Conservative Christians vs Nones

christians_nones_conservative.R

gg <- cces %>% 
  mutate(grp = frcode(religion == 9 ~ "Atheist", 
                      religion == 10 ~ "Agnostic", 
                      religion == 11 ~ "Nothing in Particular")) %>% 
  mutate(con = case_when(ideo5 == 4 | ideo5 == 5 ~ 1, 
                         ideo5 <= 3 ~ 0)) %>% 
  group_by(year, grp) %>% 
  mean_ci(con, wt = weight, ci = .84)



gg1 <- cces %>% 
  filter(religion <= 4) %>% 
  mutate(con = case_when(ideo5 == 4 | ideo5 == 5 ~ 1, 
                         ideo5 <= 3 ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(con, wt = weight, ci = .84) %>% 
  mutate(grp = "Christians")

graph <- bind_rows(gg, gg1)


graph %>% 
  filter(year >= 2008) %>% 
  filter(grp != 'NA') %>% 
  ggplot(., aes(x = year, y = mean, color = grp)) +
  geom_point(size=3, color="white") +
  geom_point(size=2, shape=1) +
  geom_point(size=1, shape=19) +
  geom_line() + 
  y_pct() + 
  scale_color_gdocs() +
  theme_rb() +
  scale_x_continuous(breaks = c(2008, 2012, 2016, 2020)) +
  add_text(x = 2014, y = .285, word = "Nothing in Particular", sz = 5) +
  add_text(x = 2014, y = .17, word = "Agnostic", sz = 5) +
  add_text(x = 2015, y = .09, word = "Atheist",  sz  = 5) +
  add_text(x = 2015, y = .50, word = "Christian",  sz  = 5) +
  labs(x = "", y = "", title = "Share Who Identify as Conservative", caption = "@ryanburge\nData: CES 2008-2020") +
  ggsave("E://type_nones_cons.png", type = "cairo-png", width = 7)
  

cces20 %>% 
  filter(ideo5 == 4 | ideo5 == 5) %>% 
  mutate(grp = frcode(religpew == 9 | religpew == 10 | religpew == 11 ~ "Nones", 
                      religpew <= 4 ~ "Christians")) %>%
  ct(grp, wt = commonweight)

# 17% of conservatives are nones, 74% are Christians ## 


ggg1 <- cces08 %>% 
  filter(V243 == 4 | V243 == 5) %>% 
  mutate(grp = frcode(religpew == 9 | religpew == 10 | religpew == 11 ~ "Nones", 
                      religpew <= 4 ~ "Christians")) %>%
  mutate(vote = CC410) %>% 
  mutate(vote = frcode(vote == 1 ~ "Republican",
                       vote == 2 ~ "Democrat",
                       vote == 3 | vote == 4 | vote == 5 | vote == 6 ~ "Third Party")) %>% 
  group_by(grp) %>% 
  ct(vote, wt = V201, show_na = FALSE) %>% 
  mutate(year = 2008)

ggg2 <- cces12 %>% 
  filter(ideo5 == 4 | ideo5 == 5) %>% 
  mutate(grp = frcode(religpew == 9 | religpew == 10 | religpew == 11 ~ "Nones", 
                      religpew <= 4 ~ "Christians")) %>%
  mutate(vote = CC410a) %>% 
  mutate(vote = frcode(vote == 1 ~ "Democrat",
                       vote == 2 ~ "Republican",
                       vote == 4 ~ "Third Party")) %>% 
  group_by(grp) %>% 
  ct(vote, wt = weight_vv_post, show_na = FALSE) %>% 
  mutate(year = 2012)


ggg3 <- cces16 %>% 
  filter(ideo5 == 4 | ideo5 == 5) %>% 
  mutate(grp = frcode(religpew == 9 | religpew == 10 | religpew == 11 ~ "Nones", 
                      religpew <= 4 ~ "Christians")) %>%
  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(grp) %>% 
  ct(vote, wt = commonweight_vv_post, show_na = FALSE) %>% 
  mutate(year = 2016)


ggg4 <- cces20 %>% 
  filter(ideo5 == 4 | ideo5 == 5) %>% 
  mutate(grp = frcode(religpew == 9 | religpew == 10 | religpew == 11 ~ "Nones", 
                      religpew <= 4 ~ "Christians")) %>%
  mutate(vote = CC20_410) %>% 
  mutate(vote = frcode(vote == 1 ~ "Democrat", 
                       vote == 2 ~ "Republican", 
                       vote == 4 ~ "Third Party")) %>% 
  group_by(grp) %>% 
  ct(vote, wt = commonpostweight, show_na = FALSE) %>% 
  mutate(year = 2020)

graph <- bind_rows(ggg1, ggg2, ggg3, ggg4) %>% na.omit()


graph %>% 
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(vote))) +
  geom_col(color = "black") + 
  coord_flip() +
  facet_grid(year ~ grp, switch = "y") +
  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)) +
  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 >.055, paste0(pct*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "black") +
  labs(x = "", y = "", title = "Vote Choice for President", subtitle = "Among Conservatives", caption = "@ryanburge\nData: CCES 2008-2020") +
  ggsave("E://vote_choice_cons.png", width = 9, height = 3.5)


fun <- function(df, var, name){
  
  df %>% 
    filter(ideo5 == 4 | ideo5 == 5) %>% 
    mutate(grp = frcode(religpew == 9 | religpew == 10 | religpew == 11 ~ "Nones", 
                        religpew <= 4 ~ "Christians")) %>%
    mutate(qq = {{var}}) %>% 
    mutate(qq = case_when(qq == 1 ~ 1, 
                          qq == 2 ~ 0)) %>% 
    group_by(grp) %>% 
    mean_ci(qq, wt = commonweight, ci = .84) %>% 
    mutate(type = name) %>% 
    na.omit()


}

yyy1 <- cces20 %>% fun(CC20_355a, "Withdraw From Paris Climate Accord")
yyy2 <- cces20 %>% fun(CC20_333a, "Give EPA Power to Regulate CO2")
yyy3 <- cces20 %>% fun(CC20_355d, "Ban Transgender from Military")
yyy4 <- cces20 %>% fun(CC20_332a, "Always Allow Abortion")
yyy5 <- cces20 %>% fun(CC20_332e, "Prohibit Federal Funds for Abortion")
yyy6 <- cces20 %>% fun(CC20_355e, "Require Work for Food Stamps")
yyy7 <- cces20 %>% fun(CC20_330b, "Ban Assault Weapons")
yyy8 <- cces20 %>% fun(CC20_330c, "Make it Easier to Obtain Concealed Carry")
yyy9 <- cces20 %>% fun(CC20_331a, "Pathway to Citizenship")
yyy10 <- cces20 %>% fun(CC20_331d, "Reduce Legal Immigration by 50%")
yyy11 <- cces20 %>% fun(CC20_334a, "Eliminate Mandatory Minimums")
yyy12 <- cces20 %>% fun(CC20_334g, "End DoD Surplus to Local Police")

graph <- bind_df("yyy")

gg1 <- graph %>% filter(grp == "Nones") %>% select(grp, nones = mean, type)
gg2 <- graph %>% filter(grp == "Christians") %>% select(xtn = mean)

sort <- bind_cols(gg1, gg2) %>% mutate(diff = nones - xtn) %>% select(type, diff)

graph <- left_join(graph, sort) 

graph$diff <- abs(graph$diff)

graph %>% 
  ggplot(., aes(x = reorder(type, -diff), y = mean, fill = grp)) +
  geom_col(color = "black", position = "dodge") +
  coord_flip() +
  scale_fill_tableau() +
  theme_rb(legend = TRUE) +
  y_pct() + 
  error_bar() +
  lab_bar(top = FALSE, type = mean, pos = .065, sz = 4) +
  labs(x = "", y = "Share in Favor", title = "Issue Positions of Conservatives", caption = "@ryanburge\nData: CES 2020") +
  ggsave("E://nones_xtn_conservative.png", type = "cairo-png", width = 7, height = 7)




ttt1 <- cces20 %>% 
  filter(ideo5 == 4 | ideo5 == 5) %>% 
  mutate(grp = frcode(religpew == 9 | religpew == 10 | religpew == 11 ~ "Nones", 
                      religpew <= 4 ~ "Christians")) %>%
  mutate(q1 = CC20_441a) %>% 
  mutate(q1 = frcode(q1 == 5 ~ "Strongly Disagree",
                     q1 == 4 ~ "Somewhat Disagree",
                     q1 == 3 ~ "Neither",
                     q1 == 2 ~ "Somewhat Agree",
                     q1 == 1 ~ "Strongly Agree")) %>% 
  group_by(grp) %>% 
  ct(q1, show_na = FALSE, wt = commonweight) %>% 
  mutate(term = "The Irish, Italians, Jews and many other minorities overcame prejudice\nand worked their way up. Black should do the same without any special favors") %>% 
  mutate(year = 2020) %>% 
  na.omit()

ttt2 <- cces20 %>% 
  filter(ideo5 == 4 | ideo5 == 5) %>% 
  mutate(grp = frcode(religpew == 9 | religpew == 10 | religpew == 11 ~ "Nones", 
                      religpew <= 4 ~ "Christians")) %>%
  mutate(q1 = CC20_441b) %>% 
  mutate(q1 = frcode(q1 == 5 ~ "Strongly Disagree",
                     q1 == 4 ~ "Somewhat Disagree",
                     q1 == 3 ~ "Neither",
                     q1 == 2 ~ "Somewhat Agree",
                     q1 == 1 ~ "Strongly Agree")) %>% 
  group_by(grp) %>% 
  ct(q1, show_na = FALSE, wt = commonweight) %>% 
  mutate(term = "Generations of slavery and discrimination have created conditions\nthat make it difficult for Blacks to work their way out of the lower class.") %>% 
  mutate(year = 2020) %>% 
  na.omit()

graph <- bind_rows(ttt1, ttt2)



top <- graph %>% 
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(q1))) +
  geom_col(color = "black") + 
  coord_flip() +
  facet_grid(grp ~ term, switch = "y") +
  scale_fill_manual(values = c("#264653", "#2a9d8f", "#e9c46a", "#f4a261", "#e76f51")) +
  theme_rb() +
  # 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 >.08, paste0(pct*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "black") +
  geom_text(aes(label = ifelse(q1 == "Strongly Agree" & pct > .06, paste0(pct*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "white") +
  labs(x = "", y = "", title = "Views of Racial Issues Among Conservatives", subtitle = "", caption = "") +
  ggsave("E://resent_cons_nones_xtn1.png", width = 12, height = 4)


ttt3 <- cces20 %>% 
  filter(ideo5 == 4 | ideo5 == 5) %>% 
  mutate(grp = frcode(religpew == 9 | religpew == 10 | religpew == 11 ~ "Nones", 
                      religpew <= 4 ~ "Christians")) %>%
  mutate(q1 = CC20_440a) %>% 
  mutate(q1 = frcode(q1 == 5 ~ "Strongly Disagree",
                     q1 == 4 ~ "Somewhat Disagree",
                     q1 == 3 ~ "Neither",
                     q1 == 2 ~ "Somewhat Agree",
                     q1 == 1 ~ "Strongly Agree")) %>% 
  group_by(grp) %>% 
  ct(q1, show_na = FALSE, wt = commonweight) %>% 
  mutate(term = "White people in the U.S. have certain advantages because of their skin color") %>% 
  mutate(year = 2020) %>% 
  na.omit()

ttt4 <- cces20 %>% 
  filter(ideo5 == 4 | ideo5 == 5) %>% 
  mutate(grp = frcode(religpew == 9 | religpew == 10 | religpew == 11 ~ "Nones", 
                      religpew <= 4 ~ "Christians")) %>%
  mutate(q1 = CC20_440b) %>% 
  mutate(q1 = frcode(q1 == 5 ~ "Strongly Disagree",
                     q1 == 4 ~ "Somewhat Disagree",
                     q1 == 3 ~ "Neither",
                     q1 == 2 ~ "Somewhat Agree",
                     q1 == 1 ~ "Strongly Agree")) %>% 
  group_by(grp) %>% 
  ct(q1, show_na = FALSE, wt = commonweight) %>% 
  mutate(term = "Racial problems in the U.S. are rare, isolated situations") %>% 
  mutate(year = 2020) %>% 
  na.omit()

graph <- bind_rows(ttt3, ttt4)


bot <- graph %>% 
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(q1))) +
  geom_col(color = "black") + 
  coord_flip() +
  facet_grid(grp ~ term, switch = "y") +
  scale_fill_manual(values = c("#264653", "#2a9d8f", "#e9c46a", "#f4a261", "#e76f51")) +
  theme_rb(legend = TRUE) +
  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 >.08, paste0(pct*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "black") +
  geom_text(aes(label = ifelse(q1 == "Strongly Agree" & pct > .06, paste0(pct*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "white") +
  labs(x = "", y = "", title = "", subtitle = "", caption = "@ryanburge\nData: CES 2020") +
  ggsave("E://resent_cons_nones_xtn2.png", width = 12, height = 4)

library(patchwork)

both <- top / bot

ggsave("E://patch_nones_xtn.png", type = "cairo-png", both, width = 11, height = 6)