RStudio_ct_selection_untitled_3EFD4A51

ns <- read.fst("D://ns_full.fst") %>% as_tibble()


gg <- ns %>% 
  mutate(pid2 = frcode(pid3 == 1 ~ "Democrat",
                       pid3 == 3 ~ "Independent",
                       pid3 == 2 ~ "Republican")) %>% 
  mutate(xtn = statements_gender_identity) %>% 
  mutate(xtn = frcode(xtn == 4 ~ "Strongly Disagree",
                      xtn == 3 ~ "Somewhat Disagree",
                      xtn == 2 ~ "Somewhat Agree",
                      xtn == 1 ~ "Strongly Agree")) %>% 
  group_by(pid2) %>% 
  ct(xtn, wt = weight, show_na = FALSE) %>% na.omit()

gg1 <- ns %>% 
  mutate(xtn = statements_gender_identity) %>% 
  mutate(xtn = frcode(xtn == 4 ~ "Strongly Disagree",
                      xtn == 3 ~ "Somewhat Disagree",
                      xtn == 2 ~ "Somewhat Agree",
                      xtn == 1 ~ "Strongly Agree")) %>% 
  ct(xtn, wt = weight, show_na = FALSE) %>% na.omit() %>% 
  mutate(pid2 = "Entire Sample")

graph <- bind_rows(gg, gg1)

graph$pid2 <- factor(graph$pid2, levels = c("Entire Sample", "Democrat", "Independent", "Republican"))


graph %>% 
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(xtn))) +
  geom_col(color = "black") + 
  coord_flip() +
  facet_wrap(~ pid2, ncol =1, strip.position = "left") +
  scale_fill_manual(values = c("#EE4035", "#F37736", "#7BC043", "#0492CF")) +
  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") +
  labs(x = "", y = "", title = "Agreement with this statement: There are only two genders- male and female", subtitle = "", caption = "@ryanburge\nData: Nationscape (July 2019-June 2020)") +
  ggsave("E://two_genders.png", width = 9, height = 3)


graph <- ns %>% 
  mutate(trans = statements_gender_identity) %>% 
  mutate(trans = case_when(trans == 1 | trans == 2 ~ 1, 
                           trans == 3 | trans == 4 ~ 0)) %>% 
  group_by(wave) %>% 
  mean_ci(trans, wt = weight, ci = .84) %>% 
  na.omit() %>% 
  mutate(pid2 = "Entire Sample")

graph1 <- ns %>% 
  mutate(trans = statements_gender_identity) %>% 
  mutate(trans = case_when(trans == 1 | trans == 2 ~ 1, 
                           trans == 3 | trans == 4 ~ 0)) %>% 
  mutate(pid2 = frcode(pid3 == 1 ~ "Democrat",
                       pid3 == 3 ~ "Independent",
                       pid3 == 2 ~ "Republican")) %>% 
  group_by(wave, pid2) %>% 
  mean_ci(trans, wt = weight, ci = .84) %>% 
  na.omit() 

gg <- bind_rows(graph, graph1)

gg$pid2 <- factor(gg$pid2, levels = c("Entire Sample", "Democrat", "Independent", "Republican"))

every_nth = function(n) {
  return(function(x) {x[c(TRUE, rep(FALSE, n - 1))]})
}

gg %>% 
  ggplot(., aes(x = wave, y = mean, color = pid2, group = pid2)) +
  geom_point() + 
  smooth() +
  scale_color_manual(values = c("black", "dodgerblue3", "forestgreen", "firebrick3")) +
  theme_rb(legend = TRUE) +
  y_pct() + 
  scale_x_discrete(breaks = every_nth(n = 3)) +
  labs(x = "", y = "Share Agreeing", title = "Agreement with this statement: There are only two genders- male and female", caption = "@ryanburge\nData: Nationscape (July 2019-June 2020)") +
  ggsave("E://two_gender_long.png", height = 7)
  


gg <- ns %>% 
  ns_trad(religion) %>% 
  group_by(trad) %>% 
  mutate(xtn = statements_gender_identity) %>% 
  mutate(xtn = frcode(xtn == 4 ~ "Strongly Disagree",
                      xtn == 3 ~ "Somewhat Disagree",
                      xtn == 2 ~ "Somewhat Agree",
                      xtn == 1 ~ "Strongly Agree")) %>% 
  ct(xtn, wt = weight, show_na = FALSE) %>% na.omit()


lvl <- gg %>% 
  filter(xtn == "Strongly Agree") %>% 
  select(trad, sort = pct)


gg <- left_join(gg, lvl)

gg$trad <- fct_reorder(gg$trad, gg$sort, .desc = TRUE)


gg %>% 
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(xtn))) +
  geom_col(color = "black") + 
  coord_flip() +
  facet_wrap(~ trad, ncol =1, strip.position = "left") +
  scale_fill_manual(values = c("#EE4035", "#F37736", "#7BC043", "#0492CF")) +
  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") +
  labs(x = "", y = "", title = "Agreement with this statement: There are only two genders- male and female", subtitle = "", caption = "@ryanburge\nData: Nationscape (July 2019-June 2020)") +
  ggsave("E://two_genders_trad.png", width = 9, height = 6)


reg <- ns %>% 
  filter(age <= 80) %>% 
  mutate(gender = frcode(gender == 2 ~ "Men",
                         gender == 1 ~ "Women")) %>% 
  mutate(trans = statements_gender_identity) %>% 
  mutate(trans = case_when(trans == 1 | trans == 2 ~ 1, 
                           trans == 3 | trans == 4 ~ 0)) %>% 
  mutate(white = case_when(race_ethnicity == 1 & hispanic == 1 ~ 1, TRUE ~ 0)) %>% 
  mutate(pid2 = frcode(pid3 == 1 ~ "Democrat",
                       pid3 == 3 ~ "Independent", 
                       pid3 == 2 ~ "Republican")) %>% 
  mutate(evan = frcode(is_evangelical == 1 ~ "Evangelical", 
                          is_evangelical == 2 ~ "Non-Evangelical")) %>%
  select(gender, age, trans, education, income = household_income, pid2, evan, white)

tt <- glm(trans ~ age*pid2*evan + white + gender + education + income, family = "binomial", data = reg)

plot <- interact_plot(tt, pred= age, modx = pid2, mod2 = evan, int.width = .76, interval = TRUE, mod2.labels = c("Evangelical", "Non-Evangelical")) 

plot +
  theme_rb(legend = TRUE) + 
  pid3_color() +
  pid3_fill() +
  y_pct() + 
  labs(x = "Age", y = "Estimate of Agreement", title = "Agreement with this statement: There are only two genders- male and female", caption = "@ryanburge\nData: Nationscape (July 2019-June 2020)") +
  ggsave("E://trans_interact.png", type = "cairo-png")