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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

Creating a faceted bar graph


This recipe will create a faceted bar graph using the Titanic dataset. This particular set comes from base R packages, but it's not a data frame. To plot this data using ggplot2, we first need to to coerce this object to a data frame. Recipe will introduce the faceting function.

The goal here is to make a plot showing how many people survived and how many died in the Titanic tragedy. Facets are used to split this analysis both by gender (male and female) and age range (child or adult). There are no prior requirements other than ggplot2 and plotly packages installed.

How to do it...

This section shows you how to create a faceted bar graph:

  1.  Coerce the Titanic table to the data frame type:
> data_titanic <- as.data.frame(Titanic)
  1. Load ggplot2, design a bar graph, and add the facets using face_grid() function:
> library(ggplot2)
> bar <- ggplot(data_titanic, aes(x = Survived)) + 
   geom_bar(aes(fill = Survived, weight = Freq)) + 
   facet_grid(Sex ~ Age...
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