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  • Book Overview & Buying IPython Notebook Essentials
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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
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
4
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
5
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
7
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
8
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

Three-dimensional plots

In this section, we present methods to display three-dimensional plots, that is, plots of mathematical objects in space. Examples include surfaces and lines that are not confined to a plate.

matplotlib has excellent support for three-dimensional plots. In this section, we will present an example of a surface plot and corresponding contour plot. The types of plot available in the three-dimensional library include wireframe plots, line plots, scatterplots, triangulated surface plots, polygon plots, and several others. The following link will help you to understand the types of plots that are not treated here: http://matplotlib.org/1.3.1/mpl_toolkits/mplot3d/tutorial.html#mplot3d-tutorial

Before we start, we need to import the three-dimensional library objects we need using the following command line:

from mpl_toolkits.mplot3d import axes3d

Now, let's draw our surface plot by running the following code in a cell:

def dist(x, y):
    return sqrt(x**2 + y**2) 
def fsurface...
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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