Let's do some Logging

Let's look at the quartiles of mean zip code incomes in NC.

summary(high_inc$mean_income)

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  55947   62380   71655   83682   90695  550849

The range is nearly $500,000! However, the median is much closer to the min than to the max, indicating a right-skew. Since the mean income variable contains exceptionally large values, the continuous color gradient is not very helpful. Log transforming a right-skewed variable pulls large values closer to the mean and yields a more symmetrically distributed variable.

Log transforming the mean income on our map increases the variation in the color gradient across the high income zip codes and enables better visualization of the distribution of mean income across the state.

This exercise is part of the course

Interactive Maps with leaflet in R

View Course

Exercise instructions

Create a logged version of the nc_pal color palette.
Apply the logged color palette to the leaflet map.
Comment out the map tile from the leaflet map to more easily visualize the variation in mean income (add # without a space prior to the function that adds the map tile).

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Use the log function to create a new version of nc_pal
nc_pal <- colorNumeric("YlGn", domain = ___(high_inc@data$mean_income))

# comment out the map tile
high_inc %>%
  leaflet() %>%
  ___addProviderTiles("CartoDB") %>%
  # apply the new nc_pal to the map
  addPolygons(weight = 1, color = ~nc_pal(___(mean_income)), fillOpacity = 1,
              label = ~paste0("Mean Income: ", dollar(mean_income)),
              highlightOptions = highlightOptions(weight = 5, color = "white", bringToFront = TRUE))

Edit and Run Code

Interactive Maps with leaflet in R

BeginnerSkill Level

4.8+

44 reviews

Chapter 1 will introduce students to the htmlwidgets package and the leaflet package. Following this introduction, students will build their first interactive web map using leaflet. Through the process of creating this first map students will be introduced to many of the core features of the leaflet package, including adding different map tiles, setting the center point and zoom level, plotting single points based on latitude and longitude coordinates, and storing leaflet maps as objects. Chapter 1 will conclude with students geocoding DataCamp’s headquarters, and creating a leaflet map that plots the headquarters and displays a popup describing the location.

Exercise 1: Introduction to leaflet Exercise 2: Loading the leaflet Library Exercise 3: Creating an Interactive Web Map Exercise 4: Map Tiles Exercise 5: Provider Tiles Exercise 6: Adding a Custom Map Tile Exercise 7: Setting the Default Map View Exercise 8: A Map with a View I Exercise 9: A Map with a Narrower View Exercise 10: Plotting DataCamp HQ Exercise 11: Mark it Exercise 12: Adding Popups and Storing your Map

In Chapter 4 students will learn to map polygons, which can be used to define geographic regions (e.g., zip codes, states, countries, etc.). Chapter 4 will start by plotting the zip codes in North Carolina that fall in the top quartile of mean family incomes. Students will learn to customize the polygons with color palettes and labels. Chapter 4 will conclude with adding a new layer to the map of every college in America that displays every zip code with a mean income of $200,000 or more during the 2015 tax year. Through the process of mapping zip codes students will learn about spatial data generally, geoJSON data, the @ symbol, and the addPolygons() function. Furthermore, students will have an opportunity to practice applying many of the options that they learned about in the previous chapters, such as popups and labels, as well as new ways to customize their maps, such as the highlight option in addPolygons().

Exercise 1: Spatial Data Exercise 2: Introduction to Spatial Data Exercise 3: Exploring Spatial Data Exercise 4: Joining Spatial Data Exercise 5: Mapping Polygons Exercise 6: addPolygons() Function Exercise 7: NC High Income Zips Exercise 8: addPolygon() Options Exercise 9: Let's do some Logging

Current Exercise

Exercise 10: Putting it All Together Exercise 11: Wealthiest Zip Codes in America Exercise 12: Final Map Exercise 13: Thank you!