divseg

CRAN status R-CMD-check Lifecycle: stable divseg status badge

divseg implements common measures of diversity (within-geography) and segregation (across-geographies).

Installation

You can install the released version of divseg from CRAN with:

 install.packages("divseg")

You can install the released version of divseg from GitHub with:

pak::pak('christopherkenny/divseg')

Example

The basic workflow relies on a tibble where each row represents a geography and has columns that represent some form of population data.

 library(divseg)
 #> 
 #> Attaching package: 'divseg'
 #> The following object is masked from 'package:base':
 #> 
 #> interaction

divseg comes with two example datasets. de_county contains 2010 Census data on the counties in Delaware. de_tract likewise has 2010 Census data on the tracts in Delaware.

 data('de_county')
 data('de_tract')

A pretty standard function call returns a vector, where the first entry is a tibble and the second is tidyselect language.

 ds_blau(.data = de_county, .cols = starts_with('pop_'))
 #> [1] 0.5155228 0.5570435 0.4052769

More importantly, if you specify an argument to .name, all functions are pipe-able.

de_county |>
 ds_blau(starts_with('pop_'), .name = 'blau') |>
 ds_delta(starts_with('pop_'), .name = 'delta') |>
 dplyr::relocate(blau, delta)
 #> Simple feature collection with 3 features and 22 fields
 #> Geometry type: MULTIPOLYGON
 #> Dimension: XY
 #> Bounding box: xmin: -75.78866 ymin: 38.45101 xmax: -75.04894 ymax: 39.83901
 #> Geodetic CRS: NAD83
 #> # A tibble: 3 ×ばつ 23
 #> blau delta GEOID NAME pop pop_white pop_black pop_hisp pop_aian pop_asian
 #> <dbl> <dbl> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
 #> 1 0.516 0.345 10001 Kent... 162310 105891 37812 9346 916 3266
 #> 2 0.557 0.345 10003 New ... 538479 331836 124426 46921 984 23132
 #> 3 0.405 0.345 10005 Suss... 197145 149025 24544 16954 924 1910
 #> # i 13 more variables: pop_nhpi <dbl>, pop_other <dbl>, pop_two <dbl>,
 #> # vap <dbl>, vap_white <dbl>, vap_black <dbl>, vap_hisp <dbl>,
 #> # vap_aian <dbl>, vap_asian <dbl>, vap_nhpi <dbl>, vap_other <dbl>,
 #> # vap_two <dbl>, geometry <MULTIPOLYGON [°]>

Each function has a partner that can go inside calls to dplyr::mutate() by dropping the ds_ prefix:

de_county |>
 dplyr::mutate(herf = hhi(starts_with('pop_'))) |>
 dplyr::relocate(herf)
 #> Simple feature collection with 3 features and 21 fields
 #> Geometry type: MULTIPOLYGON
 #> Dimension: XY
 #> Bounding box: xmin: -75.78866 ymin: 38.45101 xmax: -75.04894 ymax: 39.83901
 #> Geodetic CRS: NAD83
 #> # A tibble: 3 ×ばつ 22
 #> herf GEOID NAME pop pop_white pop_black pop_hisp pop_aian pop_asian
 #> <dbl> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
 #> 1 0.484 10001 Kent Count... 162310 105891 37812 9346 916 3266
 #> 2 0.443 10003 New Castle... 538479 331836 124426 46921 984 23132
 #> 3 0.595 10005 Sussex Cou... 197145 149025 24544 16954 924 1910
 #> # i 13 more variables: pop_nhpi <dbl>, pop_other <dbl>, pop_two <dbl>,
 #> # vap <dbl>, vap_white <dbl>, vap_black <dbl>, vap_hisp <dbl>,
 #> # vap_aian <dbl>, vap_asian <dbl>, vap_nhpi <dbl>, vap_other <dbl>,
 #> # vap_two <dbl>, geometry <MULTIPOLYGON [°]>