Interactive Data Analysis with R, Plotly, and Shiny

Montréal (March 3-4), Boston (April 14-15), Washington D.C. (June 9-10), New York City (Nov 17-18)

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Workshop Overview

This workshop is highly interactive and attendees are expected to participate in hands-on exercises designed to reinforce the lecture material. To participate in the exercises, attendees should bring a laptop and make sure they can open this RStudio Cloud project before the workshop begins.

By the end of this workshop, you will be able to rapidly pose queries about data with interactive web graphics made using the R package plotly. You will also learn about useful tidyverse tools and concepts such as tidy data, data reshaping data, and the split-apply-combine technique. Though it would be beneficial to have some prior knowledge of R and ggplot2, we do not require it, and as such, we avoid assuming pre-existing knowledge as much as possible. Furthermore, this workshop is not designed to make you an R programming expert – it’s designed to get you doing powerful things quickly regardless of your experience with R or programming in general.

Carson Sievert

Carson Sievert is a freelance data scientist developing software and creating products that make data analysis more accessible, appealing, and efficient. During his Ph.D., he became the maintainer of the R package plotly and was recognized with the John Chambers Statistical Software Award. He is also author and maintainer of numerous other R packages including LDAvis, animint, pitchRx, and rdom.

Day 1 outline

 

An overview of plotly for R

  • Motivating examples and demos
  • How does it all fit together (htmlwidgets for R, plotly.js, SVG vs WebGL, etc)?
  • Mapping data to visuals (theory and practice)
  • Tips for learning more, debugging, and generally getting “un-stuck”

Data wrangling for visualization

  • Reshaping with tidyr, manipulation with dplyr
  • The data-plot-pipeline

Interactive maps made simple

  • scattermapbox
  • scattergeo
  • sf and geom_sf()

Day 2 outline

 

Animations via plot_ly() and ggplotly()

Linking multiple views via crosstalk

  • Highlighting via direct/indirect manipulation
  • Filtering via indirect manipulation

Getting the most of out plotly in shiny

  • Quick intro to shiny
  • Accessing/responding to plotly events in shiny
  • Efficient updates via plotlyProxy()

Arrange a Private Workshop where we meet with just your team.

“Carson has done a great job bringing plotly to the R community. The workshop was great for both those newer to plotly and more advanced users who got to learn about the newer, cutting edge functionality that was available. There were lots of opportunities for hands-on examples, which was really helpful!”
~Leigh Alexander, PhD. Scientist at SomaLogic
“Dr. Sievert is the expert on all things related to R and plotly. His workshop provided me with extensive and invaluable new skills that are required to be successful when creating data analytics in R. All data scientists, even the masters, could benefit from attending Carson’s workshop.”
~Andrew Kosydar, PhD. Sandia National Labs
“Carson’s Plotly course changed the way I think about visualizing data with R. His tools make interactive visualization across objects viable and his class provided me with the fundamentals to walk away feeling comfortable building interactive dashboards that I can put in front of clients. Further, he was able to help me understand the underlying mechanics so I can extend the concepts to other visualization libraries with the appropriate structures. His class was well organized, he does a great job presenting the material, and his knowledge and experience in the area of data visualization is humbling. I will definitely look for his classes in the future, thanks Carson for a great experience!”
~Mark Druffel. Consultant at Propeller