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Applied Data Visualization with R and ggplot2

You're reading from   Applied Data Visualization with R and ggplot2 Create useful, elaborate, and visually appealing plots

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Product type Paperback
Published in Sep 2018
Publisher
ISBN-13 9781789612158
Length 140 pages
Edition 1st Edition
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Author (1):
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Dr. Tania Moulik Dr. Tania Moulik
Author Profile Icon Dr. Tania Moulik
Dr. Tania Moulik
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Changing Styles and Colors

Aside from faceting, we can also produce a color differentiated plot. It can be advantageous to use a color differentiated plot when the shapes are very similar and there is some overlap. To see small differences, it is useful to use colors. For example, we can plot the Electricity consumption versus GDP by using different colors or shapes for the countries.

Using Different Colors to Group Points by a Variable

In this section, we'll produce a color differentiated scatter plot with respect to a third variable. Let's begin by implementing the following steps:

  1. Choose a subset of dataset 1 (gapminder) and select a few countries. Use the following subset command:
dfs <- subset(df,Country...
You have been reading a chapter from
Applied Data Visualization with R and ggplot2
Published in: Sep 2018
Publisher:
ISBN-13: 9781789612158
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