3_visualize.R

source('3_visualize/src/plot_utils.R')


# For case studies approach: select one demographic characteristic (hispanic/latino), 
p3_targets <- list(
  tar_target(
    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,
      outfile_path = "3_visualize/out/med_income_census_2022.png",
      leg_title = "Median household income, 2022",
      viz_config_df = p0_viz_config_df,
      viz_config_pal = p0_viz_config_pal$socioeconomic_status,
      width = p0_viz_config_df$width_desktop,
      height = p0_viz_config_df$height_desktop,
      font_size  = p0_viz_config_df$font_size_desktop,
      barwidth = 20,
      barheight = 1
    ),
    format = "file"
  ),
  tar_target(
    p3_perc_latino_png,
    plot_census_map(
      census_data = p2_perc_census_acs5_layers_sf[[4]],
      percent_leg = TRUE,
      lim_vals = c(0, 100),
      break_vals = c(0, 25, 50, 75, 100),
      var = 'percent',
      conus_sf = p1_conus_sf,
      outfile_path = "3_visualize/out/perc_hispanic_census_2022.png",
      leg_title = "Percent Hispanic, 2022",
      viz_config_df = p0_viz_config_df,
      viz_config_pal = p0_viz_config_pal$demographic_characteristics,
      width = p0_viz_config_df$width_desktop,
      height = p0_viz_config_df$height_desktop,
      font_size  = p0_viz_config_df$font_size_desktop,
      barwidth = 20,
      barheight = 1
    ),
    format = "file"
  ),
  tar_target(
    p3_avg_household_size_png,
    plot_census_map(
      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/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,
      height = p0_viz_config_df$height_desktop,
      font_size  = p0_viz_config_df$font_size_desktop,
      barwidth = 20,
      barheight = 1
    ),
    format = "file"
  ),
  tar_target(
    p3_median_rent_png,
    plot_census_map(
      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",
      leg_title = "Median gross rent, 2022",
      viz_config_df = p0_viz_config_df,
      viz_config_pal = p0_viz_config_pal$land_tenure,
      width = p0_viz_config_df$width_desktop,
      height = p0_viz_config_df$height_desktop,
      font_size  = p0_viz_config_df$font_size_desktop,
      barwidth = 20,
      barheight = 1
    ),
    format = "file"
  ),
  tar_target(
  p3_perc_disable_png,
  plot_census_map(
    census_data = p2_census_acs5sub_disability_data[[1]],
    percent_leg = TRUE,
    lim_vals = c(0, 50),
    break_vals = c(0, 10, 20, 30, 40, 50),
    var = 'estimate',
    conus_sf = p1_conus_sf,
    outfile_path = "3_visualize/out/perc_disabled_census_2022.png",
    leg_title = "Percent disabled, 2022",
    viz_config_df = p0_viz_config_df,
    viz_config_pal = p0_viz_config_pal$demographic_characteristics,
    width = p0_viz_config_df$width_desktop,
    height = p0_viz_config_df$height_desktop,
    font_size  = p0_viz_config_df$font_size_desktop,
    barwidth = 20,
    barheight = 1
    ),
  format = "file"
)
)