Rob Wiederstein
43552a937e
- Add Dockerfile, docker-compose.yml, .dockerignore, .env (port 3842) - Add Caddyfile.snippet for analytics gateway import pattern - Add .gitea/workflows/deploy.yaml for act_runner SSH deploy - Untrack sensitive/data files (SCPA xlsx, owners.rds) - Add renv lockfile and infrastructure files - Reorganize data-raw scripts and add SarasotaCounty boundary data - Move www assets to www/images/, add docs PDFs
83 lines
2.7 KiB
R
83 lines
2.7 KiB
R
# update_owners.R
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# Weekly update script. Reads fresh SCPA property data, joins to stable
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# geometry lookup by account_number, saves data/owners.rds.
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# Only the SCPA xlsx needs to be replaced to refresh ownership data.
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# Input: data-raw/property/SCPA Public.xlsx (replace weekly)
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# data-raw/addresses/geometry_lookup.rds (static)
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# Output: data/owners.rds
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library(readxl)
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library(janitor)
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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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# load geometry lookup (static) ----
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geometry_lookup <- readRDS("./data-raw/addresses/geometry_lookup.rds")
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# download fresh scpa data ----
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download.file(
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url = "https://www.sc-pa.com/downloads/SCPA%20Public.xlsx",
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destfile = "./data-raw/property/SCPA Public.xlsx",
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mode = "wb"
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)
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# load and clean scpa data ----
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owners_raw <-
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readxl::read_xlsx(
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path = "./data-raw/property/SCPA Public.xlsx",
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n_max = Inf,
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.name_repair = ~janitor::make_clean_names(.x)
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) |>
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filter(subdivision %in% subdivisions) |>
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rename(
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situs_address = situs_address_property_address,
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homestead = homestead_exemption_yes_or_no
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) |>
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filter(!is.na(situs_address)) |>
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filter(!grepl("^0", situs_address)) |>
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mutate(
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# extract clean street address (before multiple spaces / unit suffix)
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label = str_trim(str_extract(situs_address, "^\\d+\\s+\\S+\\s+\\S+")),
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location = paste0(label, ", Venice FL")
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) |>
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select(account_number, owner_1, owner_2, subdivision, homestead, label, location)
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# join to geometry ----
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owners <- owners_raw |>
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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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# report any unmatched records ----
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n_unmatched <- nrow(owners_raw) - nrow(owners)
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if (n_unmatched > 0) {
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cat("WARNING:", n_unmatched, "records had no matching geometry and were dropped.\n")
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missing <- anti_join(owners_raw, st_drop_geometry(geometry_lookup), by = "account_number")
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print(missing)
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}
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# report most recent sale date in st. andrews ----
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latest_sale <-
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readxl::read_xlsx(
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path = "./data-raw/property/SCPA Public.xlsx",
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n_max = Inf,
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.name_repair = ~janitor::make_clean_names(.x)
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) |>
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filter(subdivision %in% subdivisions) |>
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select(account_number, owner_1, contains("sale")) |>
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filter(!is.na(account_number)) |>
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mutate(last_sale_date = as.Date(last_sale_date, format = "%m/%d/%Y")) |>
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arrange(desc(last_sale_date)) |>
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head(1)
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cat("Owners written:", nrow(owners), "\n")
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attr(owners, "last_sale_date") <- latest_sale$last_sale_date
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saveRDS(owners, "./data/owners.rds")
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cat("Saved to data/owners.rds\n")
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cat("Most recent sale date:", format(latest_sale$last_sale_date, "%B %d, %Y"), "\n")
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