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Learning Shiny

Learning Shiny

By : Hernan Resnizky
2.9 (7)
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Learning Shiny

Learning Shiny

2.9 (7)
By: Hernan Resnizky

Overview of this book

Make the most of R’s dynamic capabilities and implement web applications with Shiny About This Book Present interactive data visualizations in R within the Shiny framework Construct web dashboards in a simple, intuitive, but fully flexible environment Apply your skills to create a real-world web application with this step-by-step guide Who This Book Is For If you are a data scientist who needs a platform to show your results to a broader audience in an attractive and visual way, or a web developer with no prior experience in R or Shiny, this is the book for you. What You Will Learn Comprehend many useful functions, such as lapply and apply, to process data in R Write and structure different files to create a basic dashboard Develop graphics in R using popular graphical libraries such as ggplot2 and GoogleVis Mount a dashboard on a Linux Server Integrate Shiny with non-R-native visualization, such as D3.js Design and build a web application In Detail R is nowadays one of the most used tools in data science. However, along with Shiny, it is also gaining territory in the web application world, due to its simplicity and flexibility. Shiny is a framework that enables the creation of interactive visualizations written entirely in R and can be displayed in almost any ordinary web browser. It is a package from RStudio, which is an IDE for R. From the fundamentals of R to the administration of multi-concurrent, fully customized web applications, this book explains how to achieve your desired web application in an easy and gradual way. You will start by learning about the fundamentals of R, and will move on to looking at simple and practical examples. These examples will enable you to grasp many useful tools that will assist you in solving the usual problems that can be faced when developing data visualizations. You will then walk through the integration of Shiny with R in general and view the different visualization possibilities out there. Finally, you will put your skills to the test and create your first web application! Style and approach This is a comprehensive, step-by-step guide that will allow you to learn and make full use of R and Shiny’s capabilities in a gradual way, together with clear, applied examples.
Table of Contents (13 chapters)
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1
1. Introducing R, RStudio, and Shiny
12
Index

grep and regular expressions

grep() in R works exactly as it does in every UNIX-based operating system. Closely related to grep() (in fact, R groups them together and treats them as a group of functions), various other functions can be found. In this section, only grepl(), gregexpr(), and gsub() will be examined. One thing that all these functions have in common is that they perform an action based on a string pattern. The description of the functions are as follows:

  • grep(): This returns the indexes of the elements in a vector that match a string pattern. If the value is set to TRUE, it returns the values instead of the indexes.
  • grepl(): This returns a logical vector of the same length as the input vector, denoting whether the sought pattern was found or not.
  • gsub(): This substitutes the pattern for the replacement argument in the specified vector.
  • gregexpr(): This returns a list consisting of the vectors of starting positions that specify where the pattern was matched in the text in addition...

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