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Learning R for Geospatial Analysis

You're reading from   Learning R for Geospatial Analysis Leverage the power of R to elegantly manage crucial geospatial analysis tasks

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Product type Paperback
Published in Dec 2014
Publisher Packt
ISBN-13 9781783984367
Length 364 pages
Edition 1st Edition
Languages
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Author (1):
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Michael Dorman Michael Dorman
Author Profile Icon Michael Dorman
Michael Dorman
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Table of Contents (13) Chapters Close

Preface 1. The R Environment FREE CHAPTER 2. Working with Vectors and Time Series 3. Working with Tables 4. Working with Rasters 5. Working with Points, Lines, and Polygons 6. Modifying Rasters and Analyzing Raster Time Series 7. Combining Vector and Raster Datasets 8. Spatial Interpolation of Point Data 9. Advanced Visualization of Spatial Data A. External Datasets Used in Examples
B. Cited References
Index

Chapter 2. Working with Vectors and Time Series

In this chapter, we are going to cover the basic data structure in R—a vector. Understanding vectors is the foundation for all the subsequent chapters. You will learn how to perform efficient operations on numeric and logical vectors and how to create subsets. After this, you will learn how to write custom functions in order to expand and customize R's capabilities. Working with dates and time series and the use of graphical functions are introduced at the end of this chapter.

In this chapter, we'll cover the following topics:

  • Creating, saving, and examining the three main types of vectors
  • The principles of performing operations on vectors in R
  • Using functions that have more than one argument
  • Creating subsets of vectors
  • Dealing with missing values in vectors
  • Writing new functions
  • Working with dates
  • Displaying and saving graphical output
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