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Learning Shiny

You're reading from   Learning Shiny Make the most of R's dynamic capabilities and implement web applications with Shiny

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Product type Paperback
Published in Oct 2015
Publisher
ISBN-13 9781785280900
Length 246 pages
Edition 1st Edition
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Authors (2):
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Hernan Resnizky Hernan Resnizky
Author Profile Icon Hernan Resnizky
Hernan Resnizky
Hernan Resnizky Hernan Resnizky
Author Profile Icon Hernan Resnizky
Hernan Resnizky
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Toc

Table of Contents (13) Chapters Close

Preface 1. Introducing R, RStudio, and Shiny FREE CHAPTER 2. First Steps towards Programming in R 3. An Introduction to Data Processing in R 4. Shiny Structure – Reactivity Concepts 5. Shiny in Depth – A Deep Dive into Shiny's World 6. Using R's Visualization Alternatives in Shiny 7. Advanced Functions in Shiny 8. Shiny and HTML/JavaScript 9. Interactive Graphics in Shiny 10. Sharing Applications 11. From White Paper to a Full Application Index

The validate() function


The name of this function is definitely self-explanatory. In almost all the cases and except for extremely rare occasions, validate() is used along with need(), which is an easy wrapper that evaluates an expression in an extended way and produces an error message.

The expression evaluation performed by need() is extended with respect to normal condition evaluation in R, because it evaluates to False (and displays an error message) if the evaluation returns NA or the passed variable is empty. need() has two arguments for the error message: message and label. The first one is simply the text to be displayed and the second one is a character that can be used to be inserted dynamically into the error message. By default, message is paste(label, "must be provided"), so it expects the label argument. However, if message is passed, label is ignored. It is normally recommended to directly specify message.

Looking at Example 1 again, this could be a good need() statement to...

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