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  • Book Overview & Buying IPython Notebook Essentials
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IPython Notebook Essentials

IPython Notebook Essentials

By : Luiz Felipe Martins
3.7 (3)
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IPython Notebook Essentials

IPython Notebook Essentials

3.7 (3)
By: Luiz Felipe 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
2
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
3
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
6
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

Animations

We will finish the chapter with a more complex example that illustrates the power that matplotlib gives us. We will create an animation of a forced pendulum, a well-known and much studied example of a dynamic system exhibiting deterministic chaos.

Since this section involves more sophisticated code, we will refrain from using pylab and adopt the generally recommended way of importing modules. This makes the code easier to export to a script if we so wish. We also give samples of some of the object-oriented features of matplotlib.

The process of animating a pendulum (or any physical process) is actually very simple: we compute the position of the pendulum at a finite number of times and display the corresponding images in quick succession. So, the code will naturally break down into the following three pieces:

  • A function that displays a pendulum in an arbitrary position
  • Setting up the computation of the position of the pendulum at an arbitrary time
  • The code that actually computes the...
CONTINUE READING
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Tech Concepts
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Programming languages
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IPython Notebook Essentials
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