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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

Automated calculations using the apply family of functions

In this section, you are going to learn about two very useful functions to apply an operation on the subsets of data. The two functions, tapply and apply, along with a few others, form a collection of functions called apply functions. The functions in the collection are used to apply (hence the name) a function we choose over subsets of an object, and then join the results to form a single object once again. The apply functions are a defining feature of R; they replace the necessity to write explicit loops in many common situations in data analysis, which makes the code shorter and more elegant.

Applying a function on separate parts of a vector

The tapply function is used to apply a function over different sections of a vector and then combine the results into a single object. To do this, we need to provide three arguments for the following three parameters:

  • Vector A, which the function will operate upon (X)
  • Vector B, which defines...
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