Rob Wiederstein
77dbe8cc7f
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refresh_all.R downloads both SCPA files once, then sources update_owners.R and update_sales.R. Single cron job at 11pm Sunday.
54 lines
2.2 KiB
R
54 lines
2.2 KiB
R
# update_sales.R
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# Pull the 10 most recent arm's-length sales in St. Andrews from
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# SCPA_Parcels_Sales_CSV.zip (Sarasota.csv). Joins to geometry_lookup
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# for coordinates. Downloads the zip fresh each run.
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# Input: data-raw/addresses/geometry_lookup.rds (static)
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# Output: data/sales.rds
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library(readr)
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library(dplyr)
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library(stringr)
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library(sf)
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subdivisions <- c(
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"8120", "8113", "8171", "8195", "8221",
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"8163", "8240", "8159", "8149", "8110", "8254", "8215", "8143"
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)
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geometry_lookup <- readRDS("./data-raw/addresses/geometry_lookup.rds")
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# ── Load Sarasota.csv from cached zip ────────────────────────────────────────
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csv_con <- unz("./data-raw/property/SCPA_Parcels_Sales_CSV.zip", "Parcel_Sales_CSV/Sarasota.csv")
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# ── Load and filter ───────────────────────────────────────────────────────────
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sales <-
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read_csv(csv_con, show_col_types = FALSE) |>
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filter(SUBD %in% subdivisions) |>
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filter(QUAL_CODE %in% c("01", "03")) |>
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filter(SALE_AMT > 0, LIVING > 0) |>
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mutate(
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listed_date = as.Date(SALE_DATE, format = "%m/%d/%Y"),
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address = str_squish(paste(LOCN, LOCS, LOCCITY, LOCSTATE, LOCZIP)),
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sqft = as.integer(LIVING),
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price = as.integer(SALE_AMT),
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price_per_sqft = round(price / sqft, 0),
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account_number = str_trim(ACCOUNT)
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) |>
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arrange(desc(listed_date)) |>
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slice_head(n = 10) |>
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select(account_number, listed_date, address, sqft, price, price_per_sqft)
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# ── Join geometry ─────────────────────────────────────────────────────────────
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sales <- sales |>
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inner_join(geometry_lookup, by = "account_number") |>
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st_as_sf(sf_column_name = "geom") |>
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mutate(
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longitude = st_coordinates(geom)[, 1],
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latitude = st_coordinates(geom)[, 2]
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) |>
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st_drop_geometry() |>
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select(listed_date, address, sqft, price, price_per_sqft, latitude, longitude)
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cat("Sales written:", nrow(sales), "\n")
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saveRDS(sales, "./data/sales.rds")
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