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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

Crafting and coloring area plots using geom_area() and more


Area plots are wild cards. They can properly represent either one or two variables. In economics for example, area plots are a very popular way to display government expenditures or a country importations versus exportation. When it comes to plotting single variable can be seen as alternatives to histograms.

This recipes is rescuing the data frame built by Recipe Creating a histogram with custom colors and bins width in order to demonstrate how to craft area plots with ggplot2, ggvis and plotly packages.

Getting ready

Once this recipe relies on simulations data frame created by Recipe Creating a histogram with custom colors and bins width make sure to have it into your environment or else obtain it by running that recipe. Code needed can be found at sections Getting Ready and How to do it... (first step only).

How to do it...

Both ggplot2, ggvis and plotly are able to draw area plots, although the last two require some computation to...

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