ct_selection_untitled-A83DBA4D.R

gg <- cces %>% 
  mutate(gen = frcode(birthyr>= 1901 & birthyr <= 1924 ~ 'Greatest Generation',
                      birthyr>= 1925 & birthyr <= 1945 ~ 'Silent, 1925-1945',
                      birthyr>= 1946 & birthyr <= 1964 ~ 'Boomers, 1946-1964',
                      birthyr>= 1965 & birthyr <= 1976 ~ 'Gen X, 1965-1976',
                      birthyr>= 1977 & birthyr <= 1995 ~ 'Millennials, 1977-1995',
                      birthyr>= 1996 & birthyr <= 2019 ~ 'Gen Z, 1996-')) %>% 
  mutate(nones = case_when(religion == 9 | religion == 10 | religion == 11 ~ 1, TRUE ~ 0)) %>% 
  group_by(year, gen) %>% 
  mean_ci(nones, wt = weight, ci = .84)


gg %>% 
  mutate(lab = round(mean, 2)) %>% 
  filter(gen != "Greatest Generation") %>% 
  filter(year == 2008 | year == 2012 | year == 2016 | year == 2020 | year == 2022| year == 2023 | year == 2024) %>% 
  ggplot(., aes(x = factor(year), y = mean, fill = factor(year))) +
  geom_col(color = "black", position = "dodge") +
  facet_wrap(~ gen) +
  geom_text(aes(y = .03, label = ifelse(gen != "Gen Z, 1996-", paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 5, family = "font")+
  geom_text(aes(y = .03, label = ifelse(gen != "Gen Z, 1996-" & year == 2008, paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 5, family = "font", color = "white")+
  geom_text(aes(y = .03, label = ifelse(gen != "Gen Z, 1996-" & year == 2012, paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 5, family = "font", color = "white")+
  geom_text(aes(y = .035, label = ifelse(gen == "Gen Z, 1996-", paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 5, family = "font")+
  theme_rb() +
  error_bar() +
  scale_fill_manual(values=met.brewer("Renoir", 7)) +
  y_pct() +
  theme(strip.text = element_text(size = 20)) +
  theme(plot.title =  element_text(size = 26)) +
  labs(x = "", y = "", title = "Share Who Have No Religious Affiliation by Generation", caption = "@ryanburge\nData: Cooperative Election Study, 2008-2024") 
save("none_years_gen24.png", wd = 10, ht = 8)



gg1 <- cces %>% 
  mutate(religpew = religion) %>% 
  mutate(trad = frcode(religpew == 1 ~ "Protestant",
                       religpew == 2 ~ "Catholic",
                       religpew == 3 ~ "Mormon",
                       religpew == 4 ~ "Orthodox",
                       religpew == 5 ~ "Jewish",
                       religpew == 6 ~ "Muslim",
                       religpew == 7 ~ "Buddhist",
                       religpew == 8 ~ "Hindu",
                       religpew == 9 ~ "Atheist",
                       religpew == 10 ~ "Agnostic",
                       religpew == 11 ~ "Nothing in Particular", 
                       religpew == 12 ~ "Something Else"))  %>%
  group_by(year) %>% 
  ct(trad, wt = weight, show_na = FALSE) %>% filter(trad == "Atheist" | trad == "Agnostic" | trad == "Nothing in Particular")


gg1 %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = year, y = pct, fill = trad)) +
  geom_col(color = "black") +
  theme_rb(legend = TRUE) +
  scale_fill_gdocs() +
  y_pct() + 
  geom_text(aes(label = paste0(lab*100, '%')), position = position_stack(vjust = 0.5), size = 6.5, family = "font") + 
  theme(plot.title = element_text(size = 24)) +
  labs(x = "", y = "", title = "The Rise of the Nones, 2008-2024", caption = "@ryanburge\nData: Cooperative Election Study, 2008-2024")
save("nones_ces24.png", wd = 10)


gg1 <- cces %>% 
  filter(year == 2008 | year == 2012 | year == 2016 | year == 2020 |  year == 2024) %>% 
  cces_attend(pew_attendance) %>% 
  group_by(year) %>% 
  ct(att, wt = weight, show_na = FALSE)


gg1 %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(att))) +
  geom_col(color = "black") + 
  coord_flip() +
  facet_wrap(~ year, ncol =1, strip.position = "left") +
  theme_rb() +
  scale_fill_manual(values = c(moma.colors("OKeeffe", 6))) +
  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 = 10, family = "font", color = "black") +
  geom_text(aes(label = ifelse(att == "Never" | att == "Seldom", paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 10, family = "font", color = "white") +
  # geom_text(aes(label = ifelse(age2 == "36-44", paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "white") +
  theme(plot.title = element_text(size = 24)) +
  theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) +
  labs(x = "", y = "", title = "Religious Attendance, 2008-2024", caption = "@ryanburge\nData: Cooperative Election Study, 2008-2024") 
save("ces_relattend_2024.png", wd = 9, ht = 5)


gg1 <- cces %>% 
  filter(year == 2008 | year == 2012 | year == 2016 | year == 2020 |  year == 2024) %>% 
  mutate(gen = frcode(birthyr>= 1946 & birthyr <= 1964 ~ 'Boomers',
                      birthyr>= 1965 & birthyr <= 1976 ~ 'Gen X',
                      birthyr>= 1977 & birthyr <= 1995 ~ 'Millennials',
                      birthyr>= 1996 & birthyr <= 2019 ~ 'Gen Z')) %>% 
  mutate(att = frcode(pew_attendance == 6 | pew_attendance == 5 ~ "Never/Seldom", 
                      pew_attendance == 4 | pew_attendance == 3 ~ "Yearly/Monthly", 
                      pew_attendance == 1 | pew_attendance == 2 ~ "Weekly")) %>% 
  group_by(year, gen) %>% 
  ct(att, wt = weight, show_na = FALSE) %>% na.omit()



gg1 %>% 
  mutate(year = as.factor(year)) %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = fct_rev(year), y = pct, fill = fct_rev(att))) +
  geom_col(color = "black") + 
  coord_flip() +
  facet_wrap(~ gen, ncol =1, strip.position = "top") +
  theme_rb() +
  scale_fill_manual(values = c(moma.colors("OKeeffe", 6)[c(1, 3, 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(att == "Never/Seldom", paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 8, family = "font", color = "white") +
  # geom_text(aes(label = ifelse(age2 == "36-44", paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "white") +
  theme(plot.title = element_text(size = 24)) +
  theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) +
  labs(x = "", y = "", title = "Religious Attendance by Generation, 2008-2024", caption = "@ryanburge\nData: Cooperative Election Study, 2008-2024") 
save("ces_relattend_2024_gens.png", wd = 9, ht = 10)



gg1 <- cces24 %>% 
  mutate(relig = frcode(religpew == 1 ~ "Protestant",
                        religpew == 2 ~ "Catholic",
                        religpew >= 3 & religpew <= 8 ~ "Other World Religions", 
                        religpew == 9 | religpew == 10 ~ "Atheist/Agnostic", 
                        religpew == 11 ~ "Nothing in Part.", 
                        religpew == 12 ~ "Something Else")) %>% 
  mutate(gen = frcode(birthyr>= 1925 & birthyr <= 1945 ~ 'Silent',
                      birthyr>= 1946 & birthyr <= 1964 ~ 'Boomers',
                      birthyr>= 1965 & birthyr <= 1976 ~ 'Gen X',
                      birthyr>= 1977 & birthyr <= 1995 ~ 'Millennials',
                      birthyr>= 1996 & birthyr <= 2019 ~ 'Gen Z')) %>% 
  group_by(gen) %>% 
  ct(relig, wt = commonweight, show_na = FALSE)



gg1 %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(relig))) +
  geom_col(color = "black") + 
  coord_flip() +
  facet_wrap(~ gen, ncol =1, strip.position = "left") +
  theme_rb() +
  scale_fill_manual(values = c(
    "Protestant" = "#0072B2",         # Bold blue
    "Catholic" = "#D55E00",           # Bright orange
    "Other World Religions" = "#009E73",  # Teal green
    "Atheist/Agnostic" = "#CC79A7",   # Bright pink
    "Nothing in Part." = "#F0E442",   # Vivid yellow
    "Something Else" = "#56B4E9"      # Sky blue
  )) +
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 = 10, family = "font", color = "black") +
  geom_text(aes(label = ifelse(pct >.05 & relig == "Protestant", paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 10, family = "font", color = "white") +
  # geom_text(aes(label = ifelse(age2 == "36-44", paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "white") +
  theme(plot.title = element_text(size = 24)) +
  theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) +
  labs(x = "", y = "", title = "Religious Composition of Each Generation in 2024", caption = "@ryanburge\nData: Cooperative Election Study, 2024") 
save("ces_relcomp_gens2024.png", wd = 9, ht = 5)



gg1 <- cces %>% 
  filter(year >= 2014) %>% 
  mutate(gender = frcode(gender == 1 ~ "Men", 
                         gender == 2 ~ "Women")) %>% 
  mutate(nones = case_when(religion == 9 | religion == 10 | religion == 11 ~ 1, TRUE ~ 0)) %>% 
  group_by(gender, birthyr, year) %>% 
  mean_ci(nones, wt = weight) 


gg1 %>% 
  filter(year == 2014 | year == 2016 | year == 2018 | year == 2020 | year == 2022 | year == 2024) %>% 
  filter(birthyr >= 1940) %>% 
  filter(gender != "NA") %>% 
  ggplot(., aes(x = birthyr, y = mean, color = gender, group = gender)) +
  geom_point(stroke = .1, shape = 21, alpha = .8) + 
  geom_smooth(se = FALSE) +
  scale_color_calc() +
  y_pct() +
  facet_wrap(~ year) +
  theme_rb(legend = TRUE) +
  theme(strip.text = element_text(size = 20)) +
  labs(x = "Birth Year", y = "", title = "Share Who Are Non-Religious by Gender and Birth Year", caption = "@ryanburge\nData: Cooperative Election Study, 2016-2024")
save("gender_ces24_nones.png")