gis_workflow.R

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

denton <- counties(cb = TRUE) %>%
  filter(GEOID == "48121") %>%
  erase_water()

customers <- st_sample(denton, size = 20) %>%
  st_coordinates()

# Use set.seed() if you want the same names every time
customer_table <- tibble(
  name = randomNames(n = 20),
  longitude = customers[,1],
  latitude = customers[,2]
)

customer_sf <- customer_table %>%
  st_as_sf(coords = c("longitude", "latitude"),
           crs = 4326)

customer_buffers <- customer_sf %>%
  st_transform(26914) %>%
  st_buffer(5000)

mapview(customer_buffers)

customer_drivetimes <- customer_sf %>%
  mb_isochrone(time = 10, profile = "driving", 
               id_column = "name")

mapview(customer_drivetimes)

denton_income <- get_acs(
  geography = "tract",
  variables = "B19013_001",
  state = "TX",
  county = "Denton",
  geometry = TRUE
) %>%
  select(tract_income = estimate) %>%
  st_transform(st_crs(customer_sf))
  
customers_with_income <- customer_sf %>%
  st_join(denton_income)

customers_with_income