In the york building and york crime context, writing nearest(york_crime,york) reads as "find the nearest crime in york to each building in york, and returns a dataframe with every building in york, the nearest york_crime to each building, and the distance in metres between the two.

coverage(nearest_df, to_df, distance_cutoff = 100, ...)

Arguments

nearest_df

dataframe containing latitude and longitude

to_df

dataframe containing latitude and longitude

distance_cutoff

integer the distance threshold you are interested in assessing coverage at

...

extra arguments to pass to nearest

Value

a dataframe containing information about the distance threshold uses (distance_within), the number of events covered and not covered (n_cov, n_not_cov), the percentage covered and not covered (pct_cov, pct_not_cov), and the average distance and sd distance.

Examples

library(dplyr)
#> Warning: package ‘dplyr’ was built under R version 3.5.1
#> #> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’: #> #> filter, lag
#> The following objects are masked from ‘package:base’: #> #> intersect, setdiff, setequal, union
# already existing locations york_selected <- york %>% filter(grade == "I") # proposed locations york_unselected <- york %>% filter(grade != "I") coverage(york_selected, york_crime)
#> # A tibble: 1 x 7 #> distance_within n_cov n_not_cov pct_cov pct_not_cov dist_avg dist_sd #> <dbl> <int> <int> <dbl> <dbl> <dbl> <dbl> #> 1 100 339 1475 0.187 0.813 1400. 1597.
coverage(york_crime, york_selected)
#> # A tibble: 1 x 7 #> distance_within n_cov n_not_cov pct_cov pct_not_cov dist_avg dist_sd #> <dbl> <int> <int> <dbl> <dbl> <dbl> <dbl> #> 1 100 54 17 0.761 0.239 120. 247.