Add Sales tab with map and crosstalk table; weekly cron at 11:45pm Sunday

data-raw/update_sales.R

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+# update_sales.R
+# Pull the 10 most recent arm's-length sales in St. Andrews from
+# SCPA_Parcels_Sales_CSV.zip (Sarasota.csv). Joins to geometry_lookup
+# for coordinates. Downloads the zip fresh each run.
+# Input:  data-raw/addresses/geometry_lookup.rds  (static)
+# Output: data/sales.rds
+
+library(readr)
+library(dplyr)
+library(stringr)
+library(sf)
+
+subdivisions <- c(
+  "8120", "8113", "8171", "8195", "8221",
+  "8163", "8240", "8159", "8149", "8110", "8254", "8215", "8143"
+)
+
+geometry_lookup <- readRDS("./data-raw/addresses/geometry_lookup.rds")
+
+# ── Download and extract Sarasota.csv ─────────────────────────────────────────
+zip_path <- "./data-raw/property/SCPA_Parcels_Sales_CSV.zip"
+options(timeout = 300)
+download.file(
+  url      = "https://www.sc-pa.com/downloads/SCPA_Parcels_Sales_CSV.zip",
+  destfile = zip_path,
+  mode     = "wb"
+)
+
+csv_con <- unz(zip_path, "Parcel_Sales_CSV/Sarasota.csv")
+
+# ── Load and filter ───────────────────────────────────────────────────────────
+sales <-
+  read_csv(csv_con, show_col_types = FALSE) |>
+  filter(SUBD %in% subdivisions) |>
+  filter(QUAL_CODE %in% c("01", "03")) |>
+  filter(SALE_AMT > 0, LIVING > 0) |>
+  mutate(
+    listed_date    = as.Date(SALE_DATE, format = "%m/%d/%Y"),
+    address        = str_squish(paste(LOCN, LOCS, LOCCITY, LOCSTATE, LOCZIP)),
+    sqft           = as.integer(LIVING),
+    price          = as.integer(SALE_AMT),
+    price_per_sqft = round(price / sqft, 0),
+    account_number = str_trim(ACCOUNT)
+  ) |>
+  arrange(desc(listed_date)) |>
+  slice_head(n = 10) |>
+  select(account_number, listed_date, address, sqft, price, price_per_sqft)
+
+# ── Join geometry ─────────────────────────────────────────────────────────────
+sales <- sales |>
+  inner_join(geometry_lookup, by = "account_number") |>
+  st_as_sf(sf_column_name = "geom") |>
+  mutate(
+    longitude = st_coordinates(geom)[, 1],
+    latitude  = st_coordinates(geom)[, 2]
+  ) |>
+  st_drop_geometry() |>
+  select(listed_date, address, sqft, price, price_per_sqft, latitude, longitude)
+
+cat("Sales written:", nrow(sales), "\n")
+saveRDS(sales, "./data/sales.rds")