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Practical Data Science Cookbook, Second Edition

You're reading from   Practical Data Science Cookbook, Second Edition Data pre-processing, analysis and visualization using R and Python

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Product type Paperback
Published in Jun 2017
Publisher Packt
ISBN-13 9781787129627
Length 434 pages
Edition 2nd Edition
Languages
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Authors (5):
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Anthony Ojeda Anthony Ojeda
Author Profile Icon Anthony Ojeda
Anthony Ojeda
Prabhanjan Narayanachar Tattar Prabhanjan Narayanachar Tattar
Author Profile Icon Prabhanjan Narayanachar Tattar
Prabhanjan Narayanachar Tattar
ABHIJIT DASGUPTA ABHIJIT DASGUPTA
Author Profile Icon ABHIJIT DASGUPTA
ABHIJIT DASGUPTA
Sean P Murphy Sean P Murphy
Author Profile Icon Sean P Murphy
Sean P Murphy
Bhushan Purushottam Joshi Bhushan Purushottam Joshi
Author Profile Icon Bhushan Purushottam Joshi
Bhushan Purushottam Joshi
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Table of Contents (12) Chapters Close

Preface 1. Preparing Your Data Science Environment 2. Driving Visual Analysis with Automobile Data with R FREE CHAPTER 3. Creating Application-Oriented Analyses Using Tax Data and Python 4. Modeling Stock Market Data 5. Visually Exploring Employment Data 6. Driving Visual Analyses with Automobile Data 7. Working with Social Graphs 8. Recommending Movies at Scale (Python) 9. Harvesting and Geolocating Twitter Data (Python) 10. Forecasting New Zealand Overseas Visitors 11. German Credit Data Analysis

Exploring Jupyter Notebook


Jupyter Notebook is the perfect complement to Python. In practice, Jupyter Notebook allows you to intersperse your code with comments and images and anything else that might be useful. You can use Jupyter Notebooks for everything from presentations (a great replacement for PowerPoint) to an electronic laboratory notebook or a textbook.

Getting ready

If you have completed the installation instructions in the first chapter, you should be ready to tackle the following recipes.

How to do it...

These steps will get you started with exploring the incredibly powerful Jupyter Notebook environment. We urge you to go beyond this simple set of steps to understand the true power of the tool:

  1. Create a folder at the terminal, say test, with mkdir test, and move into that folder with cd test.
  2. Type jupyter notebook in the command prompt. You should see some text quickly scroll by in the terminal window, and then, the following screen should load in the default browser (for me, this...
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