Mapping the proportion of people with West Indian ancestry in Brooklyn, New York

library(tidyverse)
library(tidycensus)
library(sf)
library(scales)
library(viridis)
library(knitr)
library(RColorBrewer)
library(plotly)

Methods

Borough boundaries are represented with a shapefile that was downloaded from NYC Open Data.

Census tract boundaries and data are from the 2016-2020 5-year American Community Survey, accessed with the tidyverse R package. Census data includes:

The proportion of people with West Indian ancestry for each census tract was calculated and the census tracts with no residents were removed.

acs201620 <- load_variables(2020, "acs5", cache = T)
raw_ancestry <- get_acs(geography = "tract", 
                        variables = c(ancestry_pop = "B04006_001",
                                      west_indian = "B04006_094"), 
                        state='NY',
                        county = 'Kings',
                        geometry = T, 
                        year = 2020,
                        output = "wide") 
## Warning: • You have not set a Census API key. Users without a key are limited to 500
## queries per day and may experience performance limitations.
## ℹ For best results, get a Census API key at
## http://api.census.gov/data/key_signup.html and then supply the key to the
## `census_api_key()` function to use it throughout your tidycensus session.
## This warning is displayed once per session.
west_indian <- raw_ancestry |> 
  mutate(pct_west_indian = west_indianE/ancestry_popE)

na_tracts <- west_indian |> 
  filter(is.na(pct_west_indian))

west_indian <- raw_ancestry |> 
  mutate(pct_west_indian = west_indianE/ancestry_popE,
         pct_west_indian = ifelse(is.nan(pct_west_indian), NA, pct_west_indian)) |>
  filter(ancestry_popE>0)

boros <- st_read("data/raw/geo/Borough Boundaries.geojson")
nabes <- st_read("data/raw/geo/nynta2020.shp")

Results

west_indian_map <-ggplot()  + 
  geom_sf(
    data = west_indian, mapping = aes(fill = pct_west_indian,
                                      text = paste0(NAME, ":",
                                                    "<br>Percent West Indian ancestry: ",                                                  
                                                    percent(pct_west_indian, accuracy=1))),
    color = "transparent") +
    # lwd = 0) + # removes the census tract outline
  theme_void() +
  scale_fill_distiller(breaks=c(0, .2, .4, .6, .8, 1),
                       direction = 1,
                       na.value = "transparent",
                       name="Percent West Indian Ancestry (%)",
                       labels=percent_format(accuracy = 1L)) +
  labs(
    title = "Brooklyn, West Indian Ancestry by Census Tract",
    caption = "Source: American Community Survey, 2016-20"
  ) + 
  geom_sf(data = nabes |> filter(BoroName == "Brooklyn"), 
          color = "gray", fill = NA, lwd = 0.25) + 
  geom_sf(data = boros |> filter(boro_name=="Brooklyn"), color = "black", fill = NA, lwd = .5)
## Warning in layer_sf(geom = GeomSf, data = data, mapping = mapping, stat = stat,
## : Ignoring unknown aesthetics: text
ggplotly(west_indian_map, tooltip="text")

As you can see from the map above the population with largest percentage of people with West Indian ancestry are located in central and east Brooklyn.