Lab 3F: Maps
Lab 3F - Maps
Directions: Follow along with the slides and answer the questions in bold font in your journal.
Informative and Fun!
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Maps are some of the most interesting plots to make because the info represents:
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Where we live.
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Where we go.
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Places that interest us.
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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.
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In this lab, we'll use
R
to create an interactive map of themtns
data we scraped in Lab 3E.
Getting ready to map
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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.
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You'll find it very helpful, for this lab, to write all of the commands, including the
load_lab(23)
command, as anR
script.– This way you can edit the code that builds the map and quickly reload the lab.
Load your data!
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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")
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Didn't finish the lab or save the data file? Ask a friend to share it!
Build a Basic Map
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Let's start by building a basic map!
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Use the
leaflet()
function and themtns
data to create theleaf
that we can use for mapping.mtns_leaf <- leaflet(____)
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Then, insert
mtns_leaf
into theaddTiles()
function and assign the output the namemtns_map
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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
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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 = ~____)
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Supply the
peak
variable, in a similar way as we supplied thelat
andlong
variables, to thepopup
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
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Our current map looks pretty good, but what if we wanted to add some colors to our plot?
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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(____))
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Now that we've added a new variable, we need to re-build
mtns_leaf
andmtns_map
to use it.– Create
mtns_leaf
andmtns_map
as you did before.– Then change
addMarkers
toaddCircleMarkers
and keep all of the arguments the same.
Showing off our colors
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To add the colors to our plot, use the
addCircleMarkers
like before but this time includecolor = ~state_colors
as an argument. -
It's hard to know just what the different colors mean so let's add a legend.
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First, assign the map with the circle markers as
mtns_map
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Then, fill in the blanks below to place a legend in the top-right hand corner.
addLegend(_, colors = ~unique(_), labels = ~unique(____)).
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