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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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 Tattar Tattar
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Tattar
Bhushan Purushottam Joshi Bhushan Purushottam Joshi
Author Profile Icon Bhushan Purushottam Joshi
Bhushan Purushottam Joshi
Sean P Murphy Sean P Murphy
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Sean P Murphy
ABHIJIT DASGUPTA ABHIJIT DASGUPTA
Author Profile Icon ABHIJIT DASGUPTA
ABHIJIT DASGUPTA
Anthony Ojeda Anthony Ojeda
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Anthony Ojeda
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Toc

Table of Contents (17) Chapters Close

Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
1. Preparing Your Data Science Environment FREE CHAPTER 2. Driving Visual Analysis with Automobile Data with R 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

Animating maps for a geospatial time series


One of the real interests in this project is to see how wage patterns, as a surrogate for income patterns, changed over time. The QCEW site provides data from 2003 to 2012. In this recipe, we will look at the overall average annual pay by county for each of these years and create an animation that displays the changes in the pay pattern over this period.

Getting ready

For this recipe, we need to download the annual data for the years 2003 to 2011 from the BLS website, at http://www.bls.gov/cew/datatoc.htm . You will need to download the files corresponding to these years for the QCEW NIACS-based data files in the column CSVs Single Files-Annual Averages. Store these files (which are compressed .zip files) in the same location as the zipped 2012 data that you downloaded at the beginning of this project. Don't unzip them! You must also download and install the choroplethr package using install.packages('chloroplethr'), if you haven't already done...

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