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Advanced Analytics with R and Tableau

You're reading from  Advanced Analytics with R and Tableau

Product type Book
Published in Aug 2017
Publisher Packt
ISBN-13 9781786460110
Pages 178 pages
Edition 1st Edition
Languages
Authors (3):
Ruben Oliva Ramos Ruben Oliva Ramos
Profile icon Ruben Oliva Ramos
Jen Stirrup Jen Stirrup
Profile icon Jen Stirrup
Roberto Rösler Roberto Rösler
View More author details

Table of Contents (16) Chapters

Advanced Analytics with R and Tableau
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Advanced Analytics with R and Tableau 2. The Power of R 3. A Methodology for Advanced Analytics Using Tableau and R 4. Prediction with R and Tableau Using Regression 5. Classifying Data with Tableau 6. Advanced Analytics Using Clustering 7. Advanced Analytics with Unsupervised Learning 8. Interpreting Your Results for Your Audience Index

Creating your own function


There are a few important items to note about the creation of functions in R. Functions return a value. As a rule, functions return the value of the last expression in the function body.

Local variables are set temporarily for the duration of the function call, and they are cleared when the function exists.

Function parameters affect the function locally, and the original caller's value is not changed.

You can create your own functions using the function keyword. Here is an example of a function created from an earlier piece of code:

myfunction <- function(x, y, z) tapply(x,y,z)

So, if we take our earlier example, we could change it so that it uses functions:

output <-
  data.frame(MinPetalLength=myfunction(iris$Petal.Length,iris$Species,max),
             MaxPetalLength=myfunction(iris$Petal.Length,iris$Species,max),
             MeanPetalLength=myfunction(iris$Petal.Length,iris$Species,mean),
             NumberofSamples=myfunction(iris$Petal.Length,iris$Species...
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