Identifies PO boxes, placeholders, and missing fields so they go straight to
review instead of wasting geocoder calls (or producing confident-but-wrong
matches). Sets bad_address_flag and an initial review_status.
Arguments
- data
A data frame from
clean_addresses().
Value
data with added columns bad_address_flag and review_status.
Rows fit for geocoding get review_status == "ready_for_geocoding".
Details
A missing ZIP is recorded as bad_address_flag == "missing_zip" for audit,
but it does not block geocoding: as long as the address and city are
present, the row stays ready_for_geocoding (Census matches on
street/city/state and ArcGIS on the single-line address). Only genuinely
unusable rows - missing address or city, PO boxes, placeholders, test
records - are routed to needs_manual_review.
Examples
df <- tibble::tibble(
record_id = c("a", "b"),
address_clean = c("100 MAIN STREET", "PO BOX 42"),
city_clean = c("TRENTON", "TRENTON"),
zip_clean = c("08608", "08608"),
record_name = c("Real Site", "Mailbox Co")
)
flag_bad_addresses(df)
#> # A tibble: 2 × 7
#> record_id address_clean city_clean zip_clean record_name bad_address_flag
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 a 100 MAIN STREET TRENTON 08608 Real Site NA
#> 2 b PO BOX 42 TRENTON 08608 Mailbox Co po_box
#> # ℹ 1 more variable: review_status <chr>