ct_selection_untitled-3D0CDAA5.R

graph <- cces %>% 
  filter(year == 2008 | year == 2012 | year == 2016 | year == 2020 | year == 2022) %>% 
  cces_pid3(pid7) %>% 
  mutate(religpew = religion) %>% 
  mutate(rel = frcode(religpew <= 8 ~ "Religious", 
                      religpew == 9 | religpew == 10 | religpew == 11 ~ "Secular")) %>% 
  group_by(pid3, year) %>% 
  ct(rel, wt = weight, show_na = FALSE) %>% 
  na.omit() %>% 
  filter(pid3 != "Independent")


graph %>% 
  mutate(year = as.factor(year)) %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = fct_rev(year), y = pct, fill = fct_rev(rel))) +
  geom_col(color = "black") +
  coord_flip() +
  facet_wrap(~ pid3, ncol =2, strip.position = "top") +
  scale_fill_manual(values = c("#FF420E", "#004586")) +
  theme_rb() + 
  theme(legend.position = "bottom") +
  scale_y_continuous(labels = percent) +
  theme(strip.text.y.left = element_text(angle=0, hjust = 1)) +
  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 = 6, family = "font", color = "black") +
  geom_text(aes(label = ifelse(rel == "Religious", paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 6, family = "font", color = "white") +
  theme(strip.text = element_text(size = 16)) +
  labs(x = "", y = "", title = "The Religious Composition of Both Parties, 2008-2022",  caption = "@ryanburge\nData: Cooperative Election Study, 2008-2022") 
save("sec_lib_pid2.png", wd = 9, ht = 4)

graph1 <- cces22 %>% 
  cces_pid3(pid7) %>% 
  mutate(rel = frcode(religpew <= 8 ~ "Religious", 
                      religpew == 9 | religpew == 10 | religpew == 11 ~ "Secular")) %>% 
  mutate(ab = CC22_332a) %>%
  mutate(ab = case_when(ab == 1 ~ 1, 
                        ab == 2 ~ 0)) %>% 
  group_by(pid3, rel) %>% 
  mean_ci(ab, wt = commonweight, ci = .84) %>% 
  na.omit() %>% 
  filter(pid3 != "Independent") %>% 
  mutate(type = "Always Allow a Woman to Obtain An\nAbortion as a Matter of Choice")


graph2 <- cces22 %>% 
  cces_pid3(pid7) %>% 
  mutate(rel = frcode(religpew <= 8 ~ "Religious", 
                      religpew == 9 | religpew == 10 | religpew == 11 ~ "Secular")) %>% 
  mutate(ab = CC22_332c) %>%
  mutate(ab = case_when(ab == 1 ~ 1, 
                        ab == 2 ~ 0)) %>% 
  group_by(pid3, rel) %>% 
  mean_ci(ab, wt = commonweight, ci = .84) %>% 
  na.omit() %>% 
  filter(pid3 != "Independent") %>% 
  mutate(type = "Prohibit All Abortions After the 20th\nWeek of Pregnancy")

graph3 <- cces22 %>% 
  cces_pid3(pid7) %>% 
  mutate(rel = frcode(religpew <= 8 ~ "Religious", 
                      religpew == 9 | religpew == 10 | religpew == 11 ~ "Secular")) %>% 
  mutate(ab = CC22_332e) %>%
  mutate(ab = case_when(ab == 1 ~ 1, 
                        ab == 2 ~ 0)) %>% 
  group_by(pid3, rel) %>% 
  mean_ci(ab, wt = commonweight, ci = .84) %>% 
  na.omit() %>% 
  filter(pid3 != "Independent") %>% 
  mutate(type = "Prohibit Federal Funds for Abortion")

graph4 <- cces22 %>% 
  cces_pid3(pid7) %>% 
  mutate(rel = frcode(religpew <= 8 ~ "Religious", 
                      religpew == 9 | religpew == 10 | religpew == 11 ~ "Secular")) %>% 
  mutate(ab = CC22_332f) %>%
  mutate(ab = case_when(ab == 1 ~ 1, 
                        ab == 2 ~ 0)) %>% 
  group_by(pid3, rel) %>% 
  mean_ci(ab, wt = commonweight, ci = .84) %>% 
  na.omit() %>% 
  filter(pid3 != "Independent") %>% 
  mutate(type = "Abortion Illegal in All Circumstances")

all <- bind_rows(graph1, graph2, graph3, graph4)

library(ggh4x)

all %>% 
  mutate(lab = round(mean, 2)) %>% 
  ggplot(., aes(x = rel, y = mean, fill = rel)) +
  geom_col(color = "black") +
  facet_nested_wrap(~type + pid3, nrow = 4, ncol=4) +
  theme_rb() + 
  y_pct() +
  error_bar() +
  lab_bar(top = FALSE, type = lab, pos = .055, sz = 9) +
  geom_text(aes(y = .055, label = paste0(lab*100, '%')), position = position_dodge(width = .9), size = 9, family = "font", color = "white")  + 
  geom_text(aes(y = .055, label = ifelse(mean <.10, paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 9, family = "font", color = "black")  + 
  scale_fill_calc() +
  theme(strip.text = element_text(size = 16),
        strip.placement = "outside") +  # Move strip text to the top  
  labs(vars = "Type", x = "", y = "", title = "Views of Abortion by Party and Religion", caption = "@ryanburge\nData: Cooperative Election Study, 2022")
save("ab_all_ces22_rel_secular.png", wd = 8, ht = 12)


graph <- gss %>% 
  filter(year <= 2018) %>% 
  mutate(ab = abany) %>% 
  mutate(ab = case_when(ab == 1 ~ 1, 
                        ab == 2 ~ 0)) %>% 
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  mutate(rel = frcode(relig != 4 ~ "Religious", 
                      relig == 4 ~ "Secular")) %>% 
  group_by(year, pid3, rel) %>% 
  mean_ci(ab, wt = wtssall) %>% 
  na.omit() %>% 
  filter(pid3 != "Independent")

graph1 <- gss %>% 
  filter(year > 2018) %>% 
  mutate(ab = abany) %>% 
  mutate(ab = case_when(ab == 1 ~ 1, 
                        ab == 2 ~ 0)) %>% 
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  mutate(rel = frcode(relig != 4 ~ "Religious", 
                      relig == 4 ~ "Secular")) %>% 
  group_by(year, pid3, rel) %>% 
  mean_ci(ab, wt = wtssnrps) %>% 
  na.omit() %>% 
  filter(pid3 != "Independent")

both <- bind_rows(graph, graph1)

both %>% 
  ggplot(., aes(x = year, y = mean, color = rel, group = rel)) +
  geom_point(stroke = .5, shape = 21) +
  geom_smooth(se = FALSE) +
  facet_wrap(~ pid3) +
  scale_color_calc() +
  theme_rb(legend = TRUE) +
  y_pct() + 
  theme(strip.text = element_text(size = 20)) +
  labs(x = "", y = "", title = "Share in Favor of Legal Abortion for Any Reason", caption = "@ryanburge\nData: General Social Survey, 1977-2022")
save("gss_abany_22_rel_sec_pid2.png")




graph <- gss %>% 
  filter(year <= 2018) %>% 
  mutate(ab = abnomore) %>% 
  mutate(ab = case_when(ab == 1 ~ 1, 
                        ab == 2 ~ 0)) %>% 
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  mutate(rel = frcode(relig != 4 ~ "Religious", 
                      relig == 4 ~ "Secular")) %>% 
  group_by(year, pid3, rel) %>% 
  mean_ci(ab, wt = wtssall) %>% 
  na.omit() %>% 
  filter(pid3 != "Independent")

graph1 <- gss %>% 
  filter(year > 2018) %>% 
  mutate(ab = abnomore) %>% 
  mutate(ab = case_when(ab == 1 ~ 1, 
                        ab == 2 ~ 0)) %>% 
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  mutate(rel = frcode(relig != 4 ~ "Religious", 
                      relig == 4 ~ "Secular")) %>% 
  group_by(year, pid3, rel) %>% 
  mean_ci(ab, wt = wtssnrps) %>% 
  na.omit() %>% 
  filter(pid3 != "Independent")

both <- bind_rows(graph, graph1)

both %>% 
  ggplot(., aes(x = year, y = mean, color = rel, group = rel)) +
  geom_point(stroke = .5, shape = 21) +
  geom_smooth(se = FALSE) +
  facet_wrap(~ pid3) +
  scale_color_calc() +
  theme_rb(legend = TRUE) +
  y_pct() + 
  theme(strip.text = element_text(size = 20)) +
  labs(x = "", y = "", title = "Share in Favor of Legal Abortion If Woman Doesn't Want Any More Children", caption = "@ryanburge\nData: General Social Survey, 1977-2022")
save("gss_abnomore_22_rel_sec_pid2.png")