Book Image

Spatial Analytics with ArcGIS

By : Eric Pimpler
Book Image

Spatial Analytics with ArcGIS

By: Eric Pimpler

Overview of this book

Spatial statistics has the potential to provide insight that is not otherwise available through traditional GIS tools. This book is designed to introduce you to the use of spatial statistics so you can solve complex geographic analysis. The book begins by introducing you to the many spatial statistics tools available in ArcGIS. You will learn how to analyze patterns, map clusters, and model spatial relationships with these tools. Further on, you will explore how to extend the spatial statistics tools currently available in ArcGIS, and use the R programming language to create custom tools in ArcGIS through the ArcGIS Bridge using real-world examples. At the end of the book, you will be presented with two exciting case studies where you will be able to practically apply all your learning to analyze and gain insights into real estate data.
Table of Contents (16 chapters)
Title Page
About the Author
About the Reviewer
Customer Feedback

R data types

There are many types of data that can be assigned to variables in R. The most basic types are characters, numbers, and logicals. Characters, also known as strings, are a sequence of characters surrounded by quotes. Numbers are exactly what you'd expect. Numeric data types can be any type of number. Logical data types are Boolean values of either true or false. The true and false values can include any of the iterations from the following code example:

    c('T', 'True', 'TRUE', 'true') 

There are also a number of data classes, which are structures used to hold multiple values. These include vectors, matrices, data frames, factors, and lists. We'll examine each of these data types.



In R, a vector is a sequence of data elements that have the same data type. To create a vector in R, you call the c() method and pass in a list of values of the same type. Several examples have been provided in the following code: