R: applying custom function row by row with mutate() - r

Question

I have created a function that uses st_join() from the sf package to extract the congressional district (a polygon) from a set of latitude and longitude coordinates, using a different shapefile to identify the congressional district depending on a "congress" argument that is specified. (This is necessary because districts are periodically redrawn, so the boundaries change over time.) The next step is to apply the function row by row to a data frame containing multiple rows of coordinates (and associated "congress" values) so that the congress value for a given row determines which shapefile to use, and then assign the extracted district to a new variable.
I'm running into trouble applying this function row-by-row. I first tried using the rowwise() and mutate() functions from dplyr, but got a "must be size 1" error. Based on the comments to this question, I put list() around the variable assigned inside the mutate() function, but this has resulted in the new variable being a list instead a single character string.
I would greatly appreciate help figuring out a way to either (i) modify the function so that it can be applied row by row using rowwise() and mutate() or (ii) apply my function row-by-row in some other way.
Reproducible code is below; you just need to download two shapefiles from https://cdmaps.polisci.ucla.edu/ ("districts104.zip" and "districts111.zip"), unzip them, and put them in your working directory.
library(tidyverse)
library(sf)
districts_104 <- st_read("districts104.shp")
districts_111 <- st_read("districts111.shp")
congress <- c(104, 111)
latitude <- c(37.32935, 37.32935)
longitude <- c(-122.00954, -122.00954)
df_test <- data.frame(congress, latitude, longitude)
point_geo_test <- st_as_sf(df_test,
coords = c(x = "longitude", y = "latitude"),
crs = st_crs(districts_104)) # prep for st_join()
sf_use_s2(FALSE) # preempt evaluation error that would otherwise pop up when using the st_join function
extract_district <- function(points, cong) {
shapefile <- get(paste0("districts_", cong))
st_join_results <- st_join(points, shapefile, join = st_within)
paste(st_join_results$STATENAME, st_join_results$DISTRICT, sep = "-")
}
point_geo_test <- point_geo_test %>%
rowwise %>%
mutate(district = list(extract_district(points = point_geo_test, cong = congress)))

Answer 1

Edit 7 July:
From your comments I understand you were looking for something different, the assumption I made about why your function was giving multiple values was wrong. Hence this new answer from scratch:
The custom function you've written doesn't lend itself to row-by-row application, because it already processes all rows at once:
Given the following input:
congress <- c(104, 111, 104, 111, 104, 111)
latitude <- c(37.32935, 37.32935, 41.1134016, 41.1134016, 42.1554948, 42.1554948)
longitude <- c(-122.00954, -122.00954, 73.720356, 73.720356, -87.868850502543, -87.868850502543)
point_geo_test contains these values:
> point_geo_test
[...]
congress geometry
1 104 POINT (-122.0095 37.32935)
2 111 POINT (-122.0095 37.32935)
3 104 POINT (73.72036 41.1134)
4 111 POINT (73.72036 41.1134)
5 104 POINT (-87.86885 42.15549)
6 111 POINT (-87.86885 42.15549)
and extract_district() returns this:
> extract_district(point_geo_test, 104)
[...]
[1] "California-14" "California-14" "NA-NA" "NA-NA" "Illinois-10" "Illinois-10"
This is already a result for each row. The only problem is, while they are the correct results for the coordinates of each row, they the name for those coordinates only during congress 104. Hence, these values are only valid for the rows in point_geo_test where congress == 104.
Extracting correct values for all rows
We will create a function that returns the correct data for all rows, eg the correct name for the coordinates during the associated congress.
I've simplified your code slightly: the df_test is not an intermediate data frame any more, but defined directly in the creation of point_geo_test. Any values I extract, I'll save into this data frame as well.
library(tidyverse)
library(sf)
sf_use_s2(FALSE)
districts_104 <- st_read("districts104.shp")
districts_111 <- st_read("districts111.shp")
congress <- c(104, 111, 104, 111, 104, 111)
latitude <- c(37.32935, 37.32935, 41.1134016, 41.1134016, 42.1554948, 42.1554948)
longitude <- c(-122.00954, -122.00954, 73.720356, 73.720356, -87.868850502543, -87.868850502543)
point_geo_test <- st_as_sf(data.frame(congress, latitude, longitude),
coords = c(x = "longitude", y = "latitude"),
crs = st_crs(districts_104))
To keep the code more flexible and organized, I'll create a generic function that can fetch any parameter for the given coordinates:
extract_values <- function(points, parameter) {
# initialize return values, one for each row in `points`
values <- rep(NA, nrow(points))
# for each congress present in `points`, lookup parameter and store in the rows with matching congress
for(cong in unique(points$congress)) {
shapefile <- get(paste0("districts_", cong))
st_join_results <- st_join(points, shapefile, join = st_within)
values[points$congress == cong] <- st_join_results[[parameter]][points$congress == cong]
}
return(values)
}
Examples:
> extract_values(point_geo_test, 'STATENAME')
[1] "California" "California" NA NA "Illinois" "Illinois"
> extract_values(point_geo_test, 'DISTRICT')
[1] "14" "15" NA NA "10" "10"
Storing values
point_geo_test$state <- extract_values(point_geo_test, 'STATENAME')
point_geo_test$district <- extract_values(point_geo_test, 'DISTRICT')
point_geo_test$name <- paste(point_geo_test$state, point_geo_test$district, sep = "-")
Result:
> point_geo_test
Simple feature collection with 6 features and 4 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: -122.0095 ymin: 37.32935 xmax: 73.72036 ymax: 42.15549
Geodetic CRS: GRS 1980(IUGG, 1980)
congress state district name geometry
1 104 California 14 California-14 POINT (-122.0095 37.32935)
2 111 California 15 California-15 POINT (-122.0095 37.32935)
3 104 <NA> <NA> NA-NA POINT (73.72036 41.1134)
4 111 <NA> <NA> NA-NA POINT (73.72036 41.1134)
5 104 Illinois 10 Illinois-10 POINT (-87.86885 42.15549)
6 111 Illinois 10 Illinois-10 POINT (-87.86885 42.15549)