ct_selection_untitled-3F991DE7.R

ggg1 <- cces08 %>% 
  mutate(rel = frcode(religpew == 9 ~ "Atheist", 
                      religpew == 10 ~ "Agnostic",
                      religpew == 11 ~ "Nothing in Particular")) %>% 
  mutate(vote = CC410) %>% 
  mutate(vote = frcode(vote == 1 ~ "Republican",
                       vote == 2 ~ "Democrat",
                       vote == 3 | vote == 4 | vote == 5 | vote == 6 ~ "Third Party")) %>% 
  group_by(rel) %>% 
  ct(vote, wt = V201, show_na = FALSE) %>% 
  mutate(year = 2008)

ggg2 <- cces12 %>% 
  mutate(rel = frcode(religpew == 9 ~ "Atheist", 
                      religpew == 10 ~ "Agnostic",
                      religpew == 11 ~ "Nothing in Particular")) %>% 
  mutate(vote = CC410a) %>% 
  mutate(vote = frcode(vote == 1 ~ "Democrat",
                       vote == 2 ~ "Republican",
                       vote == 4 ~ "Third Party")) %>% 
  group_by(rel) %>% 
  ct(vote, wt = weight_vv_post, show_na = FALSE) %>% 
  mutate(year = 2012)


ggg3 <- cces16 %>% 
  mutate(rel = frcode(religpew == 9 ~ "Atheist", 
                      religpew == 10 ~ "Agnostic",
                      religpew == 11 ~ "Nothing in Particular")) %>% 
  mutate(vote = CC16_410a) %>% 
  mutate(vote = frcode(vote == 1 ~ "Republican",
                       vote == 2 ~ "Democrat",
                       vote == 3 | vote == 4 | vote == 5 | vote == 8 ~ "Third Party")) %>% 
  group_by(rel) %>% 
  ct(vote, wt = commonweight_vv_post, show_na = FALSE) %>% 
  mutate(year = 2016)


ggg4 <- cces20 %>% 
  mutate(rel = frcode(religpew == 9 ~ "Atheist", 
                      religpew == 10 ~ "Agnostic",
                      religpew == 11 ~ "Nothing in Particular")) %>% 
  mutate(vote = CC20_410) %>% 
  mutate(vote = frcode(vote == 1 ~ "Democrat", 
                       vote == 2 ~ "Republican", 
                       vote == 4 ~ "Third Party")) %>% 
  group_by(rel) %>% 
  ct(vote, wt = commonpostweight, show_na = FALSE) %>% 
  mutate(year = 2020)

graph <- bind_rows(ggg1, ggg2, ggg3, ggg4)


graph %>% 
  filter(rel != "NA") %>% 
  mutate(year = as.factor(year)) %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = fct_rev(year), y = pct, fill = fct_rev(vote))) +
  geom_col(color = "black") +
  coord_flip() +
  facet_wrap(~ rel, ncol =1, strip.position = "top") +
  scale_fill_manual(values = c("darkorchid", "dodgerblue3", "firebrick3")) +
  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") +
  labs(x = "", y = "", title = "Presidential Vote Choice Among the Non-Religious ", subtitle = "", caption = "@ryanburge\nData: Cooperative Election Study, 2008-2020") 
save("nones_vote_all.png", wd = 6, ht = 6)


graph1 <- cces22 %>% 
  filter(pid7  <= 7) %>% 
  mutate(trad = frcode(evangelical == 1 & race == 1 ~ "White Evangelical",
                       evangelical == 1 & race != 1 ~ "Nonwhite Evangelical",
                       bprot == 1 ~ "Black Protestants",
                       mainline == 1 ~ "Mainline", 
                       religpew == 2 & race == 1 ~ "White Catholic",
                       religpew == 2 & race != 1 ~ "Nonwhite 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", 
                       TRUE ~ "Unclassified")) %>%
  group_by(trad) %>% 
  mean_ci(pid7, wt = commonweight) %>% 
  select(pid = mean, trad)

graph2 <- cces22 %>% 
  filter(ideo5  <= 7) %>% 
  mutate(trad = frcode(evangelical == 1 & race == 1 ~ "White Evangelical",
                       evangelical == 1 & race != 1 ~ "Nonwhite Evangelical",
                       bprot == 1 ~ "Black Protestants",
                       mainline == 1 ~ "Mainline", 
                       religpew == 2 & race == 1 ~ "White Catholic",
                       religpew == 2 & race != 1 ~ "Nonwhite 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", 
                       TRUE ~ "Unclassified")) %>%
  group_by(trad) %>% 
  mean_ci(ideo5, wt = commonweight) %>% 
  select(ideo = mean, trad)

gg1 <- left_join(graph1, graph2)


graph3 <- cces22 %>% 
  filter(pid7 <= 7) %>% 
  mean_ci(pid7, wt = commonweight) %>% 
  mutate(trad = "Entire Sample") %>% 
  select(pid = mean, trad)

graph4 <- cces22 %>% 
  filter(ideo5 <= 5) %>% 
  mean_ci(ideo5, wt = commonweight) %>% 
  mutate(trad = "Entire Sample") %>% 
  select(ideo = mean, trad)

gg2 <- left_join(graph3, graph4)

gg <- bind_rows(gg1, gg2) %>% 
  mutate(color = frcode(trad == "Atheist" | trad == "Agnostic" | trad == "Nothing in Particular" ~ "Yes", TRUE ~ "No"))


library(ggrepel)

gg <- gg %>% 
  filter(trad != "Unclassified") %>% 
  filter(trad != "Something Else")  

gg %>% 
  ggplot(., aes(x = pid, y = ideo, color = color)) +
  geom_point(shape = 21, stroke = 2) +
  scale_x_continuous(limits = c(1,7), breaks = c(1,2,3,4,5,6,7), labels = c("Strong\nDem.", "Not Very\nStrong Dem.", "Lean\nDem.", "Independent", "Lean\nRep.", "Not Very\nStrong Rep.", "Strong\nRep.")) +
  scale_y_continuous(limits = c(1,5), breaks = c(1,2,3,4,5), labels = c("Very\nLiberal", "Liberal", "Moderate", "Conservative", "Very\nConservative")) +
  theme_rb() +
  scale_color_manual(values = c( "darkblue", "orange")) +
  theme(panel.grid.major = element_line(colour = "white")) + 
  geom_text_repel(data = gg, aes(x = pid, y = ideo, label = trad), family = "font") +
  labs(x = "Partisanship", y = "Ideology", title = "Placing The Nones in Ideological and Partisan Space", caption = "@ryanburge\nData: Cooperative Election Study, 2008-2022")
save("nones_scatter.png")


cces <- read.fst("E://data/cces_abort21.fst")

yyy1 <- cces %>% 
  mutate(ab = case_when(ab_choice == 1 ~ 1, 
                        ab_choice == 2 ~ 0)) %>% 
  filter(trad2 == "Atheist" | trad2 == "Agnostic" | trad2 == "Nothing in Particular") %>% 
  group_by(year, trad2) %>% 
  mean_ci(ab, wt = weight, ci = .84)

yyy2 <- cces22 %>% 
  mutate(ab = case_when(CC22_332a == 1 ~ 1, 
                        CC22_332a == 2 ~ 0)) %>% 
  mutate(trad2 = frcode(religpew == 9 ~ "Atheist", 
                        religpew == 10 ~ "Agnostic",
                        religpew == 11 ~ "Nothing in Particular")) %>% 
  group_by(trad2) %>% 
  mean_ci(ab, wt = commonweight, ci = .84) %>% 
  mutate(year = 2022)

graph1 <- bind_rows(yyy1, yyy2) %>% mutate(type = "Any Reason")

yyy1 <- cces %>% 
  mutate(ab = case_when(ab_rape == 1 ~ 1, 
                        ab_rape == 2 ~ 0)) %>% 
  filter(trad2 == "Atheist" | trad2 == "Agnostic" | trad2 == "Nothing in Particular") %>% 
  group_by(year, trad2) %>% 
  mean_ci(ab, wt = weight, ci = .84)

yyy2 <- cces22 %>% 
  mutate(ab = case_when(CC22_332b == 1 ~ 1, 
                        CC22_332b == 2 ~ 0)) %>% 
  mutate(trad2 = frcode(religpew == 9 ~ "Atheist", 
                        religpew == 10 ~ "Agnostic",
                        religpew == 11 ~ "Nothing in Particular")) %>% 
  group_by(trad2) %>% 
  mean_ci(ab, wt = commonweight, ci = .84) %>% 
  mutate(year = 2022)

graph2 <- bind_rows(yyy1, yyy2) %>% mutate(type = "Only For Rape, Incest, Life of Mother")


yyy1 <- cces %>% 
  mutate(ab = case_when(ab_late == 1 ~ 1, 
                        ab_late == 2 ~ 0)) %>% 
  filter(trad2 == "Atheist" | trad2 == "Agnostic" | trad2 == "Nothing in Particular") %>% 
  group_by(year, trad2) %>% 
  mean_ci(ab, wt = weight, ci = .84)

yyy2 <- cces22 %>% 
  mutate(ab = case_when(CC22_332c == 1 ~ 1, 
                        CC22_332c == 2 ~ 0)) %>% 
  mutate(trad2 = frcode(religpew == 9 ~ "Atheist", 
                        religpew == 10 ~ "Agnostic",
                        religpew == 11 ~ "Nothing in Particular")) %>% 
  group_by(trad2) %>% 
  mean_ci(ab, wt = commonweight, ci = .84) %>% 
  mutate(year = 2022)

graph3 <- bind_rows(yyy1, yyy2) %>% mutate(type = "Prohibit After 20 Weeks")



yyy1 <- cces %>% 
  mutate(ab = case_when(ab_ins == 1 ~ 1, 
                        ab_ins == 2 ~ 0)) %>% 
  filter(trad2 == "Atheist" | trad2 == "Agnostic" | trad2 == "Nothing in Particular") %>% 
  group_by(year, trad2) %>% 
  mean_ci(ab, wt = weight, ci = .84)

yyy2 <- cces22 %>% 
  mutate(ab = case_when(CC22_332d == 1 ~ 1, 
                        CC22_332d == 2 ~ 0)) %>% 
  mutate(trad2 = frcode(religpew == 9 ~ "Atheist", 
                        religpew == 10 ~ "Agnostic",
                        religpew == 11 ~ "Nothing in Particular")) %>% 
  group_by(trad2) %>% 
  mean_ci(ab, wt = commonweight, ci = .84) %>% 
  mutate(year = 2022)

graph4 <- bind_rows(yyy1, yyy2) %>% mutate(type = "Employers Can Deny Coverage\n For Abortion in Insurance Plans")



yyy1 <- cces %>% 
  mutate(ab = case_when(ab_funds == 1 ~ 1, 
                        ab_funds == 2 ~ 0)) %>% 
  filter(trad2 == "Atheist" | trad2 == "Agnostic" | trad2 == "Nothing in Particular") %>% 
  group_by(year, trad2) %>% 
  mean_ci(ab, wt = weight, ci = .84)

yyy2 <- cces22 %>% 
  mutate(ab = case_when(CC22_332e == 1 ~ 1, 
                        CC22_332e == 2 ~ 0)) %>% 
  mutate(trad2 = frcode(religpew == 9 ~ "Atheist", 
                        religpew == 10 ~ "Agnostic",
                        religpew == 11 ~ "Nothing in Particular")) %>% 
  group_by(trad2) %>% 
  mean_ci(ab, wt = commonweight, ci = .84) %>% 
  mutate(year = 2022)

graph5 <- bind_rows(yyy1, yyy2) %>% mutate(type = "Prohibit Federal Funds for Abortion")


yyy1 <- cces %>% 
  mutate(ab = case_when(ab_never == 1 ~ 1, 
                        ab_never == 2 ~ 0)) %>% 
  filter(trad2 == "Atheist" | trad2 == "Agnostic" | trad2 == "Nothing in Particular") %>% 
  group_by(year, trad2) %>% 
  mean_ci(ab, wt = weight, ci = .84)

yyy2 <- cces22 %>% 
  mutate(ab = case_when(CC22_332f == 1 ~ 1, 
                        CC22_332f == 2 ~ 0)) %>%
  mutate(trad2 = frcode(religpew == 9 ~ "Atheist", 
                      religpew == 10 ~ "Agnostic",
                      religpew == 11 ~ "Nothing in Particular")) %>% 
  group_by(trad2) %>% 
  mean_ci(ab, wt = commonweight, ci = .84) %>% 
  mutate(year = 2022)

graph6 <- bind_rows(yyy1, yyy2) %>% mutate(type = "Illegal in All Circumstances")

all <- bind_df("graph") %>% na.omit()

all %>% 
  mutate(lab = round(mean, 2)) %>% 
  ggplot(., aes(x = year, y = mean, color = trad2, group = trad2)) +
  geom_point() +
  geom_line() + 
  facet_wrap(~ type) +
  theme_rb(legend = TRUE) +
  scale_color_gdocs() +
  y_pct() +
  scale_x_continuous(breaks = c(2012, 2014, 2016, 2018, 2020, 2022)) +
  labs(x= "Year", y = "Share In Favor", title = "Abortion Public Opinion Since 2014 Among the Nones", caption = "@ryanburge\nData: Cooperative Election Study, 2014-2022")
save("ab_nones_2022.png")




fun <- function(df, var1, var2, var3, var4, weight, yr) {
  
  aaa1 <- df %>% 
    filter({{var1}} <= 7) %>% 
    mutate(trad2 = frcode(religpew == 9 ~ "Atheist", 
                          religpew == 10 ~ "Agnostic",
                          religpew == 11 ~ "Nothing in Particular")) %>% 
    group_by(trad2) %>% 
    mean_ci({{var1}}, wt = {{weight}}) %>% 
    mutate(year = yr) %>% 
    mutate(group = "Yourself")
  
  aaa2 <- df %>% 
    filter({{var2}} <= 7) %>% 
    mutate(trad2 = frcode(religpew == 9 ~ "Atheist", 
                          religpew == 10 ~ "Agnostic",
                          religpew == 11 ~ "Nothing in Particular")) %>% 
    group_by(trad2) %>% 
    mean_ci({{var2}}, wt = {{weight}}) %>% 
    mutate(year = yr) %>% 
    mutate(group = "Democrats")
  
  
  aaa3 <- df %>% 
    filter({{var3}} <= 7) %>% 
    mutate(trad2 = frcode(religpew == 9 ~ "Atheist", 
                          religpew == 10 ~ "Agnostic",
                          religpew == 11 ~ "Nothing in Particular")) %>% 
    group_by(trad2) %>% 
    mean_ci({{var3}}, wt = {{weight}}) %>% 
    mutate(year = yr) %>% 
    mutate(group = "Republicans")
  
  aaa4 <- df %>% 
    filter({{var3}} <= 7) %>% 
    mutate(trad2 = frcode(religpew == 9 ~ "Atheist", 
                          religpew == 10 ~ "Agnostic",
                          religpew == 11 ~ "Nothing in Particular")) %>% 
    group_by(trad2) %>% 
    mean_ci({{var4}}, wt = {{weight}}) %>% 
    mutate(year = yr) %>% 
    mutate(group = "Trump")
  
  bind_rows(aaa1, aaa2, aaa3, aaa4) 
  
}


yyy1 <- cces16 %>% fun(CC16_340a, CC16_340g, CC16_340h, CC16_340e, commonweight, yr = 2016)
yyy2 <- cces17 %>% fun(CC17_350a, CC17_350d, CC17_350e, CC17_350c, weights_common, yr = 2017)
yyy3 <- cces18 %>% fun(CC18_334A, CC18_334D, CC18_334E, CC18_334C, commonweight, yr = 2018)
yyy4 <- cces19 %>% fun(CC19_334a, CC19_334d, CC19_334e, CC19_334c, commonweight, yr = 2019)
yyy5 <- cces20 %>% fun(CC20_340a, CC20_340e, CC20_340f, CC20_340d, commonweight,  yr = 2020)
yyy6 <- cces21 %>% fun(CC21_330a, CC21_330e, CC21_330f, CC21_330b, commonweight, yr = 2021) %>%  filter(group != "Trump")
yyy7 <- cces22 %>% fun(CC22_340a, CC22_340e, CC22_340f, CC22_340d, commonweight, yr = 2022)


graph <- bind_df("yyy") %>% filter(trad2 != "NA")


graph$group <- factor(graph$group, levels = c("Democrats", "Yourself", "Trump", "Republicans"))


graph %>% 
  mutate(year = as.factor(year)) %>% 
  ggplot(., aes(x = fct_rev(year), y = mean, color = group, group = group)) +
  geom_line() + 
  geom_errorbar(aes(ymin = lower, ymax=upper), size = 1, width = 0) +
  geom_point(shape = 21, stroke = 2, fill = "white") +
  coord_flip() +
  facet_wrap(~ trad2, ncol = 1) +
  scale_y_continuous(breaks = c(1,2,3,4,5,6,7), labels = c("Very\nLib", "Lib.", "Somewhat\nLib.", "Middle of\nthe Road", "Somewhat\nCons.", "Cons.", "Very\nCons"), limits = c(1,7)) +
  scale_color_manual(values = c("dodgerblue3", "black", "darkorchid", "firebrick3")) +
  theme_rb(legend = TRUE) +
  labs(x = "", y = "", title = "Place Yourself, Democrats, Trump, and\nRepublicans in Ideological Space", subtitle = "Among the Nones", 
       caption = "@ryanburge\nData: Cooperative Election Study, 2016-2022")
save("your_self_dems_republicans_trump_nones22.png", ht = 8, wd = 5)