dotsInPolys length mismatch using data downloaded via tidycensus

Question

Can you help figure out the best way to resolve the length mismatch error thrown by dotsInPolys? I think it is because there are NA's or NULLs or some funk in the polygon data that makes it too long. Here's code that reproduces the error. Ultimately, I want to plot multiple races using Leaflet, but I can't produce the lat/lon needed for the random dots at this point.

require(maptools)
require(tidycensus)

person.number.divider <- 1000

census_api_key("ENTER KEY HERE", install = TRUE)

racevars <- c(White = "B02001_002", #"P005003" 
              Black = "B02001_003", #Black or African American alone
              Latinx = "B03001_003"
)

nj.county <- get_acs(geography = "county", #tract
              year = 2015,
              variables = racevars,
              state = "NJ", #county = "Harris County",
              geometry = TRUE,
              summary_var = "B02001_001")

library(sf)
st_write(nj.county, "nj.county.shp", delete_layer = TRUE)

nj <- rgdal::readOGR(dsn = "nj.county.shp") %>%
  spTransform(CRS("+proj=longlat +datum=WGS84"))

nj@data <- nj@data %>% 
  tidyr::separate(NAME,
                  sep =",",
                  into = c("county", "state"))  %>%
  dplyr::select(estimat,variabl, GEOID, county) %>%
  spread(key = variabl, value = estimat) %>%
  mutate(county = trimws(county))


black.dots <- dplyr::select(nj@data, Black) / person.number.divider #%>%
black.dots <-   dotsInPolys(nj, as.integer(black.dots$Black), f="random")

# Error in dotsInPolys(nj, as.integer(black.dots$Black), f = "random") : 
# different lengths

length(nj) # 63 This seems too many, because I believe NJ has 21 counties.
length(black.dots$Black) # 21

This post (Advice on troubleshooting dotsInPolys error (maptools)) came close to helping me, but I couldn't see how to apply it to my case.

I can change the length of the nj spatialpolygonsdataframe by removing NA's and counties with a black pop greater than 0, but then the map doesn't plot multiple counties (maybe there is something wrong with the census download?).

I've mostly resolved the issue. The "spread" that reshaped the data was causing problems. Using `output = "wide"` in the tidycensus download gave a better output. — dca, Oct 11 '18 at 20:13

score 1 · Accepted Answer · answered Nov 20 '18 at 15:30

It looks like you might have gotten this figured out, but I wanted to share another approach that uses sf::st_sample() instead of maptools::dotsInPolys(). One advantage of this is that you don't need to convert the sf object you get from tidycensus to a sp object.

In the following example I split the census data by race into a list three sf objects then perform st_sample() on each element of the list (each race). Next, I recombine the sampled points into one sf object with a new race variable for each point. Finally, I use tmap to make a map, though you could use ggplot2 or leaflet to map as well.

library(tidyverse)
library(tidycensus)
library(sf)
library(tmap)

person.number.divider <- 1000

racevars <- c(White = "B02001_002", #"P005003" 
              Black = "B02001_003", #Black or African American alone
              Latinx = "B03001_003"
              )

# get acs data with geography in "tidy" form
nj.county <- get_acs(geography = "county", #tract
                     year = 2015,
                     variables = racevars,
                     state = "NJ", #county = "Harris County",
                     geometry = TRUE,
                     summary_var = "B02001_001"
                     )

# split by race
county.split <- nj.county %>% 
  split(.$variable)

# randomly sample points in polygons based on population
points.list <- map(county.split, ~ st_sample(., .$estimate / person.number.divider))

# combine points into sf collections and add race variable 
points <- imap(points.list, ~ st_sf(tibble(race = rep(.y, length(.x))), geometry = .x)) %>% 
  reduce(rbind)

# map!
tm_shape(nj.county) +
  tm_borders(col = "darkgray", lwd = 0.5) +
  tm_shape(points) +
  tm_dots(col = "race", size = 0.01, pal = "Set2")

I don't have enough rep to post the map image directly, but here it is.

This is a cool way to do it and I was able to reproduce your map flawlessly. I'm not sure exactly what goes on inside st_sample and st_sf, but I look forward to reading about those two functions. Thanks — dca, Nov 21 '18 at 16:03
`st_sample` takes n random samples from the uniform distribution contained within each polygon in the `sf` object and in this case, `st_sf` creates a spatial collection of points (`sfc`) object for each of the three races. — mfherman, Nov 26 '18 at 15:40

dotsInPolys length mismatch using data downloaded via tidycensus

1 Answers1