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.
Advanced Analytics with R and Tableau
Credits
www.PacktPub.com
Customer Feedback
Preface
Free Chapter
Advanced Analytics with R and Tableau
The Power of R
A Methodology for Advanced Analytics Using Tableau and R
Prediction with R and Tableau Using Regression
Classifying Data with Tableau
Index

Graphs

A graph is a type of data structure capable of handling networks. Graphs are widely used across various domains such as the following:

• Transportation: To find the shortest routes to travel between two places

• Communication-signaling networks: To optimize the network of inter-connected computers and systems

• Understanding relationships: To build relationship trees across families or organizations

• Hydrology: To perform flow regime simulation analysis of various fluids

Terminology and representations

A graph (G) is a network of vertices (V) interconnected using a set of edges (E). Let |V| represent the count of vertices and |E| represent the count of edges. The value of |E| lies in the range of 0 to |V|2 - |V|. Based on the directional edges, the graphs are classified as directed or undirected. In directed graphs, the edges are directed from one vertex towards the other, whereas in undirected graphs, each vertex has an equal probability of being directionally connected with the others. An...