Make BPT shapes valid; bypass 403 error reading laus codes

data-raw/make_geo_sf.R

@@ -22,8 +22,8 @@ stamford_sf <- sf::st_read("https://gist.github.com/camille-s/7002148f77b0020f78
 
 bridgeport_sf <- sf::st_read("https://gist.github.com/camille-s/c5e4f0178cfbf288af454016018f5173/raw/43faa412db577c4f770d861ab913116ccdb3d445/bpt_tract_neighborhoods.geojson") |>
   dplyr::select(name = Name, geometry) |>
-  sf::st_transform(sf::st_crs(tract_sf)) |>
-  sf::st_simplify(dTolerance = 1e-6)
+  sf::st_make_valid() |>
+  sf::st_transform(sf::st_crs(tract_sf))
 
 
 hartford_sf <- sf::st_read("https://gist.github.com/camille-s/9e9761b69a7c86bf6d7163cb73636f26/raw/3858f538d955c022b43e168e4c7cec316c2e437f/hfd_shape.json") |>

data-raw/make_laus_codes.R

@@ -6,13 +6,26 @@
 #   dplyr::select(type = area_type_code, area, code = area_code)
 
 # bls updated the measures listed--for now, filter to the original 4
-laus_measures <- readr::read_tsv("https://download.bls.gov/pub/time.series/la/la.measure") |>
+
+# no longer allows direct download--403 error
+# got these headers from firefox devtools
+headers <- list("User-Agent" = "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:120.0) Gecko/20100101 Firefox/120.0",
+                "Accept" = "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,*/*;q=0.8",
+                "Accept-Language" = "en-US,en;q=0.5",
+                "Accept-Encoding" = "gzip, deflate, br")
+h1 <- curl::new_handle(); h2 <- curl::new_handle()
+curl::handle_setheaders(h1, .list = headers)
+curl::handle_setheaders(h2, .list = headers)
+
+laus_measures <- curl::curl("https://download.bls.gov/pub/time.series/la/la.measure", open = "rb", handle = h1) |>
+  readr::read_tsv() |>
   dplyr::filter(measure_code %in% c("03", "04", "05", "06"))
 
 # make this internal
 # usethis::use_data(laus_measures, overwrite = TRUE)
 
-laus_codes <- readr::read_tsv("https://download.bls.gov/pub/time.series/la/la.area") |>
+laus_codes <- curl::curl("https://download.bls.gov/pub/time.series/la/la.area", open = "rb", handle = h2) |>
+  readr::read_tsv() |>
   dplyr::mutate(state_code = substr(area_code, 3, 4)) |>
   dplyr::left_join(dplyr::distinct(tidycensus::fips_codes, state_code, state), by = "state_code") |>
   dplyr::filter(area_type_code %in% c("A", "F", "G", "H")) |>

data-raw/make_neighborhood_weights.R

@@ -74,9 +74,9 @@ tract2nhood <- block2nhood |>
   dplyr::mutate(weight = round(hh / sum(hh), 3)) |>
   dplyr::ungroup() |>
   dplyr::select(-hh) |>
-  dplyr::left_join(dplyr::distinct(cwi::xwalk, tract, tract_cog_fips), by = "tract") |>
+  dplyr::left_join(dplyr::distinct(cwi::xwalk, tract, tract_cog), by = "tract") |>
   split(~city) |>
-  purrr::map(dplyr::select, town, name, geoid = tract, geoid_cog = tract_cog_fips, weight) |>
+  purrr::map(dplyr::select, town, name, geoid = tract, geoid_cog = tract_cog, weight) |>
   purrr::map(janitor::remove_empty, "cols") |>
   rlang::set_names(~paste(., "tracts", sep = "_"))