additional maps for median income by race

2_process.R

@@ -163,5 +163,14 @@ tar_target(p2_census_acs5sub_household_data,
                            states = p1_census_states, year = 2022, proj = p1_proj, 
                            survey_var = "acs5", percent_rename = FALSE),
            pattern = map(p2_census_acs5_household_layers),
+           iteration = "list"),
+# Median Household Income in the Past 12 Months (in 2022 Inflation-Adjusted Dollars) for white only, Black or African American Alone, American Indian and Alaska Native Alone, Asian Alone, Native Hawaiian and Other Pacific Islander Alone, Hispanic or Latino
+tar_target(p2_census_acs5_income_by_race_layers,
+           c("B19013A_001", "B19013B_001", "B19013C_001", "B19013D_001", "B19013E_001", "B19013I_001")),
+tar_target(p2_census_acs5sub_income_by_race_data,
+           get_census_data(geography = 'county', variable = p2_census_acs5_income_by_race_layers,
+                           states = p1_census_states, year = 2022, proj = p1_proj, 
+                           survey_var = "acs5", percent_rename = FALSE),
+           pattern = map(p2_census_acs5_income_by_race_layers),
            iteration = "list")
 )
\ No newline at end of file

3_visualize.R

 source('3_visualize/src/plot_utils.R')
+
+
 # For case studies approach: select one demographic characteristic (hispanic/latino), 
 p3_targets <- list(
+
+# desktop maps ------------------------------------------------------------
   tar_target(
     p3_med_income_png,
     plot_census_map(
@@ -139,8 +143,129 @@ p3_targets <- list(
     ),
     format = "file"
   ),
-  # Mobile maps
-  tar_target(
+
+# median income by race maps
+tar_target(
+  p3_med_income_white_png,
+  plot_census_map(
+    census_data = p2_census_acs5sub_income_by_race_data[[1]],
+    percent_leg = FALSE,
+    var = 'estimate',
+    conus_sf = p1_conus_sf,
+    outfile_path = "3_visualize/out/med_income_census_white_2022.png",
+    leg_title = "Median Household Income in the Past 12 Months\n(in 2022 Inflation-Adjusted Dollars),\nWhite Householder",
+    viz_config_df = p0_viz_config_df,
+    viz_config_pal = p0_viz_config_pal$pal_positive,
+    width = p0_viz_config_df$width_desktop,
+    height = p0_viz_config_df$height_desktop,
+    font_size  = p0_viz_config_df$font_size_desktop,
+    barwidth = 40,
+    barheight = 2
+  ),
+  format = "file"
+),
+
+tar_target(
+  p3_med_income_black_png,
+  plot_census_map(
+    census_data = p2_census_acs5sub_income_by_race_data[[2]],
+    percent_leg = FALSE,
+    var = 'estimate',
+    conus_sf = p1_conus_sf,
+    outfile_path = "3_visualize/out/med_income_census_black_2022.png",
+    leg_title = "Median Household Income in the Past 12 Months\n(in 2022 Inflation-Adjusted Dollars),\nBlack or African American Householder",
+    viz_config_df = p0_viz_config_df,
+    viz_config_pal = p0_viz_config_pal$pal_positive,
+    width = p0_viz_config_df$width_desktop,
+    height = p0_viz_config_df$height_desktop,
+    font_size  = p0_viz_config_df$font_size_desktop,
+    barwidth = 40,
+    barheight = 2
+  ),
+  format = "file"
+),
+
+tar_target(
+  p3_med_income_american_indian_png,
+  plot_census_map(
+    census_data = p2_census_acs5sub_income_by_race_data[[3]],
+    percent_leg = FALSE,
+    var = 'estimate',
+    conus_sf = p1_conus_sf,
+    outfile_path = "3_visualize/out/med_income_census_american_indian_2022.png",
+    leg_title = "Median Household Income in the Past 12 Months\n(in 2022 Inflation-Adjusted Dollars),\nAmerican Indian and Alaska Native Householder",
+    viz_config_df = p0_viz_config_df,
+    viz_config_pal = p0_viz_config_pal$pal_positive,
+    width = p0_viz_config_df$width_desktop,
+    height = p0_viz_config_df$height_desktop,
+    font_size  = p0_viz_config_df$font_size_desktop,
+    barwidth = 40,
+    barheight = 2
+  ),
+  format = "file"
+),
+
+tar_target(
+  p3_med_income_asian_png,
+  plot_census_map(
+    census_data = p2_census_acs5sub_income_by_race_data[[4]],
+    percent_leg = FALSE,
+    var = 'estimate',
+    conus_sf = p1_conus_sf,
+    outfile_path = "3_visualize/out/med_income_census_asian_2022.png",
+    leg_title = "Median Household Income in the Past 12 Months\n(in 2022 Inflation-Adjusted Dollars),\nAsian Householder",
+    viz_config_df = p0_viz_config_df,
+    viz_config_pal = p0_viz_config_pal$pal_positive,
+    width = p0_viz_config_df$width_desktop,
+    height = p0_viz_config_df$height_desktop,
+    font_size  = p0_viz_config_df$font_size_desktop,
+    barwidth = 40,
+    barheight = 2
+  ),
+  format = "file"
+),
+
+tar_target(
+  p3_med_income_hawaiian_png,
+  plot_census_map(
+    census_data = p2_census_acs5sub_income_by_race_data[[5]],
+    percent_leg = FALSE,
+    var = 'estimate',
+    conus_sf = p1_conus_sf,
+    outfile_path = "3_visualize/out/med_income_census_hawaiian_2022.png",
+    leg_title = "Median Household Income in the Past 12 Months\n(in 2022 Inflation-Adjusted Dollars),\nNative Hawaiian and\n Other Pacific Islander Householder",
+    viz_config_df = p0_viz_config_df,
+    viz_config_pal = p0_viz_config_pal$pal_positive,
+    width = p0_viz_config_df$width_desktop,
+    height = p0_viz_config_df$height_desktop,
+    font_size  = p0_viz_config_df$font_size_desktop,
+    barwidth = 40,
+    barheight = 2
+  ),
+  format = "file"
+),
+
+tar_target(
+  p3_med_income_hispanic_png,
+  plot_census_map(
+    census_data = p2_census_acs5sub_income_by_race_data[[6]],
+    percent_leg = FALSE,
+    var = 'estimate',
+    conus_sf = p1_conus_sf,
+    outfile_path = "3_visualize/out/med_income_census_hispanic_2022.png",
+    leg_title = "Median Household Income in the Past 12 Months\n(in 2022 Inflation-Adjusted Dollars),\nHispanic or Latino Householder",
+    viz_config_df = p0_viz_config_df,
+    viz_config_pal = p0_viz_config_pal$pal_positive,
+    width = p0_viz_config_df$width_desktop,
+    height = p0_viz_config_df$height_desktop,
+    font_size  = p0_viz_config_df$font_size_desktop,
+    barwidth = 40,
+    barheight = 2
+  ),
+  format = "file"
+),
+# mobile maps -------------------------------------------------------------
+    tar_target(
     p3_med_income_mobile_png,
     plot_census_map(
       census_data = p2_perc_census_acs5_layers_sf[[2]],
@@ -178,6 +303,9 @@ p3_targets <- list(
     ),
     format = "file"
   ),
+
+# mobile maps -------------------------------------------------------------
+
   
   tar_target(
     p3_tot_latino_mobile_png,

3_visualize/src/plot_utils.R

@@ -50,7 +50,7 @@ plot_census_map <- function(census_data, conus_sf, leg_title, outfile_path, var,
     name = leg_title,
     limits = c(0, max(census_data[[var]], na.rm = TRUE)),
     labels = scales::comma,
-    na.value="white") 
+    na.value="#F5F5F5") 
   
  } else {
    census_map <- census_map +     
@@ -60,7 +60,7 @@ plot_census_map <- function(census_data, conus_sf, leg_title, outfile_path, var,
        name = leg_title,
        limits = c(0, 100),
        breaks = c(0, 25, 50, 75, 100),
-       na.value="white"
+       na.value="#F5F5F5"
      )
  }
   ggsave(outfile_path, census_map, width = width, height = height, dpi = viz_config_df$dpi, bg = viz_config_df$bg_col, units = "in")