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R Data Visualization Cookbook

You're reading from   R Data Visualization Cookbook Over 80 recipes to analyze data and create stunning visualizations with R

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781783989508
Length 236 pages
Edition 1st Edition
Languages
Tools
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Toc

Table of Contents (12) Chapters Close

Preface 1. A Simple Guide to R FREE CHAPTER 2. Basic and Interactive Plots 3. Heat Maps and Dendrograms 4. Maps 5. The Pie Chart and Its Alternatives 6. Adding the Third Dimension 7. Data in Higher Dimensions 8. Visualizing Continuous Data 9. Visualizing Text and XKCD-style Plots 10. Creating Applications in R Index

Using par to beautify a plot in R

One quick and easy way to edit a plot is by generating the plot in R and then using Inkspace or any other software to edit it. We can save some valuable time if we know some basic edits that can be applied on a plot by setting them in a par() function. All the available options to edit a plot can be studied in detail by typing ?par in the command window.

How to do it…

In the following code, I have highlighted some commonly used parameters:

x=c(1:10)
y=c(1:10)
par(bg = "#646989", las = 1, col.lab = "black", col.axis = "white",bty = "n",cex.axis = 0.9,cex.lab= 1.5)
plot(x,y, pch = 20, xlab = "fake x data", ylab = "fake y data")

How it works…

Under the par() function, we have set the background color using the bg = argument. The las = argument changes the orientation of the labels. The col.lab and col.axis arguments are used to specify the color of the labels as well as the axis. The cex argument is used to specify the size of the labels and axis. The bty argument is used to specify the box style in R.

You have been reading a chapter from
R Data Visualization Cookbook
Published in: Jan 2015
Publisher:
ISBN-13: 9781783989508
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