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R Data Analysis Cookbook, Second Edition

You're reading from   R Data Analysis Cookbook, Second Edition Customizable R Recipes for data mining, data visualization and time series analysis

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787124479
Length 560 pages
Edition 2nd Edition
Languages
Tools
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Authors (3):
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Kuntal Ganguly Kuntal Ganguly
Author Profile Icon Kuntal Ganguly
Kuntal Ganguly
Shanthi Viswanathan Shanthi Viswanathan
Author Profile Icon Shanthi Viswanathan
Shanthi Viswanathan
Viswa Viswanathan Viswa Viswanathan
Author Profile Icon Viswa Viswanathan
Viswa Viswanathan
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Table of Contents (14) Chapters Close

Preface 1. Acquire and Prepare the Ingredients - Your Data 2. What's in There - Exploratory Data Analysis FREE CHAPTER 3. Where Does It Belong? Classification 4. Give Me a Number - Regression 5. Can you Simplify That? Data Reduction Techniques 6. Lessons from History - Time Series Analysis 7. How does it look? - Advanced data visualization 8. This may also interest you - Building Recommendations 9. It's All About Your Connections - Social Network Analysis 10. Put Your Best Foot Forward - Document and Present Your Analysis 11. Work Smarter, Not Harder - Efficient and Elegant R Code 12. Where in the World? Geospatial Analysis 13. Playing Nice - Connecting to Other Systems

Where in the World? Geospatial Analysis

In this chapter, we will cover the following recipes:

  • Downloading and plotting a Google map of an area
  • Overlaying data on the downloaded Google map
  • Importing ESRI shape files to R
  • Using the sp package to plot geographic data
  • Getting maps from the maps package
  • Creating spatial data frames from regular data frames containing spatial and other data
  • Creating spatial data frames by combining regular data frames with spatial objects
  • Adding variables to an existing spatial data frame
  • Spatial data analysis with R and QGIS
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