Creates an urbanicity classification lookup table from Modified Monash Model (MMM) geographic classifications.
Usage
make_urbanicity_lookup(
data_xx,
area_populations_ls = list(AreaERP2023Share = "ERP 2023"),
area_sizes_ls = list(AreaKM2SA2 = "SA2 2021 Area (km2)", AreaKM2SA2Urbanicity =
"MMM 2023 Area in SA2 2021 (km2)"),
area_types_ls = list(SA2 = "SA2 2021 Code"),
code_var_1L_chr = "MMM 2023 Code",
coding_ls = list(urban = 1:2, rural = 3:7),
filters_ls = list(),
transformation_fn = as.character,
output_1L_chr = c("tbl_df", "data.frame", "data.table")
)Arguments
- data_xx
Spatial dataset.
- area_populations_ls
Named list specifying population variables.
- area_sizes_ls
Named list specifying area-related variables.
- area_types_ls
Named list specifying geographic identifiers.
- code_var_1L_chr
Name of the MMM classification code variable.
- coding_ls
Named list mapping MMM codes to urbanicity labels.
- filters_ls
Named list of filtering rules.
- transformation_fn
Function applied to area identifiers.
- output_1L_chr
Output type. One of
"tbl_df","data.frame"or"data.table".
Value
A lookup table containing urbanicity classifications and optional population or area summaries.
Details
Geographic areas are mapped into user-defined urbanicity categories
such as "urban" and "rural" and optionally summarised
with population and area statistics.
Examples
if (FALSE) { # \dontrun{
make_urbanicity_lookup(
data_xx,
coding_ls = list(
urban = 1:2,
rural = 3:7
),
output_1L_chr = "data.table"
)
} # }