In jr-packages/jrSpatial: Jumping Rivers: Spatial Data Analysis using R

This practical is all about Methamphetamines! Yes, you read that right. Let's load in the data and necessary packages first

library("sf")
library("leaflet")
library("dplyr")
data(meth, package = "jrSpatial")

This is a dataset containing locations of real meth lab busts in the US. Take a look at the data to get a feel of it

head(meth)

Confession: I've made up the pounds_seized column. Unfortunately the DEA don't give that kind of stuff out. However I've checked a couple of records and the numbers are within reason!

1. Using leaflet, create an interactive map of the locations of the meth lab busts. Hint: Use addCircles()

leaflet(meth) %>% 
  addTiles() %>% 
  addCircles(data = meth)

1. Try adding the argument radius = ~pounds_seized to addCircles(). What happens?

leaflet(meth) %>% 
  addTiles() %>% 
  addCircles(data = meth, 
             radius = ~pounds_seized)
# radius of circles is bigger if more pounds of meth were seized

1. Try colouring the points by the pounds seized. To do this, use the colourNumeric()

pal_size = colorNumeric(palette = c("green", "red"), 
                        domain = meth$pounds_seized)

leaflet(meth) %>% 
  addTiles() %>% 
  addCircles(data = meth, 
             radius = ~pounds_seized, 
             color = ~pal_size(pounds_seized))

1. The problem with using colourNumeric() in this instance, is that the data is heavily skewed. If we look at a histogram of the pounds_seized, there isn't many meth labs that had over 1000 pounds of meth seized

library("ggplot2")
ggplot(meth, aes(x = pounds_seized)) + 
  geom_histogram()

1. We can set up a colour scheme such that we have discrete colours using colourBin(), like so

pal_size_bin = colorBin(palette = c("Green", "Yellow", "Orange", "Red"), 
                        domain = meth$pounds_seized, 
                        bins = c(0, 150, 300, 750, max(meth$pounds_seized)))

What colour scheme do you think we're using here?

# green - from 0 -150
# yellow - from 150 - 300
# orange - from 300 - 750
# red - from 750 - max value in pounds_seized

1. Use the new colour scheme to colour the points

leaflet(meth) %>% 
  addTiles() %>% 
  addCircles(data = meth, 
             radius = ~pounds_seized, 
             color = ~pal_size_bin(pounds_seized))

1. Add a legend to the plot

leaflet(meth) %>% 
  addTiles() %>% 
  addCircles(data = meth, 
             radius = ~pounds_seized, 
             color = ~pal_size_bin(pounds_seized)) %>% 
  addLegend(title = "Pounds seized",
            pal = pal_size_bin, 
            values = ~pounds_seized)

jr-packages/jrSpatial documentation built on Sept. 23, 2020, 2:31 p.m.