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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

Data structures in R


The power of R resides in its ability to analyze data, and this ability is largely derived from its powerful data types. Fundamentally, R is a vectorized programming language. Data structures in R are constructed from vectors that are foundational. This means that R's operations are optimized to work with vectors.

Vector

The vector is a core component of R. It is a fundamental data type. Essentially, a vector is a data structure that contains an array where all of the values are the same type. For example, they could all be strings, or numbers. However, note that vectors cannot contain mixed data types.

R uses the c() function to take a list of items and turns them into a vector.

Lists

R contains two types of lists: a basic list, and a named list. A basic list is created using the list() operator. In a named list, every item in the list has a name as well as a value. named lists are a good mapping structure to help map data between R and Tableau. In R, lists are mapped using...

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