my_continent <- function(dat){dat %>% unique() %>% filter(!state_abbr %in% c("AK","HI","PR"))}
state <- my_continent(us_states())
IDcounties <- my_continent(us_counties()) %>% filter(state_abbr == "ID")

city <- my_continent(us_cities()) %>% 
  group_by(state_name) %>% 
  top_n(3, population)
my_str <- function(dat){dat %>% unlist() %>% str_flatten("|")}
city_max <- my_str(city %>%
  group_by(state_abbr) %>% 
  summarise(max(population)) %>% 
  select(`max(population)`))

city_min <- my_str(city %>%
  group_by(state_abbr) %>% 
  summarise(min(population)) %>% 
  select(`min(population)`))

cities <- city %>% 
  mutate(newpop = (population/1000)) %>% 
  group_by(state_abbr) %>% 
  mutate(rank = case_when(str_detect(population, city_max) ~ 1, str_detect(population, city_min) ~ 3, TRUE ~ 2))

top_cities <- cities %>% filter(rank == 1)
pathb <- "https://byuistats.github.io/M335/data/shp.zip"
pathw <- "https://opendata.arcgis.com/datasets/1abb666937894ae4a87afe9655d2ff83_1.zip?outSR=%7B%22latestWkid%22%3A102605%2C%22wkid%22%3A102605%7D"
pathd <- "https://opendata.arcgis.com/datasets/e163d7da3b84410ab94700a92b7735ce_0.zip?outSR=%7B%22latestWkid%22%3A102605%2C%22wkid%22%3A102605%7D"
pathh <- "https://research.idwr.idaho.gov/gis/Spatial/Hydrography/streams_lakes/c_250k/hyd250.zip"
read_my_zip <- function(my_path){
  df <- tempfile()
  uf <- tempfile()
  download(my_path, df, mode = "wb")
  unzip(df, exdir = uf)
  dataset <- read_sf(uf)
  file_delete(df)
  dir_delete(uf)
  dataset
}
big_dams <- read_my_zip(pathd) %>% 
  mutate(SurfaceAre = parse_number(SurfaceAre)) %>% 
  filter(SurfaceAre > 50)

big_wells <- read_my_zip(pathw) %>% 
  filter(Production > 5000) 

river <- read_my_zip(pathh) %>% 
  filter(str_detect(FEAT_NAME, "Snake River") | str_detect(FEAT_NAME, "Henry"))

idaho <- read_my_zip(pathb) %>% 
  filter(StateName == "Idaho" & StateFIPSN == 16)

Background

Choose from Task 19 or Task 20 and recreate your plot using leaflet

Reading

  • Leaflet for R: Introduction
  • Leaflet for R: The Map Widget
  • Leaflet for R: Basemaps
  • Leaflet for R: Markers
  • Leaflet for R: Popups and Labels
  • Leaflet for R: Lines and Shapes
  • Leaflet for R: Colors

Tasks

See tasks for Task 19 (Leaflet)

  • Create a plot that closely matches my example
    • library(USAboundaries) has three useful functions - us_cities(), us_states(), and us_counties()

See tasks for Task 20 (Leaflet)

Data Visualization

Task 19

ggplot() + 
  geom_sf(data = state, fill = NA) +
  geom_sf(data = IDcounties, fill = NA) +
  geom_sf(data = cities, aes(size = newpop, color = rank)) +
  theme_bw() +
  labs(size = "Population (1000)") +
  guides(color = FALSE) + 
  geom_label_repel(data = top_cities, aes(label = city, geometry = geometry), stat = "sf_coordinates") +
  theme(axis.title.x=element_blank(), axis.text.x=element_blank(), axis.ticks.x=element_blank(),
        axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank())

Task 20

# Use this R-Chunk to clean & wrangle your data!
ggplot() +
  geom_sf(data = idaho, fill = "white") +
  geom_sf(data = river, color = "blue", size = 2) +
  geom_sf(data = big_dams, color = "red", pch = 7, aes(size = SurfaceAre)) +
  geom_sf(data = big_wells) +
  theme_bw() +
  labs(size = "Dam Surface Area (square acres)", title = "Idaho Water Works") +
  coord_sf(crs = st_crs(3857))

Task 21

Task 19 Plot

leaflet(data = state) %>% 
  addTiles() %>% 
  addPolygons(data = IDcounties, fillColor = topo.colors(10, alpha = NULL), color = "black") %>% 
  addCircles(data = cities, color = "red") %>% 
  addMarkers(data = top_cities, popup = ~htmlEscape(city))