These sections take a data driven approach to understanding issues such as gentrification, investment in education, and variation in life expectancy around the world. In doing so, they demonstrate how to use programming skills to ask real data science questions about pressing topic areas. These include:

• Flight Delays: The dplyr In Action section uses the dplyr package to explore the nycflights13 data set, asking targetting questions about the 300,000+ flights that departed from New York City airports in 2013.
• Exploring Educational Statistics: The tidyr In Action section uses the tidyr package to explore variations in educational investment and attainment around the world using data from the World Bank.
• Finding Cuban Food in Seattle: The APIS In Action section uses the Yelp and Google Maps APIs to build a map of the highest rated Cuban Restaurants (in Seattle) on Yelp.
• Mapping Evictions in San Francisco: The ggplot2 In Action section uses the ggplot2 package to expose the intensity and distribution of evictions in the city of San Francisco.
• Visualizing Building Permits in Seattle: The Interactive Visualization In Action section uses various interactive visualization packages to explore new building permits in Seattle since 2010.
• Reporting on Life Expectancy: The R Markdown in Action section demonstrates the use of R Markdown to generate a website as a report on life expectancy data from the World Bank.
• Visualizing Fatal Police Shootings: The Shiny in Action section walk through building an interactive web application for exploring the volume of fatal police shootings in the United States (using the shiny package).