Tweet about generational differences in PID

071818.R

library(building)
library(ggsci)


two_sample <- function(df, low, high, age) {
  low <- enquo(low)
  high <- enquo(high)
  age <- enquo(age)
  
  a1 <- df %>% 
    mutate(age = 2016 - birthyr) %>% 
    filter(age >= !!low & age <= !!high) %>% 
    filter(race ==1) %>% 
    filter(educ <= 4) %>% 
    filter(evangelical ==1) %>% 
    mutate(group = "Evangelical")
  
  a2 <- df %>% 
    mutate(age = 2016 - birthyr) %>% 
    filter(age >= !!low & age <= !!high) %>% 
    filter(race ==1) %>% 
    filter(educ <= 4) %>% 
    mutate(group = "Entire Sample                 ")
  
  full <- bind_rows(a1, a2)  
  
  result <- full %>% 
    filter(pid7 <=7) %>% 
    group_by(group) %>% 
    mean_ci(pid7) %>% 
    mutate(age = !! age)
}

first <- two_sample(cces16, 18, 35, "18-35")
second <- two_sample(cces16, 36, 44, "36-44")
third <- two_sample(cces16, 45, 54, "45-54")
four <- two_sample(cces16, 55, 64, "55-64")
five <- two_sample(cces16, 65, 100, "65-100")

graph <- bind_rows(first, second, third, four, five)


font_add_google("Oswald", "font")
showtext_auto()

graph %>% 
  ggplot(., aes(x=mean, y=age)) + 
  geom_point(shape = 21, aes(color=group, fill = group), size=5, stroke=.5) +
  geom_errorbarh(aes(xmin = lower, xmax=upper, color = group), size = 1.25, height = .25) +
  theme_minimal() + 
  theme(text=element_text(size=64, family="font")) +
  theme(legend.position = "bottom") + 
  scale_fill_aaas() +
  scale_color_aaas() +
  labs(x = "Mean Party Identification", y = "Age Group", title = "Young Evangelicals Are Further Away From Their Counterparts", caption = "Data: CCES 2016", subtitle = "Includes only White Respondents with at least a 2 Year College Degree") +
  scale_x_continuous(limits = c(3.5,5.5), breaks = c(1,2,3,4,5,6,7), labels = c("Strong Democrat", "Not Strong Democrat", "Lean Democrat", "Independent", "Lean Republican", "Not Strong Republican", "Strong Republican")) +
  theme(plot.title = element_text(face = "bold")) +
  theme(legend.title=element_blank())
     
ggsave("age_diff_pid.png", type = "cairo-png", width = 12, height = 8)


library(building)
library(ggsci)


two_sample <- function(df, low, high, age) {
  low <- enquo(low)
  high <- enquo(high)
  age <- enquo(age)
  
  a1 <- df %>% 
    mutate(age = 2016 - birthyr) %>% 
    filter(age >= !!low & age <= !!high) %>% 
    filter(race ==1) %>% 
    filter(educ <= 4) %>% 
    filter(evangelical ==1) %>% 
    mutate(group = "Evangelical")
  
  a2 <- df %>% 
    mutate(age = 2016 - birthyr) %>% 
    filter(age >= !!low & age <= !!high) %>% 
    filter(race ==1) %>% 
    filter(educ <= 4) %>% 
    mutate(group = "Entire Sample                 ")
  
  full <- bind_rows(a1, a2)  
  
  result <- full %>% 
    filter(pid7 <=7) %>% 
    group_by(group) %>% 
    filter(CC16_410a <=2) %>% 
    ct(CC16_410a, wt = commonweight_vv_post) %>%  
    mutate(age = !! age)  
    
}

first <- two_sample(cces16, 18, 35, "18-35")
second <- two_sample(cces16, 36, 44, "36-44")
third <- two_sample(cces16, 45, 54, "45-54")
four <- two_sample(cces16, 55, 64, "55-64")
five <- two_sample(cces16, 65, 100, "65-100")

graph <- bind_rows(first, second, third, four, five)


font_add_google("Oswald", "font")
showtext_auto()

graph %>% 
  filter(CC16_410a ==1) %>% 
  ggplot(.,  aes(x= group, y = pct)) + 
  geom_col(aes(fill = as.factor(group)), color = "black") +
  theme_minimal() + 
  theme(text=element_text(size=64, family="font")) +
  scale_y_continuous(labels = scales::percent) + theme(legend.position="none") +
  facet_grid(.~ age) +
  scale_fill_aaas() + 
  geom_text(aes(y = pct + .025, label = paste0(pct*100, '%')), position = position_dodge(width = .9), size = 16, family = "font")+
  labs(x = "", y = "Share of Two Party Vote for Trump", title = "Young Evangelicals Were + 30% for Trump", caption = "Data: CCES 2016", subtitle = "Includes only White Respondents with at least a 2 Year College Degree") +



ggsave("age_diff_vote.png", type = "cairo-png", width = 15, height = 8)

ab <- cces16 %>% 
  filter(evangelical ==1) %>% 
  mutate(abany = recode(CC16_332a, "1=1; 2=0; else =99")) %>% 
  mutate(age = 2016 - birthyr) %>% 
  group_by(age) %>% 
  ct(abany, commonweight_vv_post) %>% 
  filter(abany == 1) %>% 
  mutate(issue = "Abortion")
  
gay <- cces16 %>% 
  # filter(evangelical ==1) %>% 
  mutate(abany = recode(CC16_335, "1=1; 2=0; else =99")) %>% 
  # mutate(age = 2016 - birthyr) %>% 
  # group_by(age) %>% 
  ct(abany, commonweight_vv_post) %>% 
  filter(abany == 1) %>% 
  mutate(issue = "Gay Marriage")

graph <- bind_rows(ab, gay)


font_add_google("Oswald", "font")

showtext_auto()

ggplot(graph, aes(x=age, y = pct, group = issue, color = as.factor(issue))) + 
  geom_point() + 
  geom_smooth() +
  theme_minimal() + 
  scale_x_continuous(limits = c(18,75)) +
  theme(text=element_text(size=64, family="font")) +
  scale_y_continuous(limits = c(0, .60), labels = scales::percent) + theme(legend.position="none") +
  labs(x = "Age", y = "Percent in Favor", title = "Social Issue Support Among Evangelicals", caption = "Data: CCES 2016")  +
  annotate("text", x= 66, y = .22, label = "Gay Marriage", size = 24, family = "font") +
  annotate("text", x= 68, y = .38, label = "Abortion", size = 24, family = "font") +
  scale_color_d3()

ggsave("age_gay_aby.png", type = "cairo-png", width = 9)