Search icon CANCEL
Subscription
0
Cart icon
Cart
Close icon
You have no products in your basket yet
Save more on your purchases!
Savings automatically calculated. No voucher code required
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
R Data Visualization Cookbook

You're reading from  R Data Visualization Cookbook

Product type Book
Published in Jan 2015
Publisher
ISBN-13 9781783989508
Pages 236 pages
Edition 1st Edition
Languages
Toc

Table of Contents (17) Chapters close

R Data Visualization Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. A Simple Guide to R 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

Writing a function in R


Most of the tasks in R are performed using functions. A function in R has the same utility as functions in Arithmetic.

Getting ready

In order to write a simple function in R, we must first open a new R script by navigating to File | New file.

How to do it…

We write a very simple function that accepts two values and adds them together. Copy and paste the code in the new blank R script:

add = function (x,y){
  x+y
}

How it works…

A function in R should be defined by function(). Once we define our function, we need to save it as a .r file. Note that the name of the file should be the same as the function; hence we save our function with name add.r.

In order to use the add() function in the R command window, we need to source the file by using the source() function as follows:

source('<your path>/add.R')

Now, we can type add(2,15) in the R command window. You get 17 printed as an output.

The function itself takes two arguments in our recipe but, in reality, it can take many arguments. Anything defined inside curly braces gets executed when we call add(). In our case, we request the user to input two variables, and the output is a simple sum.

See also

  • Functions can be helpful in performing repetitive tasks such as generating plots or perform complicated calculations. Felix Schönbrodt has implemented visually weighted watercolor plots in R using a function on his blog at http://www.nicebread.de/visually-weighted-watercolor-plots-new-variants-please-vote/.

  • We can generate similar plots simply by copying the function created by Felix in our R session and executing it. The plotting function created by Felix also provides users with different ways in which the R function's ability could be leveraged to perform repetitive tasks.

You have been reading a chapter from
R Data Visualization Cookbook
Published in: Jan 2015 Publisher: ISBN-13: 9781783989508
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €14.99/month. Cancel anytime}