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IPython Notebook Essentials

Book Description

Compute scientific data and execute code interactively with NumPy and SciPy

In Detail

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.

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
  • Downloading the example code for this book. You can download the example code files for all Packt books you have purchased from your account at If you purchased this book elsewhere, you can visit and register to have the files e-mailed directly to you.

    Table of Contents

    1. IPython Notebook Essentials
      1. Table of Contents
      2. IPython Notebook Essentials
      3. Credits
      4. About the Author
      5. About the Reviewers
        1. Support files, eBooks, discount offers, and more
          1. Why subscribe?
          2. Free access for Packt account holders
      7. Preface
        1. What this book covers
        2. What you need for this book
        3. Who this book is for
        4. Conventions
        5. Reader feedback
        6. Customer support
          1. Errata
          2. Piracy
          3. Questions
      8. 1. A Tour of the IPython Notebook
        1. Getting started with Anaconda or Wakari
          1. Installing Anaconda
        2. Running the notebook
          1. Creating a Wakari account
          2. Creating your first notebook
        3. Example – the coffee cooling problem
        4. Exercises
        5. Summary
      9. 2. The Notebook Interface
        1. Editing and navigating a notebook
          1. Getting help and interrupting computations
          2. The Edit mode
          3. The Command mode
          4. Cell types
        2. IPython magics
        3. Interacting with the operating system
          1. Saving the notebook
          2. Converting the notebook to other formats
          3. Running shell commands
        4. Running scripts, loading data, and saving data
          1. Running Python scripts
          2. Running scripts in other languages
          3. Loading and saving data
        5. The rich display system
          1. Images and YouTube videos
          2. HTML
        6. Summary
      10. 3. Graphics with matplotlib
        1. The plot function
          1. Adding a title, labels, and a legend
          2. Text and annotations
        2. Three-dimensional plots
        3. Animations
        4. Summary
      11. 4. Handling Data with pandas
        1. The Series class
        2. The DataFrame class
        3. Computational and graphics tools
        4. An example with a realistic dataset
        5. Summary
      12. 5. Advanced Computing with SciPy, Numba, and NumbaPro
        1. Overview of SciPy
        2. Advanced mathematical algorithms with SciPy
          1. Solving equations and finding optimal values
          2. Calculus and differential equations
        3. Accelerating computations with Numba and NumbaPro
        4. Summary
      13. A. IPython Notebook Reference Card
        1. Starting the notebook
        2. Keyboard shortcuts
          1. Shortcuts in the Edit mode
          2. Shortcuts in the Command mode
        3. Importing modules
        4. Getting help
      14. B. A Brief Review of Python
        1. Introduction
        2. Basic types, expressions, and variables and their assignment
        3. Sequence types
          1. Lists
          2. Tuples
          3. Strings
        4. Dictionaries
        5. Control structures
          1. Functions, objects, and methods
            1. Functions
            2. Objects and methods
        6. Summary
      15. C. NumPy Arrays
        1. Introduction
        2. Array creation and member access
        3. Indexing and Slicing
      16. Index