From 001b17b89de9ddb0aaa03778fb1ff2c3c3f809db Mon Sep 17 00:00:00 2001
From: elmeraa <eazadpour@usgs.gov>
Date: Fri, 22 Mar 2024 09:56:07 -0700
Subject: [PATCH] update maps
---
3_visualize.R | 311 ++++++++++++++++++++---------------
3_visualize/src/plot_utils.R | 10 +-
2 files changed, 185 insertions(+), 136 deletions(-)
diff --git a/3_visualize.R b/3_visualize.R
index 5047d30..d0bcfb3 100644
--- a/3_visualize.R
+++ b/3_visualize.R
@@ -1,48 +1,63 @@
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]],
percent_leg = FALSE,
- var = 'estimate',
- conus_sf = p1_conus_sf,
+ 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 = viz_config_df
- ),
- format = "file"
- ),
-
- tar_target(
- p3_tot_black_png,
- plot_census_map(
- 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",
- leg_title = "Total Black, 2022",
- viz_config_df = viz_config_df
+ viz_config_df = viz_config_df,
+ viz_config_pal = viz_config_pal$pal_positive
),
format = "file"
),
-
-
tar_target(
- p3_perc_black_png,
+ p3_perc_household_income_map_png,
plot_census_map(
- census_data = p2_perc_census_acs5_layers_sf[[3]],
+ census_data = p2_census_acs5sub_income_data[[1]],
percent_leg = TRUE,
- var = 'percent',
+ var = 'percent',
conus_sf = p1_conus_sf,
- outfile_path = "3_visualize/out/perc_black_census_2022.png",
- leg_title = "Percent Black, 2022",
- viz_config_df = viz_config_df
+ outfile_path = "3_visualize/out/perc_household_income_2022.png",
+ leg_title = "Percent allocated household income in the past 12 months, 2022",
+ viz_config_df = viz_config_df,
+ viz_config_pal = viz_config_pal$pal_positive
),
format = "file"
),
+ #
+ # tar_target(
+ # p3_tot_black_png,
+ # plot_census_map(
+ # 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",
+ # leg_title = "Total Black, 2022",
+ # viz_config_df = viz_config_df,
+ # viz_config_pal = viz_config_pal$pal_positive
+ # ),
+ # format = "file"
+ # ),
+ # tar_target(
+ # p3_perc_black_png,
+ # plot_census_map(
+ # census_data = p2_perc_census_acs5_layers_sf[[3]],
+ # percent_leg = TRUE,
+ # var = 'percent',
+ # conus_sf = p1_conus_sf,
+ # outfile_path = "3_visualize/out/perc_black_census_2022.png",
+ # leg_title = "Percent Black, 2022",
+ # viz_config_df = viz_config_df,
+ # viz_config_pal = viz_config_pal$pal_positive
+ # ),
+ # format = "file"
+ # ),
tar_target(
p3_tot_latino_png,
@@ -53,7 +68,8 @@ p3_targets <- list(
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/tot_latino_census_2022.png",
leg_title = "Total Latino, 2022",
- viz_config_df = viz_config_df
+ viz_config_df = viz_config_df,
+ viz_config_pal = viz_config_pal$pal_positive
),
format = "file"
),
@@ -67,131 +83,162 @@ p3_targets <- list(
conus_sf = p1_conus_sf,
outfile_path = "3_visualize/out/perc_latino_census_2022.png",
leg_title = "Percent Latino, 2022",
- viz_config_df = viz_config_df
+ viz_config_df = viz_config_df,
+ viz_config_pal = viz_config_pal$pal_positive
),
format = "file"
),
- tar_target(
- p3_tot_male_png,
- plot_census_map(
- 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",
- leg_title = "Total Male, 2022",
- viz_config_df = viz_config_df
- ),
- format = "file"
- ),
+ # tar_target(
+ # p3_tot_male_png,
+ # plot_census_map(
+ # 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",
+ # leg_title = "Total Male, 2022",
+ # viz_config_df = viz_config_df
+ # ),
+ # format = "file"
+ # ),
+ #
+ # tar_target(
+ # p3_tot_female_png,
+ # plot_census_map(
+ # 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",
+ # leg_title = "Total Female, 2022",
+ # viz_config_df = viz_config_df,
+ # viz_config_pal = viz_config_pal$pal_positive
+ # ),
+ # 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",
+ # leg_title = "Percent of Total Poulation Under 18, 2022",
+ # viz_config_df = viz_config_df
+ # ),
+ # 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",
+ # leg_title = "Percent of Total Poulation 18-24 years, 2022",
+ # viz_config_df = viz_config_df
+ # ),
+ # 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",
+ # leg_title = "Percent of Total Poulation 15-44 years, 2022",
+ # viz_config_df = viz_config_df
+ # ),
+ # 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",
+ # leg_title = "Percent of Total Poulation 60 years & plus, 2022",
+ # viz_config_df = viz_config_df
+ # ),
+ # 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",
+ # leg_title = "Total population 18-24 years\nhigh school graduate (includes equivalency), 2022",
+ # viz_config_df = viz_config_df
+ # ),
+ # 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",
+ # leg_title = "Total population 25 and older\nhigh school graduate (includes equivalency), 2022",
+ # viz_config_df = viz_config_df
+ # ),
+ # format = "file"
+ # ),
+ # Household related maps
tar_target(
- p3_tot_female_png,
+ p3_total_households_png,
plot_census_map(
- census_data = p2_perc_census_acs5_layers_sf[[6]],
+ census_data = p2_census_acs5sub_household_data[[1]],
percent_leg = FALSE,
- var = 'estimate',
- conus_sf = p1_conus_sf,
- outfile_path = "3_visualize/out/tot_female_census_2022.png",
- leg_title = "Total Female, 2022",
- viz_config_df = viz_config_df
- ),
- 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",
- leg_title = "Percent of Total Poulation Under 18, 2022",
- viz_config_df = viz_config_df
- ),
- 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",
- leg_title = "Percent of Total Poulation 18-24 years, 2022",
- viz_config_df = viz_config_df
- ),
- 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",
- leg_title = "Percent of Total Poulation 15-44 years, 2022",
- viz_config_df = viz_config_df
- ),
- 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",
- leg_title = "Percent of Total Poulation 60 years & plus, 2022",
- viz_config_df = viz_config_df
- ),
- 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",
- leg_title = "Percent allocated household income in the past 12 months, 2022",
- viz_config_df = viz_config_df
+ var = 'estimate',
+ conus_sf = p1_conus_sf,
+ outfile_path = "3_visualize/out/tot_households_2022.png",
+ leg_title = "Total households, 2022",
+ viz_config_df = viz_config_df,
+ viz_config_pal = viz_config_pal$pal_positive
),
format = "file"
),
- # education related map
tar_target(
- p3_tot_18_24_highschool_education_map_png,
+ p3_female_households_png,
plot_census_map(
- census_data = p2_census_acs5sub_education_data[[1]],
+ census_data = p2_census_acs5sub_household_data[[2]],
percent_leg = FALSE,
- var = 'estimate',
- conus_sf = p1_conus_sf,
- outfile_path = "3_visualize/out/tot_education_18-24_highschool_2022.png",
- leg_title = "Total population 18-24 years\nhigh school graduate (includes equivalency), 2022",
- viz_config_df = viz_config_df
+ var = 'estimate',
+ conus_sf = p1_conus_sf,
+ outfile_path = "3_visualize/out/tot_female_households_2022.png",
+ leg_title = "Total female households, 2022",
+ viz_config_df = viz_config_df,
+ viz_config_pal = viz_config_pal$pal_positive
),
format = "file"
),
tar_target(
- p3_tot_25_plus_highschool_education_map_png,
+ p3_median_rent_png,
plot_census_map(
- census_data = p2_census_acs5sub_education_data[[2]],
+ census_data = p2_census_acs5sub_household_data[[3]],
percent_leg = FALSE,
- var = 'estimate',
- conus_sf = p1_conus_sf,
- outfile_path = "3_visualize/out/tot_education_25-plus_highschool_2022.png",
- leg_title = "Total population 25 and older\nhigh school graduate (includes equivalency), 2022",
- viz_config_df = viz_config_df
+ var = 'estimate',
+ conus_sf = p1_conus_sf,
+ outfile_path = "3_visualize/out/median_rent_2022.png",
+ leg_title = "Median gross rent, 2022",
+ viz_config_df = viz_config_df,
+ viz_config_pal = viz_config_pal$pal_neg
),
format = "file"
)
diff --git a/3_visualize/src/plot_utils.R b/3_visualize/src/plot_utils.R
index 301efbf..3a41230 100644
--- a/3_visualize/src/plot_utils.R
+++ b/3_visualize/src/plot_utils.R
@@ -4,9 +4,11 @@
#' @param conus_sf, sf of conus states outline
#' @param leg_title, character string for legend title
#' @param outfile_path, outfile path for pngs
-#' @param viz_config_df `data.frame` with palette, width, height, counties outline color, conus outline color, background color, font nam, and font size
+#' @param viz_config_df `data.frame` width, height, counties outline color, conus outline color, background color, font nam, and font size
+#' @param viz_config_pal `data.frame` assign colors for postively and negatively correlated dimensions for census maps
+
#' @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, leg_title, outfile_path, font_size, var, percent_leg, viz_config_df){
+plot_census_map <- function(census_data, conus_sf, leg_title, outfile_path, font_size, var, percent_leg, viz_config_df, viz_config_pal){
font_legend <- viz_config_df$load_font
font_add_google(font_legend)
@@ -37,7 +39,7 @@ plot_census_map <- function(census_data, conus_sf, leg_title, outfile_path, font
if (percent_leg == FALSE) {
census_map <- census_map +
scale_fill_distiller(
- palette = viz_config_df$pal,
+ palette = viz_config_pal,
direction = 1,
name = leg_title,
limits = c(0, max(census_data[[var]], na.rm = TRUE)),
@@ -46,7 +48,7 @@ plot_census_map <- function(census_data, conus_sf, leg_title, outfile_path, font
} else {
census_map <- census_map +
scale_fill_distiller(
- palette = viz_config_df$pal,
+ palette = viz_config_pal,
direction = 1,
name = leg_title,
limits = c(0, 100),
--
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