Book Image

Advanced Analytics with R and Tableau

By : Ruben Oliva Ramos, Jen Stirrup, Roberto Rösler
Book Image

Advanced Analytics with R and Tableau

By: Ruben Oliva Ramos, Jen Stirrup, Roberto Rösler

Overview of this book

Tableau and R offer accessible analytics by allowing a combination of easy-to-use data visualization along with industry-standard, robust statistical computation. Moving from data visualization into deeper, more advanced analytics? This book will intensify data skills for data viz-savvy users who want to move into analytics and data science in order to enhance their businesses by harnessing the analytical power of R and the stunning visualization capabilities of Tableau. Readers will come across a wide range of machine learning algorithms and learn how descriptive, prescriptive, predictive, and visually appealing analytical solutions can be designed with R and Tableau. In order to maximize learning, hands-on examples will ease the transition from being a data-savvy user to a data analyst using sound statistical tools to perform advanced analytics. By the end of this book, you will get to grips with advanced calculations in R and Tableau for analytics and prediction with the help of use cases and hands-on examples.
Table of Contents (16 chapters)
Advanced Analytics with R and Tableau
About the Authors
About the Reviewers
Customer Feedback

Finding clusters in data

Cluster analysis partitions marks in the view into clusters, where the marks within each cluster are more similar to one another than they are to marks in other clusters.

In Tableau Desktop, you create clusters by dragging Cluster from the Analytics pane and dropping it in the view. Now you will see that there is a statistical object. Here, Tableau places it on the Color shelf. Note that, if there is already a field on Color, Tableau moves that field to Detail and replaces it on Color with the clustering results.

Using clustering, Tableau assigns each mark to one of the clusters on the canvas. If any of the marks do not fit well in one of the clusters, then it is put into a not clustered cluster.

Clustering has its own dialog box, which allows you to add a cluster, or edit a cluster that exists already. The clustering dialog box gives you a lot of flexibility and control over the clustering process, whilst also giving you the ability to use suggested features. For example...