3: Graphics with matplotlib
The plot function
Three-dimensional plots
Animations
Summary
Chapter 4: Handling Data with pandas
The Series class
The DataFrame class
Computational and graphics tools
An example with a realistic dataset
Summary
Chapter 5: Advanced Computing with SciPy, Numba, and NumbaPro
Overview of SciPy
Advanced mathematical algorithms with SciPy
Accelerating computations with Numba and NumbaPro
Summary

Book Details

ISBN 139781783988341
Paperback190 pages
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