Add an equivalent HOOD_158 column to a HOOD_140-keyed data.frame — morie_tps_add_hood_158_from

Looks up each row's HOOD_140 (or hood_140 / NEIGHBOURHOOD_140 / neighbourhood_140) in the bundled crosswalk and writes the PRIMARY-overlap 158 hood code into a new column (default name HOOD_158_equiv).

Usage

morie_tps_add_hood_158_from_140(
  df,
  col_in = NULL,
  col_out = "HOOD_158_equiv",
  crosswalk = NULL
)

Arguments

df: A TPS crime data.frame.
col_in: Name of the input HOOD_140 column. By default the first match from c("HOOD_140", "hood_140", "NEIGHBOURHOOD_140", "neighbourhood_140") present in df.
col_out: Name of the new column to add. Default "HOOD_158_equiv".
crosswalk: Optional pre-loaded crosswalk; defaults to morie_to_hood_crosswalk().

Value

df with the equivalent-code column appended.

Details

For 1:1 mappings the result is exact. For splits (1 historical hood -> 2–4 current hoods) the 158 hood with the largest area overlap wins; this is lossy – analyses at the 158-level should ideally re-aggregate from the per-incident lat/lon rather than relying on the primary-overlap join.

Examples

df <- data.frame(EVENT_ID = 1:3, HOOD_140 = c("082", "001", "075"))
morie_tps_add_hood_158_from_140(df)
#>   EVENT_ID HOOD_140 HOOD_158_equiv
#> 1        1      082            163
#> 2        2      001            001
#> 3        3      075            168