walkerke

library(tidycensus)
library(tigris)
library(tidyverse)
library(sf)
library(ggiraph)
library(patchwork)
options(tigris_use_cache = TRUE)
set.seed(123456)

# Get a list of counties within the Austin CBSA using tigris

walkerke

library(mapboxapi)
library(mapview)

mb_access_token("YOUR TOKEN GOES HERE")

isos <- mb_isochrone("2500 Victory Ave, Dallas TX",
                     time = c(5, 10, 15),
                     profile = "driving-traffic")

mapview(isos, zcol = "time",

walkerke

library(tidycensus)
library(tidyverse)
library(showtext)
font_add_google("Montserrat")
showtext_auto()

us_occ_pums <- get_pums(
  variables = c("OCCP", "WAGP"),
  state = "all",
  survey = "acs1",

walkerke

library(tidycensus)
library(tigris)
library(tidyverse)
library(sf)
options(tigris_use_cache = TRUE)
set.seed(123456)

austin_counties <- counties(year = 2021) %>%
  filter(CBSAFP == "12420") %>%
  pull(COUNTYFP)

walkerke

library(tidycensus)
library(tidyverse)
options(tigris_use_cache = TRUE)

state_names <- c(state.name, "District of Columbia")
names(state_names) <- state_names

tictoc::tic()
age_maps <- map(state_names, ~{
  

walkerke

library(tidyverse)
library(tidycensus)
library(showtext)
font_add_google("Montserrat")
showtext_auto()

continental <- read_csv("https://www.ncei.noaa.gov/access/monitoring/climate-at-a-glance/county/mapping/110-tavg-202402-1.csv", skip = 4) |>
  mutate(avg_temp = as.numeric(Value),
         GEOID = map_chr(ID, ~{
           last3 <- str_sub(.x, start = -3)

walkerke

# Requires tidycensus dev version
# remotes::install_github("walkerke/tidycensus")

library(tidyverse)
library(tidycensus)
library(showtext)
font_add_google("Montserrat")
showtext_auto()

pres_results <- read_csv("https://raw.githubusercontent.com/tonmcg/US_County_Level_Election_Results_08-20/master/2020_US_County_Level_Presidential_Results.csv")

walkerke

library(sf)
library(tigris)
library(tidycensus)
library(tidyverse)
library(mapview)
library(mapboxapi)
library(randomNames)
options(tigris_use_cache = TRUE)

denton <- counties(cb = TRUE) %>%

walkerke

library(mapboxapi)
library(tidycensus)
library(tidyverse)
library(sf)
library(ggspatial)
options(tigris_use_cache = TRUE)

# Get the data from the ACS
tarrant <- get_acs(
  geography = "tract",

walkerke

library(tidyverse)
library(sf)
library(mapboxapi)
library(tigris)
library(fasterize)
library(leaflet)

# Get county boundaries; you can analyze for any county
target_GEOID <- "48309"