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p3_targets <- list(
tar_target(
p3_med_income_png,
plot_census_map(
census_data = p2_med_income_sf,
var = 'estimate',
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/med_income_census_2022.png",
pal = "OrRd",
leg_title = "Median household income\n2022",
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"
),
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tar_target(
p3_tot_black_png,
plot_census_map(
census_data = p2_tot_black_sf,
var = 'estimate',
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/tot_black_census_2022.png",
pal = "OrRd",
leg_title = "Total Black\n2022",
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_black_png,
plot_census_map(
census_data = p2_perc_black_sf,
var = 'percent',
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/perc_black_census_2022.png",
pal = "OrRd",
leg_title = "Percent Black\n2022",
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_latino_png,
plot_census_map(
census_data = p2_tot_latino_sf,
var = 'estimate',
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/tot_latino_census_2022.png",
pal = "OrRd",
leg_title = "Total Latino\n2022",
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_latino_png,
plot_census_map(
census_data = p2_perc_latino_sf,
var = 'percent',
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/perc_latino_census_2022.png",
pal = "OrRd",
leg_title = "Percent Latino\n2022",
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_male_png,
plot_census_map(
census_data = p2_tot_male_sf,
var = 'estimate',
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/tot_male_census_2022.png",
pal = "OrRd",
leg_title = "Total Male\n2022",
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_female_png,
plot_census_map(
census_data = p2_tot_female_sf,
var = 'estimate',
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/tot_female_census_2022.png",
pal = "OrRd",
leg_title = "Total Female\n2022",
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"
)