Mastering Shiny: Build Interactive Apps, Reports, and Dashboards Powered by R

Master the Shiny web framework--and take your R skills to a whole new level. By letting you...
¥18,596 JPY
¥18,596 JPY
SKU: 9781492047384
Product Type: Books
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Author: Hadley Wickham
Format: Paperback
Language: English
Subtotal: ¥18,596
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Mastering Shiny: Build Interactive Apps, Reports, and Dashboards Powered by R by Wickham, Hadley

Mastering Shiny: Build Interactive Apps, Reports, and Dashboards Powered by R

¥18,596

Mastering Shiny: Build Interactive Apps, Reports, and Dashboards Powered by R

¥18,596
Author: Hadley Wickham
Format: Paperback
Language: English

Master the Shiny web framework--and take your R skills to a whole new level. By letting you move beyond static reports, Shiny helps you create fully interactive web apps for data analyses. Users will be able to jump between datasets, explore different subsets or facets of the data, 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 rich web apps from R. This in-depth guide provides a learning path that you can follow with confidence, as you go from a Shiny beginner to an expert developer who can write large, complex apps that are maintainable and performant.

  • Get started: Discover how the major pieces of a Shiny app fit together
  • Put Shiny in action: Explore Shiny functionality with a focus on code samples, example apps, and useful techniques
  • Master reactivity: Go deep into the theory and practice of reactive programming and examine reactive graph components
  • Apply best practices: Examine useful techniques for making your Shiny apps work well in production


Author: Hadley Wickham
Publisher: O'Reilly Media
Published: 05/25/2021
Pages: 372
Binding Type: Paperback
Weight: 1.75lbs
Size: 9.17h x 7.01w x 1.01d
ISBN: 9781492047384

About the Author

Hadley Wickham is an Assistant Professor and the Dobelman FamilyJunior Chair in Statistics at Rice University. He is an active memberof the R community, has written and contributed to over 30 R packages, and won the John Chambers Award for Statistical Computing for his work developing tools for data reshaping and visualization. His research focuses on how to make data analysis better, faster and easier, with a particular emphasis on the use of visualization to better understand data and models.


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