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RStudio for R Statistical Computing Cookbook

You're reading from   RStudio for R Statistical Computing Cookbook Over 50 practical and useful recipes to help you perform data analysis with R by unleashing every native RStudio feature

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Product type Paperback
Published in Apr 2016
Publisher
ISBN-13 9781784391034
Length 246 pages
Edition 1st Edition
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Author (1):
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Andrea Cirillo Andrea Cirillo
Author Profile Icon Andrea Cirillo
Andrea Cirillo
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Table of Contents (10) Chapters Close

Preface 1. Acquiring Data for Your Project 2. Preparing for Analysis – Data Cleansing and Manipulation FREE CHAPTER 3. Basic Visualization Techniques 4. Advanced and Interactive Visualization 5. Power Programming with R 6. Domain-specific Applications 7. Developing Static Reports 8. Dynamic Reporting and Web Application Development Index

Looking at your data using the plot() function


The plot() function is one of most powerful functions in base R. The main point of using the plot() function is that it will always try to print out a representation of your data. It basically tries to figure out which kind of representation is the best, based on the data type. This will let you easily and quickly get a first view of the data you are working with.

Behind the scenes, the power of the plot() function comes from being packed with a number of methods developed for specific types of object.

So, when an object is passed as an argument to plot(), it looks for the most appropriate method within the ones available and uses it to represent data stored within the object.

It is even possible to further expand the plot() function, as is regularly done in various packages, adding new methods for specific types of object by running setMethod() on it. This is out of the scope of this recipe, but you can find a good explanation in the R language...

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