Informative and Fun!

• Maps are some of the most interesting plots to make because the info represents:
  • Where we live.
  • Where we go.
  • Places that interest us.
• Maps are also helpful to display geographic information.
  • John Snow (the physician, not the character from Game of Thrones…) once famously used a map to discover how cholera was transmitted.
• In this lab, we’ll use R to create an interactive map of the mtns data we scraped in Lab 3E.

Getting ready to map

• The map we’ll be creating will end up in RStudio’s Viewer pane.
  • Which means you’ll need to alternate between building the map and loading the lab.
• You’ll find it very helpful, for this lab, to write all of the commands, including the load_lab(23) command, as an R script.
  • This way you can edit the code that builds the map and quickly reload the lab.

Load your data!

• In Lab 3E you created a dataset. Load it into Rstudio now by filling in the blank with the file name of the data.

load("___.Rda")

• Didn’t finish the lab or save the data file? Ask a friend to share it!

Build a Basic Map

• Let’s start by building a basic map!
• Use the leaflet() function and the mtns data to create the leaf that we can use for mapping.

mtns_leaf <- leaflet(____)

• Then, insert mtns_leaf into the addTiles() function and assign the output the name mtns_map
• Run mtns_map in the console to look at your basic map with no data displayed.
  • Be sure to try clicking on the map to pan and zoom.

Including our data

• Now we can add markers for the locations of the mountains using the addMarkers() function.
  • Fill in the blanks below with the basic map we’ve created and the values for latitude and longitude.

addMarkers(map = ____, lng = ~____, lat = ~____)

• Supply the peak variable, in a similar way as we supplied the lat and long variables, to the popup argument and include it in the code above.
  • Click on a marker within California and write down the name of the mountain you clicked on.

Colorize

• Our current map looks pretty good, but what if we wanted to add some colors to our plot?
• Fill in the blanks below to create a new variable that assigns a color to each mountain based on the state its located.

mtns <- mutate(____, state_colors = colorize(____))

• Now that we’ve added a new variable, we need to re-build mtns_leaf and mtns_map to use it.
  • Create mtns_leaf and mtns_map as you did before.
  • Then change addMarkers to addCircleMarkers and keep all of the arguments the same.

Showing off our colors

• To add the colors to our plot, use the addCircleMarkers like before but this time include color = ~state_colors as an argument.
• It’s hard to know just what the different colors mean so let’s add a legend.
  • First, assign the map with the circle markers as mtns_map.
  • Then, fill in the blanks below to place a legend in the top-right hand corner.

addLegend(____, colors = ~unique(____), labels = ~unique(____))