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Interactive Web-Based Data Visualization with R, plotly, and shiny

Interactive Web-Based Data Visualization with R, plotly, and shiny

Authors
Publisher Taylor & Francis Ltd
Year 21/01/2020
Pages 470
Version paperback
Readership level College/higher education
Language English
ISBN 9781138331457
Categories Probability & statistics, Computer science
$92.82 (with VAT)
412.65 PLN / €88.47 / £76.80
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Book description

The richly illustrated Interactive Web-Based Data Visualization with R, plotly, and shiny focuses on the process of programming interactive web graphics for multidimensional data analysis. It is written for the data analyst who wants to leverage the capabilities of interactive web graphics without having to learn web programming. Through many R code examples, you will learn how to tap the extensive functionality of these tools to enhance the presentation and exploration of data. By mastering these concepts and tools, you will impress your colleagues with your ability to quickly generate more informative, engaging, and reproducible interactive graphics using free and open source software that you can share over email, export to pdf, and more.


Key Features:








Convert static ggplot2 graphics to an interactive web-based form







Link, animate, and arrange multiple plots in standalone HTML from R







Embed, modify, and respond to plotly graphics in a shiny app







Learn best practices for visualizing continuous, discrete, and multivariate data







Learn numerous ways to visualize geo-spatial data





This book makes heavy use of plotly for graphical rendering, but you will also learn about other R packages that support different phases of a data science workflow, such as tidyr, dplyr, and tidyverse. Along the way, you will gain insight into best practices for visualization of high-dimensional data, statistical graphics, and graphical perception. The printed book is complemented by an interactive website where readers can view movies demonstrating the examples and interact with graphics. "Plotly is the most-downloaded interactive graphics system for R, and this book should help all plotly users-both new and experienced-understand more about plotly graphics. With this in mind, I feel that this book (once it makes its way to a final form) will have a wide appeal for a large swath of R users. This audience will include both statisticians and data scientists, and a wide range of education and experience levels, ranging from the novice student to the seasoned data scientist to the statistics faculty member...I suspect a book on plotly will be wildly successful."
~Adam Loy, Carleton College


"This book is well-written and well-structured. The potential readership of this book is those who would like to learn or master interactive data visualization with R, and I'm not aware of any competing books in this regard. Both novice R users and experts could find this book useful and learn about plotly more systematically. Data practitioners could obtain lots of practical advice on how to make their plotly applications more responsive and more aesthetically appealing. I would also recommend this book as the textbook for courses that focus on data visualisation using web technology."
~Earo Wang, Monash University





"This book fills a gap in the currently-available texts, providing information on making interactive graphics in R. I recently taught a course entitled 'Advanced Statistical Software,' and found it difficult to locate resources on plot.ly and shiny. As far as I know, this is the first book to really cover these topics. As with many other books published by Chapman and Hall, the availability of the website version of the book is extremely useful for the R community. I have already used materials from the web version, but if I were to teach this course again I would consider making the paper book a required text...Because Dr. Sievert wrote the plotly R package, he is clearly the world expert in the material. He also brings a wealth of general visualization knowledge to the book, which is full of rich references to other materials."
~Amelia McNamara, University of St. Thomas





"This text would be an excellent resource for an advanced (graduate level) data visualization course. I think it could also be very valuable in data journalism coursework, where interactivity is a powerful communication tool. The book is very clearly written, and there are plenty of examples to demonstrate the tools to the reader...I especially enjoyed that the author provides the reader with a link to an RStudio cloud environment with which to run all of the examples in the book on their own. I believe this is an essential piece to this and any other modern computing text."
~Sam Tyner


"Some sections of this book will be very useful for two classes I teach. One is introduction to data science where I teach about JSON and HTML data and how to display them. The second course is a data visualization course where I teach interactive visualization...Currently, I am recommending several books. This book will certainly be an addition, in the sense that it provides detailed materials on interactive visualization."
~Mahbubul Majumder, University of Nebraska

Interactive Web-Based Data Visualization with R, plotly, and shiny

Table of contents

Introduction





Why interactive web graphics from R?





What you will learn





What you won't learn (much of)





Web technologies





djs





ggplot





Graphical data analysis





Data visualization best practices





Prerequisites





Run code examples





Getting help and learning more





Acknowledgements





Colophon











I Creating views











Overview





Intro to plot_ly()





Intro to plotlyjs





Intro to ggplotly()











Scattered foundations





Markers





Alpha blending





Colors





Symbols





Stroke and span





Size





Dotplots & error bars





Lines





Linetypes





Segments





Density plots





Parallel Coordinates





Polygons





Ribbons











Maps





Integrated maps





Overview





Choropleths





Custom maps





Simple features (sf)





Cartograms











Bars & histograms





Multiple numeric distributions





Multiple discrete distributions











Boxplots











D frequencies





Rectangular binning in plotlyjs





Rectangular binning in R





Categorical axes











D charts





Markers





Paths





Lines





Axes





Surfaces











II Publishing views











Introduction











Saving and embedding HTML











Exporting static images





With code





From a browser





Sizing exports











Editing views for publishing











III Combining multiple views











Arranging views





Arranging plotly objects





Recursive subplots





Other approaches & applications





Arranging htmlwidgets





Flexdashboard





Bootstrap grid layout





CSS flexbox





Arranging many views











Animating views





Animation API





Animation support











IV Linking multiple views











Introduction











Client-side linking





Graphical queries





Highlight versus filter events





Linking animated views





Examples





Querying facetted charts





Statistical queries





Statistical queries with ggplotly()





Geo-spatial queries





Linking with other htmlwidgets





Generalized pairs plots





vi Contents





Querying diagnostic plots





Limitations











Server-side linking with shiny





Embedding plotly in shiny





Your first shiny app





Hiding and redrawing on resize





Leveraging plotly input events





Dragging events





D events





Edit events





Relayout vs restyle events





Scoping events





Event priority





Handling discrete axes





Accumulating and managing event data





Improving performance





Partial plotly updates





Partial update examples





Advanced applications





Drill-down





Cross-filter





A draggable brush





Discussion











V Event handling in JavaScript











Introduction











Working with JSON





Assignment, subsetting, and iteration





Mapping R to JSON











Adding custom event handlers











Supplying custom data











Leveraging web technologies from R





Web infrastructure





Modern JS & React











VI Various special topics











Is plotly free & secure?











Improving performance











Controlling tooltips





plot_ly() tooltips





ggplotly() tooltips





Styling











Control the modebar





Remove the entire modebar





Remove the plotly logo





Remove modebar buttons by name





Add custom modebar buttons





Control image downloads











Working with colors











Working with symbols and glyphs











Embedding images











Language support











LaTeX rendering





MathJax caveats











The data-plot-pipeline











Improving ggplotly()





Modifying layout





Modifying data





Leveraging statistical output











Translating custom ggplot geoms

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