diff --git a/3_visualize.R b/3_visualize.R
index b456eedd2e2530fae79b5f813e6c806612937864..66ce1ca5f57ed89aa827af62821cd2a378490f20 100644
--- a/3_visualize.R
+++ b/3_visualize.R
@@ -4,7 +4,8 @@ p3_targets <- list(
tar_target(
p3_med_income_png,
plot_census_map(
- census_data = p2_perc_census_layers_sf[[2]],
+ census_data = p2_perc_census_acs5_layers_sf[[2]],
+ percent_leg = FALSE,
var = 'estimate',
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/med_income_census_2022.png",
@@ -25,7 +26,8 @@ p3_targets <- list(
tar_target(
p3_tot_black_png,
plot_census_map(
- census_data = p2_perc_census_layers_sf[[3]],
+ census_data = p2_perc_census_acs5_layers_sf[[3]],
+ percent_leg = FALSE,
var = 'estimate',
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/tot_black_census_2022.png",
@@ -47,7 +49,8 @@ p3_targets <- list(
tar_target(
p3_perc_black_png,
plot_census_map(
- census_data = p2_perc_census_layers_sf[[3]],
+ census_data = p2_perc_census_acs5_layers_sf[[3]],
+ percent_leg = TRUE,
var = 'percent',
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/perc_black_census_2022.png",
@@ -68,7 +71,8 @@ p3_targets <- list(
tar_target(
p3_tot_latino_png,
plot_census_map(
- census_data = p2_perc_census_layers_sf[[4]],
+ census_data = p2_perc_census_acs5_layers_sf[[4]],
+ percent_leg = FALSE,
var = 'estimate',
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/tot_latino_census_2022.png",
@@ -89,7 +93,8 @@ p3_targets <- list(
tar_target(
p3_perc_latino_png,
plot_census_map(
- census_data = p2_perc_census_layers_sf[[4]],
+ census_data = p2_perc_census_acs5_layers_sf[[4]],
+ percent_leg = TRUE,
var = 'percent',
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/perc_latino_census_2022.png",
@@ -110,7 +115,8 @@ p3_targets <- list(
tar_target(
p3_tot_male_png,
plot_census_map(
- census_data = p2_perc_census_layers_sf[[5]],
+ census_data = p2_perc_census_acs5_layers_sf[[5]],
+ percent_leg = FALSE,
var = 'estimate',
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/tot_male_census_2022.png",
@@ -131,7 +137,8 @@ p3_targets <- list(
tar_target(
p3_tot_female_png,
plot_census_map(
- census_data = p2_perc_census_layers_sf[[6]],
+ census_data = p2_perc_census_acs5_layers_sf[[6]],
+ percent_leg = FALSE,
var = 'estimate',
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/tot_female_census_2022.png",
@@ -147,5 +154,201 @@ p3_targets <- list(
font_size = 10
),
format = "file"
+ ),
+
+ # Disaggregated maps
+ # percent age maps
+ tar_target(
+ p3_perc_under_18_map_png,
+ plot_census_map(
+ census_data = p2_census_acs5sub_age_data[[1]],
+ percent_leg = TRUE,
+ var = 'percent',
+ conus_sf = p1_conus_sf,
+ outfile_path = "3_visualize/out/perc_pop_under_18_2022.png",
+ pal = "OrRd",
+ leg_title = "Percent of Total Poulation\nUnder 18, 2022",
+ width = 6,
+ height = 4,
+ dpi = 300,
+ counties_outline_col = "grey80",
+ conus_outline_col = 'grey50',
+ bg_col = "white",
+ load_font = 'Source Sans Pro',
+ font_size = 10
+ ),
+ format = "file"
+ ),
+ tar_target(
+ p3_perc_18_24_map_png,
+ plot_census_map(
+ census_data = p2_census_acs5sub_age_data[[2]],
+ percent_leg = TRUE,
+ var = 'percent',
+ conus_sf = p1_conus_sf,
+ outfile_path = "3_visualize/out/perc_pop_under_18-24_2022.png",
+ pal = "OrRd",
+ leg_title = "Percent of Total Poulation\n18-24 years, 2022",
+ width = 6,
+ height = 4,
+ dpi = 300,
+ counties_outline_col = "grey80",
+ conus_outline_col = 'grey50',
+ bg_col = "white",
+ load_font = 'Source Sans Pro',
+ font_size = 10
+ ),
+ format = "file"
+ ),
+ tar_target(
+ p3_perc_15_44_map_png,
+ plot_census_map(
+ census_data = p2_census_acs5sub_age_data[[3]],
+ percent_leg = TRUE,
+ var = 'percent',
+ conus_sf = p1_conus_sf,
+ outfile_path = "3_visualize/out/perc_pop_under_15-44_2022.png",
+ pal = "OrRd",
+ leg_title = "Percent of Total Poulation\n15-44 years, 2022",
+ width = 6,
+ height = 4,
+ dpi = 300,
+ counties_outline_col = "grey80",
+ conus_outline_col = 'grey50',
+ bg_col = "white",
+ load_font = 'Source Sans Pro',
+ font_size = 10
+ ),
+ format = "file"
+ ),
+ tar_target(
+ p3_perc_60_plus_map_png,
+ plot_census_map(
+ census_data = p2_census_acs5sub_age_data[[4]],
+ percent_leg = TRUE,
+ var = 'percent',
+ conus_sf = p1_conus_sf,
+ outfile_path = "3_visualize/out/perc_pop_under_60_plus_2022.png",
+ pal = "OrRd",
+ leg_title = "Percent of Total Poulation\n60 years & plus, 2022",
+ width = 6,
+ height = 4,
+ dpi = 300,
+ counties_outline_col = "grey80",
+ conus_outline_col = 'grey50',
+ bg_col = "white",
+ load_font = 'Source Sans Pro',
+ font_size = 10
+ ),
+ format = "file"
+ ),
+ # percent income maps
+ tar_target(
+ p3_perc_household_income_map_png,
+ plot_census_map(
+ census_data = p2_census_acs5sub_income_data[[1]],
+ percent_leg = TRUE,
+ var = 'percent',
+ conus_sf = p1_conus_sf,
+ outfile_path = "3_visualize/out/perc_household_income_2022.png",
+ pal = "OrRd",
+ leg_title = "Percent allocated\nhousehold income\nin the past 12 months, 2022",
+ width = 6,
+ height = 4,
+ dpi = 300,
+ counties_outline_col = "grey80",
+ conus_outline_col = 'grey50',
+ bg_col = "white",
+ load_font = 'Source Sans Pro',
+ font_size = 10
+ ),
+ format = "file"
+ ),
+ tar_target(
+ # empty map
+ p3_perc_family_income_map_png,
+ plot_census_map(
+ census_data = p2_census_acs5sub_income_data[[2]],
+ percent_leg = TRUE,
+ var = 'percent',
+ conus_sf = p1_conus_sf,
+ outfile_path = "3_visualize/out/perc_family_income_2022.png",
+ pal = "OrRd",
+ leg_title = "Percent allocated\family income\nin the past 12 months, 2022",
+ width = 6,
+ height = 4,
+ dpi = 300,
+ counties_outline_col = "grey80",
+ conus_outline_col = 'grey50',
+ bg_col = "white",
+ load_font = 'Source Sans Pro',
+ font_size = 10
+ ),
+ format = "file"
+ ),
+ tar_target(
+ # empty map
+ p3_perc_nonfamily_income_map_png,
+ plot_census_map(
+ census_data = p2_census_acs5sub_income_data[[3]],
+ percent_leg = TRUE,
+ var = 'percent',
+ conus_sf = p1_conus_sf,
+ outfile_path = "3_visualize/out/perc_nonfamily_income_2022.png",
+ pal = "OrRd",
+ leg_title = "Percent allocated\nonfamily income\nin the past 12 months, 2022",
+ width = 6,
+ height = 4,
+ dpi = 300,
+ counties_outline_col = "grey80",
+ conus_outline_col = 'grey50',
+ bg_col = "white",
+ load_font = 'Source Sans Pro',
+ font_size = 10
+ ),
+ format = "file"
+ ),
+ # education related map
+ tar_target(
+ p3_tot_18_24_highschool_education_map_png,
+ plot_census_map(
+ census_data = p2_census_acs5sub_education_data[[1]],
+ percent_leg = FALSE,
+ var = 'estimate',
+ conus_sf = p1_conus_sf,
+ outfile_path = "3_visualize/out/tot_education_18-24_highschool_2022.png",
+ pal = "OrRd",
+ leg_title = "Total population 18-24 years\nHigh school graduate (includes equivalency), 2022",
+ width = 6,
+ height = 4,
+ dpi = 300,
+ counties_outline_col = "grey80",
+ conus_outline_col = 'grey50',
+ bg_col = "white",
+ load_font = 'Source Sans Pro',
+ font_size = 10
+ ),
+ format = "file"
+ ),
+ tar_target(
+ p3_tot_25_plus_highschool_education_map_png,
+ plot_census_map(
+ census_data = p2_census_acs5sub_education_data[[2]],
+ percent_leg = FALSE,
+ var = 'estimate',
+ conus_sf = p1_conus_sf,
+ outfile_path = "3_visualize/out/tot_education_25-plus_highschool_2022.png",
+ pal = "OrRd",
+ leg_title = "Total population 25 and older\nHigh school graduate (includes equivalency), 2022",
+ width = 6,
+ height = 4,
+ dpi = 300,
+ counties_outline_col = "grey80",
+ conus_outline_col = 'grey50',
+ bg_col = "white",
+ load_font = 'Source Sans Pro',
+ font_size = 10
+ ),
+ format = "file"
)
)
\ No newline at end of file
diff --git a/3_visualize/src/plot_utils.R b/3_visualize/src/plot_utils.R
index 89e1440f41be5ae1dfd6086944c9b7fdfd95f6bd..b62a0f7aa5746d6aae25d50c26192e5fab63d69f 100644
--- a/3_visualize/src/plot_utils.R
+++ b/3_visualize/src/plot_utils.R
@@ -12,14 +12,15 @@
#' @param conus_outline_col, assign color to conus outline
#' @param bg_col, assign background color for maps
#' @param load_font, assign font name
+#' @param percent_leg if else statement where if TRUE, apply 0-100 legend, otherwise retain 0 - max of variable name
plot_census_map <- function(census_data, conus_sf, pal, leg_title, outfile_path, width, height, dpi,
- counties_outline_col, conus_outline_col, bg_col, load_font, font_size, var){
+ counties_outline_col, conus_outline_col, bg_col, load_font, font_size, var, percent_leg){
font_legend <- load_font
font_add_google(font_legend)
showtext_opts(dpi = 300, regular.wt = 200, bold.wt = 700)
showtext_auto(enable = TRUE)
-
+
census_map <- census_data |>
ggplot(aes(fill = .data[[var]])) +
geom_sf(color = counties_outline_col,
@@ -30,15 +31,28 @@ plot_census_map <- function(census_data, conus_sf, pal, leg_title, outfile_path,
linewidth = 0.2,
linetype = "solid") +
theme_void() +
- scale_fill_distiller(
- palette = pal,
- direction = 1,
- name = leg_title,
- limits = c(0, max(census_data[[var]], na.rm = TRUE)),
- labels = scales::comma) +
theme(text = element_text(family = font_legend, size = font_size),
legend.margin = margin(r = 10))
+ if (percent_leg == FALSE) {
+ census_map <- census_map +
+ scale_fill_distiller(
+ palette = pal,
+ direction = 1,
+ name = leg_title,
+ limits = c(0, max(census_data[[var]], na.rm = TRUE)),
+ labels = scales::comma)
+
+ } else {
+ census_map <- census_map +
+ scale_fill_distiller(
+ palette = pal,
+ direction = 1,
+ name = leg_title,
+ limits = c(0, 100),
+ breaks = c(0, 25, 50, 75, 100)
+ )
+ }
ggsave(outfile_path, census_map, width = width, height = height, dpi = dpi, bg = bg_col)
return(outfile_path)