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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

Writing modular code in RStudio

Using modular code is a best practice of computer programming. It basically involves dividing your code into independent pieces, where one module takes as an input the output of another one.

This recipe implements modular programming by leveraging the + function, which lets you execute R scripts from another script (or from the R terminal session itself) by collecting it in the local environment code output.

The advantage of modular code lies in the orthogonality principle: two pieces of code are orthogonal to each other if changing the first has no effect on the other.

Take, for instance, two pieces of code: the first one gives as an output a ZIP code from an address, and the second one takes that ZIP code and calculates the shipping cost for that ZIP code.

Until the first module gives a ZIP code as an output, the second module is totally unaware of how this code was defined. That is to say that any change in the first code will have no effect on the second...

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