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

This book describes interactive data visualization using the R package plotly. It focuses on tools and techniques that data analysts should find useful for asking follow-up questions from their data using interactive web graphics. A basic understanding of R is assumed.

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