The Starbucks data, compiled by Danny Kaplan, contains information about every Starbucks in the world at the time the data were collected.
# Get the map background information (images)
world <- get_stamenmap(
bbox = c(left = -180, bottom = -57, right = 179, top = 82.1),
maptype = "terrain",
zoom = 2
)
# In groups: What does each line of code do?
ggmap(world) + # Action: Creates the map "background"
geom_point( # Action:
data = Starbucks, # Action:
aes(x = Longitude, y = Latitude), # Action:
alpha = 0.3, # Action:
size = 0.2 # Action:
) +
theme_map() # Action:
Error in (function (msg) : TopologyException: Input geom 0 is invalid: Self-intersection at -163.87651444908798 -84.347832316374607
US_map2 <- get_stamenmap(
bbox = c(left = -132, bottom = 20, right = -65, top = 55),
maptype = "toner-lite",
zoom = 5
)
# Contour plot
ggmap(US_map2) + #Action: Set background map
geom_density_2d( #Action: Set glyph to be a 2d density contour
data = Starbucks, #Action: Pass Starbucks data to geom_density_2d
aes(x = Longitude, y = Latitude), #Action: Set aesthetic mapping of x and y to data variables
size = 0.3) + #Action: Change line width
theme_map() #Action: Remove axes and labels
# 2D Density plot
ggmap(US_map2) + #Action: Set background map
geom_density_2d_filled( #Action: Set glyph to be contours + bands
data = Starbucks, #Action: Pass Starbucks data to geom_density_2d_filled
aes(x = Longitude, y = Latitude), #Action: Set aesthetic mapping of x and y to data variables
size = 0.05, #Action: Change line width
alpha = .5, #Action: Change transparency of fill
bins = 20, #Action: Change the number of bins
color = 'white' #Action: Change of lines
) +
scale_fill_viridis_d( #Action: Change the scale for fill color to follow viridis palette & remove guide
guide = 'none'
) +
theme_map() #Action: Remove axes and labels
starbucks_us_by_state <- Starbucks %>% # Action: Save new object
filter(Country == "US") %>% # Action: Keep rows in the US
count(`State/Province`) %>% # Action: Summarize rows by counting rows per state
mutate(state_name = str_to_lower(abbr2state(`State/Province`))) # Action: Create new variable, state_name, as lower case state names using the state abbreviations
# US states map information - coordinates used to draw borders
states_map <- map_data("state")
# map that colors state by number of Starbucks
starbucks_us_by_state %>% # Action: pass new dataset to ggplot
ggplot() + # Action: Create frame
geom_map( # Action: Set glyph to be polygons from a reference map
map = states_map, # Action: data of map coordinates
aes( # Action: links between aesthetics and variables
map_id = state_name, # Action: set the variable to connect info in starbucks_us_by_state with map dataset
fill = n # Action: set fill to represent the count
)
) +
# This assures the map looks decently nice:
expand_limits(x = states_map$long, y = states_map$lat) +
theme_map()
