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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
Languages
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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 proportional stacked bar


If you have to make a stand about proportions, proportional stacked bar graphs may be the way to go. Note that it works better when there are only few categories to analyze. If you have two continuous variables to display at both axes and still want to reinforce how proportions are changing among categories you shall call for proportional area plots instead.

Sticking with car::Salaries data frame, this recipes is demonstrating how to craft proportional stacked bar graphs. Codes are covering  plots made with ggplot2, ggvis and plotly.

Getting ready

The only requirement that the recipes have the car , scales, and plyr packages installed. Try running the following code to check for them and install if they not there:

> if( !require(car)){ install.packages('car')}
> if( !require(plyr)){ install.packages('plyr')}
> if( !require(scales)){ install.packages('scales')}

To install a missing package, internet connection is required.

How to do it...

Proportional stacked...

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