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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

Drawing facets using plotly


By its version 0.4.3, ggvis did not support facets, but at the same time, plotly  kind did. As the current chapter had stressed, plotly is able to coerce several ggplot facets properly. This recipe will show you how plotly can be used to brew facets from scratch using subplot() function. Drawing nice facets from scratch using plotly is not an easy task. Also, facets breed this way can be seem more as embed graphs though. It's very code-demanding and lots of data manipulation may be required. Yet there is this possibility and some nuts and bolts to go through. Plotting separated titles is very tricky as this example shows.

This recipe will adopt the Titanic context and handle a simple comparison between child and adult survivals, similar to the plot displayed by the recipe, Creating a faceted bar graph. Even if a very simple facet is being created here, this example can be extended and generalized to create more complicated ones. Also think carefully about creating...

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