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IPython Notebook Essentials

IPython Notebook Essentials

By : Martins
3.7 (3)
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IPython Notebook Essentials

IPython Notebook Essentials

3.7 (3)
By: Martins
Buy this Book

Overview of this book

If you are a professional, student, or educator who wants to learn to use IPython Notebook as a tool for technical and scientific computing, visualization, and data analysis, this is the book for you. This book will prove valuable for anyone that needs to do computations in an agile environment.
Table of Contents (10 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. A Tour of the IPython Notebook
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1. A Tour of the IPython Notebook
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Getting started with Anaconda or Wakari
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Running the notebook
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Example – the coffee cooling problem
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Exercises
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Summary
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2. The Notebook Interface
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2. The Notebook Interface
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Editing and navigating a notebook
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IPython magics
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Interacting with the operating system
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Running scripts, loading data, and saving data
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The rich display system
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Summary
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3. Graphics with matplotlib
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3. Graphics with matplotlib
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The plot function
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Three-dimensional plots
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Animations
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Summary
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4. Handling Data with pandas
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4. Handling Data with pandas
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The Series class
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The DataFrame class
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Computational and graphics tools
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An example with a realistic dataset
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Summary
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5. Advanced Computing with SciPy, Numba, and NumbaPro
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5. Advanced Computing with SciPy, Numba, and NumbaPro
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Overview of SciPy
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Advanced mathematical algorithms with SciPy
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Accelerating computations with Numba and NumbaPro
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Summary
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A. IPython Notebook Reference Card
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Starting the notebook
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Keyboard shortcuts
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Importing modules
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Getting help
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B. A Brief Review of Python
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Introduction
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Basic types, expressions, and variables and their assignment
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Sequence types
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Dictionaries
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Control structures
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Summary
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C. NumPy Arrays
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Introduction
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Array creation and member access
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Indexing and Slicing
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Index
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Index

Getting started with Anaconda or Wakari

There are several approaches to setting up an IPython notebook environment. We suggest you use Anaconda, a free distribution designed for large-scale data processing, predictive analytics, and scientific computing. Alternatively, you can use Wakari, which is a web-based installation of Anaconda. Wakari has several levels of service, but the basic level is free and suitable for experimenting and learning.

Tip

We recommend that you set up both a Wakari account and a local Anaconda installation. Wakari has the functionality of easy sharing and publication. This local installation does not require an Internet connection and may be more responsive. Thus, you get the best of both worlds!

Installing Anaconda

To install Anaconda on your computer, perform the following steps:

  1. Download Anaconda for your platform from https://store.continuum.io/cshop/anaconda/.
  2. After the file is completely downloaded, install Anaconda:
    • Windows users can double-click on the installer and follow the on-screen instruction
    • Mac users can double-click the .pkg file and follow the instructions displayed on screen
    • Linux users can run the following command:
      bash <downloaded file>

Note

Anaconda supports several different versions of Python. This book assumes you are using Version 2.7, which is the standard version that comes with Anaconda. The most recent version of Python, Version 3.0, is significantly different and is just starting to gain popularity. Many Python packages are still only fully supported in Version 2.7.

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