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R Data Visualization Recipes

You're reading from   R Data Visualization Recipes A cookbook with 65+ data visualization recipes for smarter decision-making

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781788398312
Length 366 pages
Edition 1st Edition
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Author (1):
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Vitor Bianchi Lanzetta Vitor Bianchi Lanzetta
Author Profile Icon Vitor Bianchi Lanzetta
Vitor Bianchi Lanzetta
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Table of Contents (13) Chapters Close

Preface 1. Installation and Introduction FREE CHAPTER 2. Plotting Two Continuous Variables 3. Plotting a Discrete Predictor and a Continuous Response 4. Plotting One Variable 5. Making Other Bivariate Plots 6. Creating Maps 7. Faceting 8. Designing Three-Dimensional Plots 9. Using Theming Packages 10. Designing More Specialized Plots 11. Making Interactive Plots 12. Building Shiny Dashboards

Introduction


Finally, maps! If you think about maps single purpose is to take from location A to B I hope this chapter will change your mid. Maps are actually a wonderful way to display all sorts of information. Data journalists often use maps, a tendency created by Dr. John Snow whose creativity and efforts ended a cholera outbreak that happened in London by the nineteenths.

Maps can optimally display information that is somehow related to geography. This chapter shall create those using ggplot2,  ggvis, and plotly. We will begin by drawing the John Snow cholera map, going all the way through Afghanistan map to an interactive globe showing the countries affected by the 2009 baking crises.

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