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IPython Notebook Essentials

By : Martins

3.7 (3)

IPython Notebook Essentials

3.7 (3)

By: Martins

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.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

1. A Tour of the IPython Notebook

1. A Tour of the IPython Notebook

Getting started with Anaconda or Wakari

Running the notebook

Example – the coffee cooling problem

Exercises

Summary

2. The Notebook Interface

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

3. Graphics with matplotlib

3. Graphics with matplotlib

The plot function

Three-dimensional plots

Animations

Summary

4. Handling Data with pandas

4. Handling Data with pandas

The Series class

The DataFrame class

Computational and graphics tools

An example with a realistic dataset

Summary

5. Advanced Computing with SciPy, Numba, and NumbaPro

5. Advanced Computing with SciPy, Numba, and NumbaPro

Overview of SciPy

Advanced mathematical algorithms with SciPy

Accelerating computations with Numba and NumbaPro

Summary

A. IPython Notebook Reference Card

Starting the notebook

Keyboard shortcuts

Importing modules

Getting help

B. A Brief Review of Python

Introduction

Basic types, expressions, and variables and their assignment

Sequence types

Dictionaries

Control structures

Summary

C. NumPy Arrays

Introduction

Array creation and member access

Indexing and Slicing

Index

Index

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Exercises

The following are some practice questions that will help you to understand and apply the concepts learned in this chapter:

In our example, we discussed how to determine the cooling rate r. Modify the example to plot the temperature evolution for several values of r, keeping all other variables fixed.
Search the matplotlib documentation at http://matplotlib.org to figure out how to generate a contour plot of the temperature differences.
Our analysis ignores the fact that the cream will also change temperature as we walk. Change the notebook so that this factor is taken into account

Visually different images

CONTINUE READING

83

Tech Concepts

36

Programming languages

73

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