In fresques/ggmap: Spatial Visualization with ggplot2

knitr::opts_chunk$set(
  collapse = TRUE, cache = TRUE,
  comment = "# ",
  fig.path = "tools/README-"
)

ggmap

ggmap makes it easy to retrieve raster map tiles from popular online mapping services like Google Maps, OpenStreetMap, Stamen Maps, and plot them using the ggplot2 framework:

library(ggmap)

us <- c(left = -125, bottom = 25.75, right = -67, top = 49)
map <- get_stamenmap(us, zoom = 5, maptype = "toner-lite")
ggmap(map)
ggmap(map, extent = "device")

Use qmplot() in the same way you'd use qplot(), but with a map automatically added in the background:

library(dplyr)

# only violent crimes
violent_crimes <- filter(crime, 
  offense != "auto theft", offense != "theft", offense != "burglary"
)

# rank violent crimes
violent_crimes$offense <- factor(
  violent_crimes$offense,
  levels = c("robbery", "aggravated assault", "rape", "murder")
)

# restrict to downtown
violent_crimes <- filter(violent_crimes,
  -95.39681 <= lon & lon <= -95.34188,
   29.73631 <= lat & lat <=  29.78400
)

qmplot(lon, lat, data = violent_crimes, maptype = "toner-lite", color = I("red"))
qmplot(lon, lat, data = violent_crimes, maptype = "toner-lite", geom = "density2d", color = I("red"))

Since ggmap's built on top of ggplot2, all your usual ggplot2 stuff (geoms, polishing, etc.) will work, and there are some unique graphing perks ggmap brings to the table, too.

robberies <- violent_crimes %>% filter(offense == "robbery")

qmplot(lon, lat, data = violent_crimes, geom = "blank", zoom = 15, maptype = "toner-background", darken = .7, legend = "topleft") +
  stat_density_2d(aes(fill = ..level..), geom = "polygon", alpha = .3, color = NA) +
  scale_fill_gradient2("Robbery\nPropensity", low = "white", mid = "yellow", high = "red", midpoint = 650)

Faceting works, too:

qmplot(lon, lat, data = violent_crimes, maptype = "toner-background", color = offense) + 
  facet_wrap(~ offense)

For convenience, here's a map of Europe:

europe <- c(left = -12, bottom = 35, right = 30, top = 63)
get_stamenmap(europe, zoom = 5) %>% ggmap()
get_stamenmap(europe, zoom = 5, maptype = "toner-lite") %>% ggmap()

Google Maps and Credentials

Google Maps can be used just as easily. However, since Google Maps use a center/zoom specification, their input is a bit different:

get_googlemap("waco texas", zoom = 12) %>% ggmap()

Moreover, you can get various different styles of Google Maps with ggmap (just like Stamen Maps):

get_googlemap("waco texas", zoom = 12, maptype = "satellite") %>% ggmap()
get_googlemap("waco texas", zoom = 12, maptype = "roadmap") %>% ggmap()
get_googlemap("waco texas", zoom = 12, maptype = "hybrid") %>% ggmap()

Google's geocoding and reverse geocoding API's are available through geocode() and revgeocode(), respectively:

geocode("1301 S University Parks Dr, Waco, TX 76798")
revgeocode(c(lon = -97.1161, lat = 31.55098))

There is also a mutate_geocode() that works similarly to dplyr's mutate() function:

library(tidyverse)
tb <- data_frame(address = c("1600 Pennsylvania Avenue, Washington DC", "", "waco texas"))
tb %>% mutate_geocode(address)

Treks use Google's routing API to give you routes (route() and trek() give slightly different results; the latter hugs roads):

trek_df <- trek("houson, texas", "waco, texas", structure = "route")
qmap("college station, texas", zoom = 8) +
  geom_path(
    aes(x = lon, y = lat),  colour = "blue",
    size = 1.5, alpha = .5,
    data = trek_df, lineend = "round"
  )

(They also provide information on how long it takes to get from point A to point B.)

Map distances, in both length and anticipated time, can be computed with mapdist()). Moreover the function is vectorized:

mapdist(c("houston, texas", "dallas"), "waco, texas")

Google credentialing

If you have a Google API key, you can exceed the standard limits Google places on queries. By default, when ggmap is loaded it will set the following credentials and limits:

ggmap_credentials()

Look at the documentation of ?register_google() to learn more. If you do have an API key, you set it with:

register_google(key = "[your key here]", account_type = "premium", day_limit = 100000)
ggmap_credentials()

These will then be used and checked when creating the query URL:

register_google(key = "AbCdEfGhIjKlMnOpQrStUvWxYz")
get_googlemap("waco texas", urlonly = TRUE)

For anything that hasn't been implemente (URL-wise), you can inject code into the query usin g inject:

get_googlemap("waco texas", urlonly = TRUE, inject = "otherItem = Stuff")

Installation

• From CRAN: install.packages("ggmap")

• From Github: devtools::install_github("dkahle/ggmap")

fresques/ggmap documentation built on May 28, 2019, 8:40 p.m.