RIP Post 12/7/2020

rip_post_1272020.R

gg <- cces %>% 
  mutate(wev = case_when(race == 1 & pew_bornagain == 1 ~ 1, TRUE ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(wev, wt = weight, ci = .84) %>% 
  mutate(survey = "CCES")


gg2 <- gss %>% 
  filter(year >= 2008) %>% 
  mutate(white = case_when(race == 1 & hispanic == 1 ~ 1, TRUE ~ 0)) %>% 
  mutate(ba = case_when(reborn == 1 ~ 1, TRUE ~ 0)) %>% 
  mutate(wev = case_when(white == 1 & ba == 1 ~ 1, TRUE~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(wev, wt = wtssall, ci = .84) %>% 
  mutate(survey = "GSS")

graph <- bind_rows(gg, gg2)

graph %>% 
  filter(year >= 2008) %>% 
  filter(year != 2017) %>% 
  filter(year != 2019) %>% 
  ggplot(., aes(x = factor(year),  y= mean, fill = survey)) +
  geom_col(color = "black", position = "dodge") +
  theme_rb(legend = TRUE) +
  scale_fill_tron() +
  y_pct() +
  error_bar() +
  lab_bar(top = FALSE, type = mean, pos = .02, sz = 4) +
  labs(x = "", y = "", title =  "Share of Americans Who Are White and Identify\nas Born-Again or Evangelical", caption = "@ryanburge\nData: CCES 2008-2019") +
  ggsave("E://evangelical_year_cces_white.png", type = "cairo-png", width = 7)


gg1 <- cces %>% 
  mutate(evan = case_when(pew_bornagain == 1 ~ 1, pew_bornagain == 2 ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(evan, wt = weight, ci = .84)  %>% 
  mutate(survey = "CCES")


gg2 <- gss %>% 
  filter(year >= 2008) %>% 
  mutate(evan = case_when(reborn == 1 ~ 1, reborn == 2 ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(evan, wt = wtssall, ci = .84)  %>% 
  mutate(survey = "GSS")

graph <- bind_rows(gg1, gg2)

graph %>% 
  filter(year >= 2008) %>% 
  filter(year != 2017) %>% 
  filter(year != 2019) %>% 
  ggplot(., aes(x = factor(year),  y= mean, fill = survey)) +
  geom_col(color = "black", position = "dodge") +
  theme_rb(legend = TRUE) +
  scale_fill_npg() +
  y_pct() +
  error_bar() +
  lab_bar(top = FALSE, type = mean, pos = .02, sz = 4.5) +
  labs(x = "", y = "", title =  "Share of Americans Who Identify as Born-Again or Evangelical", caption = "@ryanburge\nData: CCES 2008-2019") +
  ggsave("E://evangelical_year_cces_gss.png", type = "cairo-png", width = 7)


gg <- cces %>%
  filter(year >= 2010) %>% 
  mutate(prot = case_when(religion == 1 ~ 1, TRUE ~ 0)) %>% 
  filter(pew_bornagain == 1) %>% 
  group_by(year) %>% 
  mean_ci(prot, wt = weight, ci = .84) %>% 
  mutate(survey = "CCES")

gg2 <- gss %>% 
  filter(year >= 2010) %>% 
  mutate(prot = case_when(relig == 1 ~ 1, TRUE ~ 0)) %>% 
  filter(reborn == 1) %>% 
  group_by(year) %>% 
  mean_ci(prot, wt = wtssall, ci = .84) %>% 
  mutate(survey = "GSS")

graph <- bind_rows(gg, gg2)

graph %>% 
  filter(year >= 2008) %>% 
  filter(year != 2017) %>% 
  filter(year != 2019) %>% 
  ggplot(., aes(x = factor(year),  y= mean, fill = survey)) +
  geom_col(color = "black", position = "dodge") +
  theme_rb(legend = TRUE) +
  error_bar() +
  scale_fill_npg() +
  y_pct() +
  lab_bar(top = FALSE, type = mean, pos = .03, sz = 5.5) +
  labs(x = "", y = "", title =  "Share of Born-Again/Evangelicals Who Identify as Protestants", caption = "@ryanburge\nData: CCES 2010-2019") +
  ggsave("E://evangelical_year_cces_gss_prot.png", type = "cairo-png", width = 7)



graph <- cces %>% 
  filter(year == 2010 | year == 2019) %>% 
  group_by(year) %>% 
  filter(pew_bornagain == 1) %>% 
  mutate(trad = frcode(religion == 1 ~ "Protestant", 
                     religion == 2 ~ "Catholic",
                     religion == 9 | religion == 10 | religion == 11 ~ "None", 
                     TRUE ~ "Other Faith Group")) %>%
  ct(trad, wt = weight)


graph %>% 
  ggplot(., aes(x = trad, y = pct, fill = factor(year))) +
  geom_col(color = "black", position = "dodge") +
  theme_rb(legend = TRUE) + 
  scale_fill_d3() +
  lab_bar(top = TRUE, type =  pct, pos = .03, sz = 5) +
  y_pct() + 
  labs(x = "", y = "", title= "Tradition Breakdown of Born-Again/Evangelicals", caption = "@ryanburge\nData: CCES 2010 + 2019") +
  ggsave("E://ba_breakdown.png", type = "cairo-png", width = 6)


gg <- cces %>% 
  filter(protestant == 3) %>% 
  mutate(ev = case_when(pew_bornagain == 1 ~ 1, pew_bornagain == 2 ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(ev, wt = weight)

gg %>% 
  ggplot(., aes(x = factor(year), y= mean, fill = mean)) +
  geom_col(color = "black") +
  scale_fill_gradient(low = "#FFE47A", high = "#3D7EAA") +
  error_bar() +
  lab_bar(top = FALSE, type = mean, sz = 5, pos = .035) +
  theme_rb() + 
  y_pct() + 
  labs(x = "", y = "", title = "Share of Non-Denoms Who ID as Evangelical", caption = "@ryanburge\nData: CCES 2008-2019") +
  ggsave("E://nd_evans.png", type = "cairo-png", width = 7)



graph <- cces %>% 
  filter(year == 2010 | year == 2019) %>% 
  group_by(year) %>% 
  filter(pew_bornagain == 1) %>% 
  mutate(trad = frcode(religion == 1 ~ "Protestant", 
                       religion == 2 ~ "Catholic",
                       religion == 9 | religion == 10 | religion == 11 ~ "None", 
                       TRUE ~ "Other Faith Group")) %>%
  ct(trad, wt = weight)


graph %>% 
  ggplot(., aes(x = trad, y = pct, fill = factor(year))) +
  geom_col(color = "black", position = "dodge") +
  theme_rb(legend = TRUE) + 
  scale_fill_d3() +
  lab_bar(top = TRUE, type =  pct, pos = .03, sz = 5) +
  y_pct() + 
  labs(x = "", y = "", title= "Tradition Breakdown of Self-Identified Evangelicals", caption = "@ryanburge\nData: CCES 2010 + 2019") +
  ggsave("E://ba_breakdown.png", type = "cairo-png", width = 6)



graph <- cces %>% 
  filter(year == 2010 | year == 2019) %>% 
  mutate(ev = frcode(pew_bornagain == 1 ~ "Self ID Evangelicals", 
                       pew_bornagain == 2 ~ "Not Self ID Evangelicals")) %>% 
  mutate(trad = frcode(religion == 1 ~ "Protestant", 
                       religion == 2 ~ "Catholic",
                       religion == 9 | religion == 10 | religion == 11 ~ "None", 
                       TRUE ~ "Other Faith Group")) %>%
  mutate(rep = case_when(pid7 == 5 | pid7 == 6 | pid7 == 7 ~ 1, 
                         pid7 <= 4 ~ 0)) %>% 
  group_by(year, ev, trad) %>% 
  mean_ci(rep, wt = weight) %>% 
  na.omit()


graph %>% 
  ggplot(., aes(x = trad, y = mean, fill = factor(year))) +
  geom_col(color = "black", position = "dodge") +
  theme_rb(legend = TRUE) + 
  scale_fill_d3() +
  facet_wrap(~ ev) +
  lab_bar(top = TRUE, type =  mean, pos = .02, sz = 4) +
  y_pct() + 
  labs(x = "", y = "", title= "Share Who Identify as Republicans", caption = "@ryanburge\nData: CCES 2010 + 2019") +
  ggsave("E://ba_breakdown2.png", type = "cairo-png", width = 8)