ryanburge/ct_selection_untitled-4FF6038D.R Secret

## ct_selection_untitled-4FF6038D.R
ess <- read_csv("E://data/ess11.csv") %>% select(-name)

country_names <- tibble(
  cntry = c("AL", "AT", "BE", "BG", "CH", "CY", "CZ", "DE", "DK", "EE", "ES", "FI", "FR", "GB", "GE", "GR", "HR", "HU", "IE", "IS", "IL", "IT", "LT", "LU", "LV", "ME", "MK", "NL", "NO", "PL", "PT", "RO", "RS", "RU", "SE", "SI", "SK", "TR", "UA", "XK"),
  country = c("Albania", "Austria", "Belgium", "Bulgaria", "Switzerland", "Cyprus", "Czechia", "Germany", "Denmark", "Estonia", "Spain", "Finland", "France", "United Kingdom", "Georgia", "Greece", "Croatia", "Hungary", "Ireland", "Iceland", "Israel", "Italy", "Lithuania", "Luxembourg", "Latvia", "Montenegro", "North Macedonia", "Netherlands", "Norway", "Poland", "Portugal", "Romania", "Serbia", "Russian Federation", "Sweden", "Slovenia", "Slovakia", "Turkey", "Ukraine", "Kosovo")
)

ess <- ess %>%
  left_join(country_names, by = "cntry")

rel <- ess %>%
  group_by(country) %>%
  mutate(bel = rlgblg)  %>%
  mutate(bel = case_when(bel == 1 ~ 1,
                         bel == 2 ~ 0)) %>%
  mean_ci(bel, wt = weighta, ci = .84)

custom_palette <- c(
  "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00",
  "#FFFF33", "#A65628", "#F781BF", "#999999", "#66C2A5",
  "#FC8D62", "#8DA0CB", "#E78AC3"
)

rel  %>%
  mutate(lab = round(mean, 2)) %>%
  ggplot(., aes(x = reorder(country, mean),  y = mean, fill = country)) +
  geom_col(color = "black") +
  coord_flip() +
  theme_rb() +
  scale_fill_manual(values = custom_palette) +
  error_bar() +
  y_pct() +
  geom_text(aes(y = .035, label = paste0(lab*100, '%')), position = position_dodge(width = .9), size = 7, family = "font") +
  labs(x = "", y = "Share Saying Yes", title = "Do you consider yourself as belonging to any particular religion or denomination?", caption = "@ryanburge\nData: European Social Survey, 2023-24")
save("ess_23_rel_belong.png")

gg <- ess %>%
  mutate(rel = rlgdnm) %>%
  mutate(rel = frcode(rel == 2 ~ "Protestant",
                      rel == 1 ~ "Roman Catholic",
                      rel == 6 ~ "Islam",
                      rel == 66 ~ "No Religion",
                      TRUE ~ "All Others")) %>%
  group_by(country) %>%
  ct(rel, wt = weighta, show_na = FALSE)


lvl <- gg %>%
  filter(rel == "Protestant" | rel == "Roman Catholic") %>%
  group_by(country) %>%
  summarise(sum = sum(pct)) %>%
  select(country, sort = sum)

gg <- left_join(gg, lvl)

gg$country <- fct_reorder(gg$country, gg$sort, .desc = TRUE)

gg %>%
  mutate(lab = round(pct, 2)) %>%
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(rel))) +
  geom_col(color = "black") +
  coord_flip() +
  facet_wrap(~ country, ncol =1, strip.position = "left") +
  theme_rb() +
  scale_fill_manual(values = c(moma.colors("OKeeffe", 5))) +
  theme(legend.position = "bottom") +
  scale_y_continuous(labels = percent) +
  theme(strip.text.y.left = element_text(angle=0)) +
  guides(fill = guide_legend(reverse=T, nrow = 1)) +
  theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) +
  theme(panel.grid.minor.y=element_blank(), panel.grid.major.y=element_blank()) +
  geom_text(aes(label = ifelse(pct >.05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "black") +
  geom_text(aes(label = ifelse(rel == "Protestant" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
  geom_text(aes(label = ifelse(rel == "Roman Catholic" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
  theme(plot.title = element_text(size = 16)) +
  theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) +
  labs(x = "", y = "", title = "The Religious Composition of Thirteen European Countries", caption = "@ryanburge\nData: European Social Survey, 2023-24")
save("ess23_rel_comp.png", wd = 9, ht = 8)

#
# > gg %>% filter(rel == "Islam") %>% arrange(-pct)
# # A tibble: 11 × 5
# # Groups:   country [11]
# country        rel       n   pct  sort
# <fct>          <fct> <dbl> <dbl> <dbl>
#   1 Switzerland    Islam  6341 0.05  0.426
# 2 United Kingdom Islam 17342 0.044 0.326
# 3 Austria        Islam 10549 0.035 0.617
# 4 Norway         Islam  3969 0.03  0.314
# 5 Slovenia       Islam  4153 0.03  0.485
# 6 Netherlands    Islam  4769 0.028 0.24
# 7 Germany        Islam  6677 0.025 0.447
# 8 Croatia        Islam  2424 0.014 0.696
# 9 Ireland        Islam  3184 0.013 0.631
# 10 Finland        Islam   976 0.006 0.489
# 11 Lithuania      Islam    70 0     0.66


gg <- ess %>%
  group_by(country) %>%
  mutate(bel = rlgblg)  %>%
  mutate(bel = case_when(bel == 1 ~ 1,
                         bel == 2 ~ 0)) %>%
  filter(bel == 0) %>%
  mutate(ever = rlgblge)  %>%
  mutate(ever = frcode(ever == 1 ~ "I Once Belonged to a Religious Tradition",
                             ever == 2 ~ "I Never Belonged")) %>%
  ct(ever, wt = weighta, show_na = FALSE)


lvl <- gg %>%
  filter(ever == "I Once Belonged to a Religious Tradition") %>%
  group_by(country) %>%
  select(country, sort = pct)

gg <- left_join(gg, lvl)

gg$country <- fct_reorder(gg$country, gg$sort, .desc = TRUE)


gg %>%
  mutate(lab = round(pct, 2)) %>%
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(ever))) +
  geom_col(color = "black") +
  coord_flip() +
  facet_wrap(~ country, ncol =1, strip.position = "left") +
  theme_rb() +
  scale_fill_calc() +
  theme(legend.position = "bottom") +
  scale_y_continuous(labels = percent) +
  theme(strip.text.y.left = element_text(angle=0)) +
  guides(fill = guide_legend(reverse=T, nrow = 1)) +
  theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) +
  theme(panel.grid.minor.y=element_blank(), panel.grid.major.y=element_blank()) +
  geom_text(aes(label = ifelse(pct >.05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
  # geom_text(aes(label = ifelse(rel == "Protestant" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
  # geom_text(aes(label = ifelse(rel == "Roman Catholic" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
  theme(plot.title = element_text(size = 16)) +
  theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) +
  labs(x = "", y = "", title = "Among Those Who Aren't Religious, Did You Ever Belong to a Tradition?", caption = "@ryanburge\nData: European Social Survey, 2023-24")
save("ess23_rel_ever.png", wd = 9, ht = 8)

library(ggridges)

ess_meaned <- ess %>%
  mutate(imp = rlgdgr) %>%
  filter(imp <= 10) %>%
  group_by(country) %>%
  mutate(mean = mean(imp)) %>%
  ungroup() %>%
  mutate(country = fct_reorder(country, mean))

religion_labels <- c(
  "Not at\nall religious", "1", "2", "3", "4", "5",
  "6", "7", "8", "9", "Very\nreligious")

ess_meaned %>%
  mutate(imp = rlgdgr) %>%
  filter(imp <= 10) %>%
  ggplot() +
  geom_density_ridges(
    aes(x = imp, y = country, fill = country),
    quantile_lines = T, quantile_fun = mean, alpha = .5)  +
  scale_x_continuous(
    breaks = 0:10,
    labels = religion_labels,
    expand = c(0, 0)
  ) +  # scale_y_discrete(expand = c(0, 0)) +     # will generally have to set the `expand` option
  # scale_x_continuous(expand = c(0, 0)) +   # for both axes to remove unneeded padding
  coord_cartesian(clip = "off") +
  theme_rb() +
  scale_fill_manual(values = custom_palette) +
  theme(plot.title = element_text(size = 14)) +
  labs(x = "", y = "", title = "Regardless of whether you belong to a particular religion, how religious would you say you are?", caption = "@ryanburge\nData: European Social Survey, 2023-24")
 save("ridges_ess23.png", ht = 10)


 aa1 <- ess %>%
   mutate(imp = rlgdgr) %>%
   filter(imp <= 10) %>%
   mutate(not = case_when(imp == 0 ~ 1,
                          TRUE ~ 0)) %>%
   group_by(country) %>%
   mean_ci(not, wt = weighta, ci = .84) %>%
   mutate(type = "Not\nAt All")


 aa2 <- ess %>%
   mutate(imp = rlgdgr) %>%
   filter(imp <= 10) %>%
   mutate(not = case_when(imp == 10 ~ 1,
                          TRUE ~ 0)) %>%
   group_by(country) %>%
   mean_ci(not, wt = weighta, ci = .84) %>%
   mutate(type = "Very\nreligious")

 graph <- bind_rows(aa1, aa2)

 graph %>%
   mutate(lab = round(mean, 2)) %>%
   ggplot(., aes(x = type, y = mean, fill = type)) +
   geom_col(color = "black") +
   facet_wrap(~ country, ncol = 5) +
   scale_fill_tableau() +
   labs(x = "", y = "", title = "Share of Each Country At Either End of the Religious Spectrum", caption = "@ryanburge\nData: European Social Survey, 2023-24") +
   y_pct() +
   theme_rb() +
   geom_text(aes(y = mean + .025, label = paste0(lab*100, '%')), position = position_dodge(width = .9), size = 8, family = "font")
 save("ends_imp_ess.png", ht = 10, wd = 8)


 gg <- ess %>%
   mutate(rel = rlgdnm) %>%
   mutate(rel = frcode(rel == 2 ~ "Protestant",
                       rel == 1 ~ "Roman Catholic",
                       rel == 6 ~ "Islam",
                       rel == 66 ~ "No Religion",
                       TRUE ~ "All Others")) %>%
   # group_by(country) %>%
   ct(rel, wt = weighta, show_na = FALSE)


 name <- c("Protestant = 7", "Catholic = 16", "Prot./Catholic = 23", "No Religion = 19")
 num <- c(7, 16, 23, 19)


 graph <- data.frame(name, num)

 graph <- graph %>%
   mutate(name = fct_reorder(name, num))

 graph$name <- factor(graph$name, levels = c("Protestant = 7", "Catholic = 16", "Prot./Catholic = 23", "No Religion = 19"))


 library(waffle)

 graph %>%
   ggplot(., aes(fill = name, values = num)) +
   geom_waffle(color = "white", size = 1.125) +
   facet_wrap(~ name, ncol = 4) +
   coord_equal() +
   theme_rb() +
   theme_enhance_waffle()+
   scale_fill_gdocs() +
   labs(x = "", y  = "", title = "For Each Muslim How Many _____ Are There in Europe?", caption = "@ryanburge\nData: European Social Survey, 2023-24")
 save("waffle_size_muslim_ess.png", wd = 8)

gg <- ess %>%
   mutate(att = rlgatnd) %>%
   mutate(att = frcode(att == 7 ~ "Never",
                       att == 6 ~ "Less Often",
                       att == 5 ~ "Holy Days",
                       att == 4 ~ "Monthly",
                       att == 3 | att == 1 | att == 2 ~ "Weekly")) %>%
   group_by(country) %>%
   ct(att, wt = weighta, show_na = FALSE)


lvl <- gg %>%
  filter(att == "Never") %>%
  group_by(country) %>%
  select(country, sort = pct)

gg <- left_join(gg, lvl)

gg$country <- fct_reorder(gg$country, gg$sort, .desc = TRUE)


gg %>%
  mutate(lab = round(pct, 2)) %>%
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(att))) +
  geom_col(color = "black") +
  coord_flip() +
  facet_wrap(~ country, ncol =1, strip.position = "left") +
  theme_rb() +
  theme(legend.position = "bottom") +
  scale_fill_manual(values = c(moma.colors("ustwo", 6))) +
  scale_y_continuous(labels = percent) +
  theme(strip.text.y.left = element_text(angle=0)) +
  guides(fill = guide_legend(reverse=T, nrow = 1)) +
  theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) +
  theme(panel.grid.minor.y=element_blank(), panel.grid.major.y=element_blank()) +
  geom_text(aes(label = ifelse(pct >.05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "black") +
  # geom_text(aes(label = ifelse(rel == "Protestant" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
  # geom_text(aes(label = ifelse(rel == "Roman Catholic" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
  theme(plot.title = element_text(size = 22)) +
  theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) +
  labs(x = "", y = "", title = "Apart from special occasions such as weddings and funerals,\nabout how often do you attend religious services nowadays?", caption = "@ryanburge\nData: European Social Survey, 2023-24")
save("ess23_attend.png", wd = 9, ht = 8)


gg <- ess %>%
  mutate(pray = frcode(pray == 7 ~ "Never",
                       pray == 6 ~ "Less Often",
                       pray == 5 | pray == 4 ~ "Monthly",
                       pray == 3 | pray == 2 ~ "Weekly",
                       pray == 1 ~ "Daily")) %>%
  # group_by(country) %>%
  ct(pray, wt = weighta, show_na = FALSE)


lvl <- gg %>%
  filter(pray == "Never") %>%
  group_by(country) %>%
  select(country, sort = pct)

gg <- left_join(gg, lvl)

gg$country <- fct_reorder(gg$country, gg$sort, .desc = TRUE)


gg %>%
  mutate(lab = round(pct, 2)) %>%
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(pray))) +
  geom_col(color = "black") +
  coord_flip() +
  facet_wrap(~ country, ncol =1, strip.position = "left") +
  theme_rb() +
  theme(legend.position = "bottom") +
  scale_fill_manual(values = c(met.brewer("Hiroshige", 5))) +
  scale_y_continuous(labels = percent) +
  theme(strip.text.y.left = element_text(angle=0)) +
  guides(fill = guide_legend(reverse=T, nrow = 1)) +
  theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) +
  theme(panel.grid.minor.y=element_blank(), panel.grid.major.y=element_blank()) +
  geom_text(aes(label = ifelse(pct >.05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "black") +
  geom_text(aes(label = ifelse(pray == "Never" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
  # geom_text(aes(label = ifelse(rel == "Roman Catholic" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
  theme(plot.title = element_text(size = 18)) +
  theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) +
  labs(x = "", y = "", title = "Apart from when you are at religious services, how often, if at all, do you pray?", caption = "@ryanburge\nData: European Social Survey, 2023-24")
save("ess23_pray.png", wd = 9, ht = 8)
	ess <- read_csv("E://data/ess11.csv") %>% select(-name)

	country_names <- tibble(
	cntry = c("AL", "AT", "BE", "BG", "CH", "CY", "CZ", "DE", "DK", "EE", "ES", "FI", "FR", "GB", "GE", "GR", "HR", "HU", "IE", "IS", "IL", "IT", "LT", "LU", "LV", "ME", "MK", "NL", "NO", "PL", "PT", "RO", "RS", "RU", "SE", "SI", "SK", "TR", "UA", "XK"),
	country = c("Albania", "Austria", "Belgium", "Bulgaria", "Switzerland", "Cyprus", "Czechia", "Germany", "Denmark", "Estonia", "Spain", "Finland", "France", "United Kingdom", "Georgia", "Greece", "Croatia", "Hungary", "Ireland", "Iceland", "Israel", "Italy", "Lithuania", "Luxembourg", "Latvia", "Montenegro", "North Macedonia", "Netherlands", "Norway", "Poland", "Portugal", "Romania", "Serbia", "Russian Federation", "Sweden", "Slovenia", "Slovakia", "Turkey", "Ukraine", "Kosovo")
	)

	ess <- ess %>%
	left_join(country_names, by = "cntry")

	rel <- ess %>%
	group_by(country) %>%
	mutate(bel = rlgblg) %>%
	mutate(bel = case_when(bel == 1 ~ 1,
	bel == 2 ~ 0)) %>%
	mean_ci(bel, wt = weighta, ci = .84)

	custom_palette <- c(
	"#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00",
	"#FFFF33", "#A65628", "#F781BF", "#999999", "#66C2A5",
	"#FC8D62", "#8DA0CB", "#E78AC3"
	)

	rel %>%
	mutate(lab = round(mean, 2)) %>%
	ggplot(., aes(x = reorder(country, mean), y = mean, fill = country)) +
	geom_col(color = "black") +
	coord_flip() +
	theme_rb() +
	scale_fill_manual(values = custom_palette) +
	error_bar() +
	y_pct() +
	geom_text(aes(y = .035, label = paste0(lab*100, '%')), position = position_dodge(width = .9), size = 7, family = "font") +
	labs(x = "", y = "Share Saying Yes", title = "Do you consider yourself as belonging to any particular religion or denomination?", caption = "@ryanburge\nData: European Social Survey, 2023-24")
	save("ess_23_rel_belong.png")

	gg <- ess %>%
	mutate(rel = rlgdnm) %>%
	mutate(rel = frcode(rel == 2 ~ "Protestant",
	rel == 1 ~ "Roman Catholic",
	rel == 6 ~ "Islam",
	rel == 66 ~ "No Religion",
	TRUE ~ "All Others")) %>%
	group_by(country) %>%
	ct(rel, wt = weighta, show_na = FALSE)


	lvl <- gg %>%
	filter(rel == "Protestant" \| rel == "Roman Catholic") %>%
	group_by(country) %>%
	summarise(sum = sum(pct)) %>%
	select(country, sort = sum)

	gg <- left_join(gg, lvl)

	gg$country <- fct_reorder(gg$country, gg$sort, .desc = TRUE)

	gg %>%
	mutate(lab = round(pct, 2)) %>%
	ggplot(., aes(x = 1, y = pct, fill = fct_rev(rel))) +
	geom_col(color = "black") +
	coord_flip() +
	facet_wrap(~ country, ncol =1, strip.position = "left") +
	theme_rb() +
	scale_fill_manual(values = c(moma.colors("OKeeffe", 5))) +
	theme(legend.position = "bottom") +
	scale_y_continuous(labels = percent) +
	theme(strip.text.y.left = element_text(angle=0)) +
	guides(fill = guide_legend(reverse=T, nrow = 1)) +
	theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) +
	theme(panel.grid.minor.y=element_blank(), panel.grid.major.y=element_blank()) +
	geom_text(aes(label = ifelse(pct >.05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "black") +
	geom_text(aes(label = ifelse(rel == "Protestant" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
	geom_text(aes(label = ifelse(rel == "Roman Catholic" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
	theme(plot.title = element_text(size = 16)) +
	theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) +
	labs(x = "", y = "", title = "The Religious Composition of Thirteen European Countries", caption = "@ryanburge\nData: European Social Survey, 2023-24")
	save("ess23_rel_comp.png", wd = 9, ht = 8)

	#
	# > gg %>% filter(rel == "Islam") %>% arrange(-pct)
	# # A tibble: 11 × 5
	# # Groups: country [11]
	# country rel n pct sort
	# <fct> <fct> <dbl> <dbl> <dbl>
	# 1 Switzerland Islam 6341 0.05 0.426
	# 2 United Kingdom Islam 17342 0.044 0.326
	# 3 Austria Islam 10549 0.035 0.617
	# 4 Norway Islam 3969 0.03 0.314
	# 5 Slovenia Islam 4153 0.03 0.485
	# 6 Netherlands Islam 4769 0.028 0.24
	# 7 Germany Islam 6677 0.025 0.447
	# 8 Croatia Islam 2424 0.014 0.696
	# 9 Ireland Islam 3184 0.013 0.631
	# 10 Finland Islam 976 0.006 0.489
	# 11 Lithuania Islam 70 0 0.66


	gg <- ess %>%
	group_by(country) %>%
	mutate(bel = rlgblg) %>%
	mutate(bel = case_when(bel == 1 ~ 1,
	bel == 2 ~ 0)) %>%
	filter(bel == 0) %>%
	mutate(ever = rlgblge) %>%
	mutate(ever = frcode(ever == 1 ~ "I Once Belonged to a Religious Tradition",
	ever == 2 ~ "I Never Belonged")) %>%
	ct(ever, wt = weighta, show_na = FALSE)


	lvl <- gg %>%
	filter(ever == "I Once Belonged to a Religious Tradition") %>%
	group_by(country) %>%
	select(country, sort = pct)

	gg <- left_join(gg, lvl)

	gg$country <- fct_reorder(gg$country, gg$sort, .desc = TRUE)


	gg %>%
	mutate(lab = round(pct, 2)) %>%
	ggplot(., aes(x = 1, y = pct, fill = fct_rev(ever))) +
	geom_col(color = "black") +
	coord_flip() +
	facet_wrap(~ country, ncol =1, strip.position = "left") +
	theme_rb() +
	scale_fill_calc() +
	theme(legend.position = "bottom") +
	scale_y_continuous(labels = percent) +
	theme(strip.text.y.left = element_text(angle=0)) +
	guides(fill = guide_legend(reverse=T, nrow = 1)) +
	theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) +
	theme(panel.grid.minor.y=element_blank(), panel.grid.major.y=element_blank()) +
	geom_text(aes(label = ifelse(pct >.05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
	# geom_text(aes(label = ifelse(rel == "Protestant" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
	# geom_text(aes(label = ifelse(rel == "Roman Catholic" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
	theme(plot.title = element_text(size = 16)) +
	theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) +
	labs(x = "", y = "", title = "Among Those Who Aren't Religious, Did You Ever Belong to a Tradition?", caption = "@ryanburge\nData: European Social Survey, 2023-24")
	save("ess23_rel_ever.png", wd = 9, ht = 8)

	library(ggridges)

	ess_meaned <- ess %>%
	mutate(imp = rlgdgr) %>%
	filter(imp <= 10) %>%
	group_by(country) %>%
	mutate(mean = mean(imp)) %>%
	ungroup() %>%
	mutate(country = fct_reorder(country, mean))

	religion_labels <- c(
	"Not at\nall religious", "1", "2", "3", "4", "5",
	"6", "7", "8", "9", "Very\nreligious")

	ess_meaned %>%
	mutate(imp = rlgdgr) %>%
	filter(imp <= 10) %>%
	ggplot() +
	geom_density_ridges(
	aes(x = imp, y = country, fill = country),
	quantile_lines = T, quantile_fun = mean, alpha = .5) +
	scale_x_continuous(
	breaks = 0:10,
	labels = religion_labels,
	expand = c(0, 0)
	) + # scale_y_discrete(expand = c(0, 0)) + # will generally have to set the `expand` option
	# scale_x_continuous(expand = c(0, 0)) + # for both axes to remove unneeded padding
	coord_cartesian(clip = "off") +
	theme_rb() +
	scale_fill_manual(values = custom_palette) +
	theme(plot.title = element_text(size = 14)) +
	labs(x = "", y = "", title = "Regardless of whether you belong to a particular religion, how religious would you say you are?", caption = "@ryanburge\nData: European Social Survey, 2023-24")
	save("ridges_ess23.png", ht = 10)


	aa1 <- ess %>%
	mutate(imp = rlgdgr) %>%
	filter(imp <= 10) %>%
	mutate(not = case_when(imp == 0 ~ 1,
	TRUE ~ 0)) %>%
	group_by(country) %>%
	mean_ci(not, wt = weighta, ci = .84) %>%
	mutate(type = "Not\nAt All")


	aa2 <- ess %>%
	mutate(imp = rlgdgr) %>%
	filter(imp <= 10) %>%
	mutate(not = case_when(imp == 10 ~ 1,
	TRUE ~ 0)) %>%
	group_by(country) %>%
	mean_ci(not, wt = weighta, ci = .84) %>%
	mutate(type = "Very\nreligious")

	graph <- bind_rows(aa1, aa2)

	graph %>%
	mutate(lab = round(mean, 2)) %>%
	ggplot(., aes(x = type, y = mean, fill = type)) +
	geom_col(color = "black") +
	facet_wrap(~ country, ncol = 5) +
	scale_fill_tableau() +
	labs(x = "", y = "", title = "Share of Each Country At Either End of the Religious Spectrum", caption = "@ryanburge\nData: European Social Survey, 2023-24") +
	y_pct() +
	theme_rb() +
	geom_text(aes(y = mean + .025, label = paste0(lab*100, '%')), position = position_dodge(width = .9), size = 8, family = "font")
	save("ends_imp_ess.png", ht = 10, wd = 8)


	gg <- ess %>%
	mutate(rel = rlgdnm) %>%
	mutate(rel = frcode(rel == 2 ~ "Protestant",
	rel == 1 ~ "Roman Catholic",
	rel == 6 ~ "Islam",
	rel == 66 ~ "No Religion",
	TRUE ~ "All Others")) %>%
	# group_by(country) %>%
	ct(rel, wt = weighta, show_na = FALSE)



	name <- c("Protestant = 7", "Catholic = 16", "Prot./Catholic = 23", "No Religion = 19")
	num <- c(7, 16, 23, 19)



	graph <- data.frame(name, num)

	graph <- graph %>%
	mutate(name = fct_reorder(name, num))

	graph$name <- factor(graph$name, levels = c("Protestant = 7", "Catholic = 16", "Prot./Catholic = 23", "No Religion = 19"))


	library(waffle)

	graph %>%
	ggplot(., aes(fill = name, values = num)) +
	geom_waffle(color = "white", size = 1.125) +
	facet_wrap(~ name, ncol = 4) +
	coord_equal() +
	theme_rb() +
	theme_enhance_waffle()+
	scale_fill_gdocs() +
	labs(x = "", y = "", title = "For Each Muslim How Many _____ Are There in Europe?", caption = "@ryanburge\nData: European Social Survey, 2023-24")
	save("waffle_size_muslim_ess.png", wd = 8)

	gg <- ess %>%
	mutate(att = rlgatnd) %>%
	mutate(att = frcode(att == 7 ~ "Never",
	att == 6 ~ "Less Often",
	att == 5 ~ "Holy Days",
	att == 4 ~ "Monthly",
	att == 3 \| att == 1 \| att == 2 ~ "Weekly")) %>%
	group_by(country) %>%
	ct(att, wt = weighta, show_na = FALSE)



	lvl <- gg %>%
	filter(att == "Never") %>%
	group_by(country) %>%
	select(country, sort = pct)

	gg <- left_join(gg, lvl)

	gg$country <- fct_reorder(gg$country, gg$sort, .desc = TRUE)


	gg %>%
	mutate(lab = round(pct, 2)) %>%
	ggplot(., aes(x = 1, y = pct, fill = fct_rev(att))) +
	geom_col(color = "black") +
	coord_flip() +
	facet_wrap(~ country, ncol =1, strip.position = "left") +
	theme_rb() +
	theme(legend.position = "bottom") +
	scale_fill_manual(values = c(moma.colors("ustwo", 6))) +
	scale_y_continuous(labels = percent) +
	theme(strip.text.y.left = element_text(angle=0)) +
	guides(fill = guide_legend(reverse=T, nrow = 1)) +
	theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) +
	theme(panel.grid.minor.y=element_blank(), panel.grid.major.y=element_blank()) +
	geom_text(aes(label = ifelse(pct >.05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "black") +
	# geom_text(aes(label = ifelse(rel == "Protestant" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
	# geom_text(aes(label = ifelse(rel == "Roman Catholic" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
	theme(plot.title = element_text(size = 22)) +
	theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) +
	labs(x = "", y = "", title = "Apart from special occasions such as weddings and funerals,\nabout how often do you attend religious services nowadays?", caption = "@ryanburge\nData: European Social Survey, 2023-24")
	save("ess23_attend.png", wd = 9, ht = 8)


	gg <- ess %>%
	mutate(pray = frcode(pray == 7 ~ "Never",
	pray == 6 ~ "Less Often",
	pray == 5 \| pray == 4 ~ "Monthly",
	pray == 3 \| pray == 2 ~ "Weekly",
	pray == 1 ~ "Daily")) %>%
	# group_by(country) %>%
	ct(pray, wt = weighta, show_na = FALSE)




	lvl <- gg %>%
	filter(pray == "Never") %>%
	group_by(country) %>%
	select(country, sort = pct)

	gg <- left_join(gg, lvl)

	gg$country <- fct_reorder(gg$country, gg$sort, .desc = TRUE)


	gg %>%
	mutate(lab = round(pct, 2)) %>%
	ggplot(., aes(x = 1, y = pct, fill = fct_rev(pray))) +
	geom_col(color = "black") +
	coord_flip() +
	facet_wrap(~ country, ncol =1, strip.position = "left") +
	theme_rb() +
	theme(legend.position = "bottom") +
	scale_fill_manual(values = c(met.brewer("Hiroshige", 5))) +
	scale_y_continuous(labels = percent) +
	theme(strip.text.y.left = element_text(angle=0)) +
	guides(fill = guide_legend(reverse=T, nrow = 1)) +
	theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) +
	theme(panel.grid.minor.y=element_blank(), panel.grid.major.y=element_blank()) +
	geom_text(aes(label = ifelse(pct >.05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "black") +
	geom_text(aes(label = ifelse(pray == "Never" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
	# geom_text(aes(label = ifelse(rel == "Roman Catholic" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
	theme(plot.title = element_text(size = 18)) +
	theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) +
	labs(x = "", y = "", title = "Apart from when you are at religious services, how often, if at all, do you pray?", caption = "@ryanburge\nData: European Social Survey, 2023-24")
	save("ess23_pray.png", wd = 9, ht = 8)