Interactivity Continued

Content for Wednesday, November 30, 2022

This week is a bit of a departure from some of the ‘strictly GIS’ components of the course to explore some more creative approaches to data (spatial or otherwise) visualization. Using the idea of the storymap as motivation, we’ll take a look at some of the growing list of tools that R provides to integrate high-powered data analysis with interactive web applications into an intuitive, visually appealing webpage. As publicly funded scientists are increasingly called upon to make their research available to the public, these tools provide a valuable framework for moving your research beyond the university walls or outside of paywalled journals.

Resources

  • The Arranging Views chapter in (Sievert 2020) introduces flexdashboards and describes how plotly and other htmlwidgets can be integrated for a complete data-plot-story pipeline.

  • This blogpost by Zev Ross provides a very thorough introduction to shiny, it’s syntax, and the ideas of reactivity in interactive applications.

  • The shiny and flexdashboard pages at RStudio have lots of examples of cool applications of both products, tutorials, and cheatsheets. There is a lot more to them than we’ll be able to cover in this class, but there’s plenty of additional material on both webpages.

Objectives

By the end of today you should be able to:

  • Build simple interactive graphics with ggplot and plotly

  • Describe the basic structure of shiny apps

  • Begin incorporating interactive elements into stories

Slides

The slides for today’s lesson are available online as an HTML file. Use the buttons below to open the slides either as an interactive website or as a static PDF (for printing or storing for later). You can also click in the slides below and navigate through them with your left and right arrow keys.

View all slides in new window Download PDF of all slides

References

Sievert, C. 2020. Interactive web-based data visualization with r, plotly, and shiny. CRC Press.