R: Interactive Visualizations with htmlwidgets

Learn how to rapidly create rich, interactive data visualizations with R and htmlwidgets—packages that connect R to popular JavaScript libraries like Plotly, Leaflet, and DT.

Introduction

• Welcome
• What you should know
• Exercise files

1. Getting Started with htmlwidgets

• What are htmlwidgets?
• Where can you use htmlwidgets?
• Set up RStudio for htmlwidgets
• Install htmlwidget libraries
• Select the best htmlwidget
• Use the pipe operator (%>%)
• Prepare data to be tidy

2. Creating Interactive Maps with Leaflet

• What is the Leaflet library?
• Create interactive scattergeo maps
• Change map styles in Leaflet
• Prepare data for a choropleth plot
• Create interactive choropleth maps
• Create interactive geolines maps
• Add legends to Leaflet maps
• Extract click information from Leaflet

3. Creating Interactive Charts with Plotly

• What is the Plotly library?
• Make ggplot2 interactive using Plotly
• Create interactive stacked bar charts
• Interactive scatter, line, and bubble charts with Leaflet
• Create interactive maps
• Specify custom colors
• Customize tooltips
• Combine multiple charts
• Extract click information from Plotly

4. Creating Interactive Charts with Highcharter

• What is the Highcharter library?
• Create interactive stacked bar charts
• Create interactive scatter charts and bubble charts
• Create interactive time series
• Create interactive treemaps
• Create interactive choropleth maps
• Specify your own colors
• Modify tooltips in Highcharter
• Extract click information from Highcharter

5. Creating Interactive Networks with visNetwork

• What is the visNetwork library?
• Create basic network diagrams
• Style visNetwork graph
• Use visNetwork with igraph
• Choose graph layouts and embeddings
• Cluster nodes in visNetwork using groups
• Add legends to visNetwork
• Extract click information from visNetwork

6. Creating Interactive Tables

• What is the DT library?
• Create interactive data tables with DT
• Format columns and data
• Design responsive (mobile-ready) tables
• Allow users to download data
• Extract click information from data tables

Conclusion

• Next steps