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Advanced Analytics with R and Tableau

You're reading from   Advanced Analytics with R and Tableau Advanced analytics using data classification, unsupervised learning and data visualization

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781786460110
Length 178 pages
Edition 1st Edition
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Authors (3):
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Roberto Rösler Roberto Rösler
Author Profile Icon Roberto Rösler
Roberto Rösler
Ruben Oliva Ramos Ruben Oliva Ramos
Author Profile Icon Ruben Oliva Ramos
Ruben Oliva Ramos
Jen Stirrup Jen Stirrup
Author Profile Icon Jen Stirrup
Jen Stirrup
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Table of Contents (10) Chapters Close

Preface 1. Advanced Analytics with R and Tableau FREE CHAPTER 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

For loops and vectorization in R

Specifically, we will look at the constructs involved in loops. Note, however, that it is more efficient to use vectorized operations rather than loops, because R is vector-based. We investigate loops here, because they are a good first step in understanding how R works, and then we can optimize this understanding by focusing on vectorized alternatives that are more efficient.

More information about control flows can be obtained by executing the command at the command line:

Help?Control

The control flow commands take decisions and make decisions between alternative actions. The main constructs are for, while, and repeat.

For loops

Let's look at a for loop in more detail. For this exercise, we will use the Fisher iris dataset, which is installed along with R by default. We are going to produce summary statistics for each species of iris in the dataset.

You can see some of the iris data by typing in the following command at the command prompt:

head(iris)

We...

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