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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

Draw alternative lollipop and density plots with ggalt


This is another creation from the R master sorcerer, Bob Rudis. This package called ggalt displays lots of alternative geometries and statistical transformations addressed to ggplot2. For example, we could name stat_bkde() and stat_bkde2d(), which use alternative functions to create kernel density estimates (respectively for one and two dimensions).

This recipe demonstrates how to use ggalt to craft these two kinds of visuals with the help of the car::Salaries package. The recipe also demonstrates how to easily craft lollipop plots using geom_lollipop(). This last example uses the car::Migration dataset.

Getting Ready

Both car and ggalt packages can be obtained from CRAN:

if(!require(ggalt)){install.packages('ggalt')}
if(!require(car)){install.packages('car')}

With both packages installed we can go on.

How to do it...

While density estimates are drawn using the Salaries data frame, the lollipop plot uses Migration, both coming from the car...

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