library(tidyverse)
library(sf)
library(colorspace)
library(scales)
# set default theme
theme_set(theme_minimal())
# create reusable labels for each plot
map_labels <- labs(
title = "Median household income in New York in 2023",
subtitle = "By census tract",
color = NULL,
fill = NULL,
caption = "Source: American Community Survey"
)AE 17: Visualizing household income in New York
Suggested answers
Application exercise
Answers
Packages
Load New York 2023 median household income
We will use two data files for this analysis. The first contains median household incomes for each census tract in New York from 2023. The second contains the boundaries of each county in New York.
# load data
ny_inc <- st_read(dsn = "data/ny-inc.geojson")Reading layer `ny-inc.geojson' from data source
`/Users/soltoffbc/Projects/info-3312/course-site/ae/data/ny-inc.geojson'
using driver `GeoJSON'
Simple feature collection with 5396 features and 4 fields (with 16 geometries empty)
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: -79.76215 ymin: 40.4961 xmax: -71.85648 ymax: 45.01585
Geodetic CRS: NAD83ny_counties <- st_read(dsn = "data/ny-counties.geojson")Reading layer `ny-counties.geojson' from data source
`/Users/soltoffbc/Projects/info-3312/course-site/ae/data/ny-counties.geojson'
using driver `GeoJSON'
Simple feature collection with 62 features and 4 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: -79.76215 ymin: 40.4961 xmax: -71.85648 ymax: 45.01585
Geodetic CRS: NAD83ny_incSimple feature collection with 5396 features and 4 fields (with 16 geometries empty)
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: -79.76215 ymin: 40.4961 xmax: -71.85648 ymax: 45.01585
Geodetic CRS: NAD83
First 10 features:
GEOID NAME medincomeE
1 36015010800 Census Tract 108; Chemung County; New York 54354
2 36055010200 Census Tract 102; Monroe County; New York 135260
3 36055011705 Census Tract 117.05; Monroe County; New York 115568
4 36055013902 Census Tract 139.02; Monroe County; New York 57588
5 36055004702 Census Tract 47.02; Monroe County; New York 46250
6 36055013604 Census Tract 136.04; Monroe County; New York 52766
7 36055006300 Census Tract 63; Monroe County; New York 65167
8 36055006000 Census Tract 60; Monroe County; New York 56951
9 36055008100 Census Tract 81; Monroe County; New York 47273
10 36055012700 Census Tract 127; Monroe County; New York 120753
medincomeM geometry
1 7404 MULTIPOLYGON (((-76.83044 4...
2 10008 MULTIPOLYGON (((-77.61592 4...
3 31498 MULTIPOLYGON (((-77.48616 4...
4 13986 MULTIPOLYGON (((-77.65909 4...
5 8729 MULTIPOLYGON (((-77.61634 4...
6 12776 MULTIPOLYGON (((-77.69645 4...
7 32012 MULTIPOLYGON (((-77.64697 4...
8 10918 MULTIPOLYGON (((-77.56453 4...
9 22281 MULTIPOLYGON (((-77.6001 43...
10 7602 MULTIPOLYGON (((-77.57503 4...ny_countiesSimple feature collection with 62 features and 4 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: -79.76215 ymin: 40.4961 xmax: -71.85648 ymax: 45.01585
Geodetic CRS: NAD83
First 10 features:
GEOID NAME medincomeE medincomeM
1 36013 Chautauqua County, New York 56507 1981
2 36045 Jefferson County, New York 64978 2730
3 36059 Nassau County, New York 143408 1643
4 36111 Ulster County, New York 81804 2953
5 36051 Livingston County, New York 72464 2969
6 36123 Yates County, New York 67521 4456
7 36025 Delaware County, New York 60226 2922
8 36103 Suffolk County, New York 128329 1374
9 36047 Kings County, New York 78548 1052
10 36105 Sullivan County, New York 69826 2633
geometry
1 MULTIPOLYGON (((-79.76215 4...
2 MULTIPOLYGON (((-76.14744 4...
3 MULTIPOLYGON (((-73.76871 4...
4 MULTIPOLYGON (((-74.78069 4...
5 MULTIPOLYGON (((-78.06078 4...
6 MULTIPOLYGON (((-77.36711 4...
7 MULTIPOLYGON (((-75.42264 4...
8 MULTIPOLYGON (((-72.0377 41...
9 MULTIPOLYGON (((-74.04171 4...
10 MULTIPOLYGON (((-75.14474 4...Part 1
Draw a continuous choropleth of median household income
Your turn: Create a choropleth map of median household income in New York. Use a continuous color gradient to identify each tract’s median household income.
Tip
Use the stored map_labels to set the title, subtitle, and caption for this and the remaining plots.
ggplot(data = ny_inc) +
# use fill and color to avoid gray boundary lines
geom_sf(aes(fill = medincomeE, color = medincomeE)) +
# increase interpretability of graph
scale_color_continuous(labels = label_dollar()) +
scale_fill_continuous(labels = label_dollar()) +
map_labels
Your turn: Now revise the map to use an optimized color gradient for improved readability.
ggplot(data = ny_inc) +
# use fill and color to avoid gray boundary lines
geom_sf(mapping = aes(fill = medincomeE, color = medincomeE)) +
# increase interpretability of graph
scale_fill_continuous_sequential(
palette = "viridis",
rev = FALSE,
aesthetics = c("fill", "color"),
labels = label_dollar(),
name = NULL
) +
map_labels
Overlay county borders
Your turn: To provide better context, overlay the NY county borders on the choropleth map.
ggplot(data = ny_inc) +
# use fill and color to avoid gray boundary lines
geom_sf(mapping = aes(fill = medincomeE, color = medincomeE)) +
# add county borders
geom_sf(data = ny_counties, color = "white", fill = NA) +
# increase interpretability of graph
scale_fill_continuous_sequential(
palette = "viridis",
rev = FALSE,
aesthetics = c("fill", "color"),
labels = label_dollar(),
name = NULL
) +
map_labels
Part 2
Your turn: Continuous color palettes can be hard to distinguish visibly. To improve readability, convert the continuous color palette into a discrete one with 6 levels. Additionally, modify the projection method to use this projection optimized for New York.
# binned_scale() - default breaks
ggplot(data = ny_inc) +
geom_sf(mapping = aes(fill = medincomeE)) +
geom_sf(data = ny_counties, color = "white", fill = NA) +
scale_fill_binned_sequential(
palette = "viridis",
rev = FALSE,
labels = label_dollar()
) +
# increase interpretability of graph
map_labels +
coord_sf(crs = 2261)
Session information
sessioninfo::session_info()─ Session info ───────────────────────────────────────────────────────────────
setting value
version R version 4.4.2 (2024-10-31)
os macOS Sonoma 14.6.1
system aarch64, darwin20
ui X11
language (EN)
collate en_US.UTF-8
ctype en_US.UTF-8
tz America/New_York
date 2025-03-28
pandoc 3.4 @ /usr/local/bin/ (via rmarkdown)
─ Packages ───────────────────────────────────────────────────────────────────
package * version date (UTC) lib source
class 7.3-22 2023-05-03 [1] CRAN (R 4.4.2)
classInt 0.4-10 2023-09-05 [1] CRAN (R 4.3.0)
cli 3.6.3 2024-06-21 [1] CRAN (R 4.4.0)
colorspace * 2.1-1 2024-07-26 [1] CRAN (R 4.4.0)
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