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OverviewMaster the Shiny web framework-and take your R skills to a whole new level. Shiny helps you create fully interactive web apps for data analyses by letting you move beyond static reports, tables, and graphs. Your users will be able to jump between datasets, explore different subsets, run models with parameter values of their choosing, customize visualizations, and much more. Hadley Wickham from RStudio shows data scientists, data analysts, statisticians, and scientific researchers with no knowledge of HTML, CSS, or JavaScript how to create complex Shiny apps. Shiny is easy to learn, but even intermediate users often wonder what they've missed. This in-depth introduction provides a learning path that you can follow with confidence. Getting started: Begin with a tutorial-style exploration of the basics Shiny in action: Explore Shiny functionality with a focus on code samples and example apps Best practices: Learn techniques for managing complexity and ensuring correctness, and explore ways to measure and improve your Shiny app's scalability Mastering reactivity: Learn the underlying theory of reactivity to improve your ability to reason about complex Shiny apps Full Product DetailsAuthor: Hadley WickhamPublisher: O'Reilly Media Imprint: O'Reilly Media ISBN: 9781492047384ISBN 10: 1492047384 Pages: 450 Publication Date: 14 May 2021 Audience: Professional and scholarly , College/higher education , General/trade , Professional & Vocational , Postgraduate, Research & Scholarly Format: Paperback Publisher's Status: Active Availability: In Print ![]() This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsReviewsAuthor InformationHadley is Chief Scientist at RStudio, winner of the 2019 COPSS award, and a member of the R Foundation. He builds tools (both computational and cognitive) to make data science easier, faster, and more fun. His work includes packages for data science (like the tidyverse, which includes ggplot2, dplyr, and tidyr)and principled software development (e.g. roxygen2, testthat, and pkgdown). He is also a writer, educator, and speaker promoting the use of R for data science. Tab Content 6Author Website:Countries AvailableAll regions |