diff --git a/2_process.R b/2_process.R
index 83aa138d786aa147e751ca4316a079770a8366bd..1b5d8716c0deee0a6f3c1580aef8375855384a4e 100644
--- a/2_process.R
+++ b/2_process.R
@@ -158,12 +158,11 @@ tar_target(p2_census_acs5sub_education_data,
            pattern = map(p2_census_acs5sub_education_layers),
            iteration = "list"),
 
-# household related variables
-# S1101_C01_001 = Estimate!!Total!!HOUSEHOLDS!!Total households
-# S1101_C04_001 = Estimate!!Female householder, no spouse present, family household!!HOUSEHOLDS!!Total households
+# household and rent related variables
+# B25010_001 = Estimate!!Average household size --!!Total:Average Household Size of Occupied Housing Units by Tenure
 # B25064_001 = Estimate!!Median gross rent
 tar_target(p2_census_acs5_household_layers,
-           c("S1101_C01_001", "S1101_C04_001", "B25064_001")),
+           c("B25010_001", "B25064_001")),
 tar_target(p2_census_acs5sub_household_data,
            get_census_data(geography = 'county', variable = p2_census_acs5_household_layers,
                            states = p1_census_states, year = 2022, proj = p1_proj, 
diff --git a/3_visualize.R b/3_visualize.R
index 72b5fba2362f17a4049889a32e3aabb74eeda076..16f7a21343476ebcb05e897fd795a674e520580e 100644
--- a/3_visualize.R
+++ b/3_visualize.R
@@ -7,6 +7,7 @@ p3_targets <- list(
     p3_med_income_png,
     plot_census_map(
       census_data = p2_perc_census_acs5_layers_sf[[2]],
+      lim_vals = c(0, 155000),
       percent_leg = FALSE,
       var = 'estimate',
       conus_sf = p1_conus_sf,
@@ -44,16 +45,15 @@ p3_targets <- list(
     format = "file"
   ),
   tar_target(
-    p3_perc_occ_households_png,
+    p3_avg_household_size_png,
     plot_census_map(
-      census_data = p2_census_acs5profile_household_sf,
-      percent_leg = TRUE,
-      lim_vals = c(0, 100),
-      break_vals = c(0, 25, 50, 75, 100),
+      census_data = p2_census_acs5sub_household_data[[1]],
+      percent_leg = FALSE,
+      lim_vals = c(1, 5),
       var = 'estimate',
       conus_sf = p1_conus_sf,
-      outfile_path = "3_visualize/out/perc_occupied_households_2022.png",
-      leg_title = "Percent occupied housing units, 2022",
+      outfile_path = "3_visualize/out/avg_household_size_2022.png",
+      leg_title = "Average household size, 2022",
       viz_config_df = p0_viz_config_df,
       viz_config_pal = p0_viz_config_pal$demographic_characteristics,
       width = p0_viz_config_df$width_desktop,
@@ -67,8 +67,9 @@ p3_targets <- list(
   tar_target(
     p3_median_rent_png,
     plot_census_map(
-      census_data = p2_census_acs5sub_household_data[[3]],
+      census_data = p2_census_acs5sub_household_data[[2]],
       percent_leg = FALSE,
+      lim_vals = c(0, 3000),
       var = 'estimate',
       conus_sf = p1_conus_sf,
       outfile_path = "3_visualize/out/median_rent_2022.png",
diff --git a/3_visualize/src/plot_utils.R b/3_visualize/src/plot_utils.R
index c7e4cdd42bf08e247dc85f588a77073377358dfa..2a3223b359a3495a2291f57374e2e36ec9b926c8 100644
--- a/3_visualize/src/plot_utils.R
+++ b/3_visualize/src/plot_utils.R
@@ -49,7 +49,7 @@ plot_census_map <- function(census_data, conus_sf, leg_title, outfile_path, var,
     scale_fill_gradientn(
     colors = colorRampPalette(c("#eef0ff", viz_config_pal))(100), 
     name = leg_title,
-    limits = c(0, max(census_data[[var]], na.rm = TRUE)),
+    limits = lim_vals,
     labels = scales::comma,
     na.value="#F5F5F5")