In kgilds/ACLOlderAmericansProfile: ACL Profle of Older Americans

library(urbnmapr)
library(urbnthemes)
library(ggplot2)
library(dplyr)
library(tibble)
library(ACLOlderAmericansProfile)


set_urbn_defaults(style = "map")

states_sf <- get_urbn_map("states", sf = TRUE) %>%
  left_join(statedata, by = "state_name")


ggplot() +
  geom_sf(states_sf,
          mapping = aes(fill = horate),
          color = "#ffffff", size = 0.25) +
  labs(fill = "Homeownership rate")


#states_sf %>% 

  #ggplot(aes(fill = horate)) +
  #geom_sf(fill = "grey", color = "#ffffff")


#mapping = aes(fill = horate),
          #color = "#ffffff", size = 0.25) +
  #labs(fill = "Homeownership rate")

data_shape %>% 
  left_join(dummy_data,by = "NAME") -> merged_1

state_profile_n <- state_profile %>%
  dplyr::rename(state_name = State,
                population65plus = "Number of Persons 65 and Older")



states <- get_urbn_map(map = "states", sf = TRUE) %>% 
  dplyr::left_join(state_profile_n, by = "state_name")





ggplot() +
  geom_sf(states,
          mapping = aes(fill = population65plus),
          color = "#ffffff", size = 0.25)  +
  scale_fill_continuous( low = "grey", high = "purple", 
                           name = "Population 65 Plus", label = scales::label_number_si()) 

states

spatial_data <- left_join(statedata,
                          get_urbn_map(map = "states", sf = TRUE),
                          by = "state_name")

ggplot() +
  geom_sf(spatial_data,
          mapping = aes(fill = horate),
          color = "#ffffff", size = 0.25) +
  labs(fill = "Homeownership rate")

states_sf <- get_urbn_map(map = "states", sf = TRUE)

states_sf %>%
  ggplot() +
  geom_sf(aes(), 
          fill = "grey", color = "#ffffff", size = 0.25) +
  geom_sf_text(data = get_urbn_labels(map = "states", sf = TRUE), 
                aes(label = state_abbv), 
            size = 3)