ct_selection_untitled-E7769953.R

library(rio)
library(janitor)

pew <- import("E://data/atp106.sav") %>% as_tibble() %>% clean_names()

gg <- pew %>% 
  mutate(ev = f_born) %>% 
  mutate(rel = frcode(f_relig == 1 & ev == 1 ~ "Evangelical Protestant", 
                      f_relig == 1 & ev == 2 ~ "Non-Evangelical Prot.",
                    f_relig == 2 ~ "Catholic", 
                    f_relig == 3 | f_relig == 4 | f_relig == 5 | f_relig == 6 | f_relig == 7 | f_relig == 8 ~ "Other World Religions", 
                    f_relig == 9 ~ "Atheist",
                    f_relig == 10 ~ "Agnostic",
                    f_relig == 12 ~ "Nothing in Particular")) %>% 
  mutate(live = ftrper_a_w106) %>% 
  mutate(live = frcode(live == 5 ~ "Not At All", 
                       live == 4 ~ "A Little Bit", 
                       live == 3 ~ "Somewhat", 
                       live == 2 ~ "Mostly", 
                       live == 1 ~ "Completely")) %>% 
  group_by(rel) %>% 
  ct(live, wt = weight_w106, show_na = FALSE)


gg %>% 
  filter(rel != "NA") %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(live))) +
  geom_col(color = "black") +
  coord_flip() +
  facet_wrap(~ rel, ncol =1, strip.position = "left") +
  scale_fill_gdocs() +
  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 = "I want to live the best life I can right now and not worry too much about the future", caption = "@ryanburge + @religiondata\nData: Pew American Trends Panel 106") 
save("live_best_life.png", wd = 9, ht =4)



gg <- pew %>% 
  mutate(ev = f_born) %>% 
  mutate(rel = frcode(f_relig == 1 & ev == 1 ~ "Evangelical Protestant", 
                      f_relig == 1 & ev == 2 ~ "Non-Evangelical Prot.",
                      f_relig == 2 ~ "Catholic", 
                      f_relig == 3 | f_relig == 4 | f_relig == 5 | f_relig == 6 | f_relig == 7 | f_relig == 8 ~ "Other World Religions", 
                      f_relig == 9 ~ "Atheist",
                      f_relig == 10 ~ "Agnostic",
                      f_relig == 12 ~ "Nothing in Particular")) %>% 
  mutate(live = ftrper_b_w106) %>% 
  mutate(live = frcode(live == 5 ~ "Not At All", 
                       live == 4 ~ "A Little Bit", 
                       live == 3 ~ "Somewhat", 
                       live == 2 ~ "Mostly", 
                       live == 1 ~ "Completely")) %>% 
  group_by(rel) %>% 
  ct(live, wt = weight_w106, show_na = FALSE)


gg %>% 
  filter(rel != "NA") %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(live))) +
  geom_col(color = "black") +
  coord_flip() +
  facet_wrap(~ rel, ncol =1, strip.position = "left") +
  scale_fill_gdocs() +
  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 = "I would be willing to make sacrifices in the way I live today if I knew it would help future generations", caption = "@ryanburge + @religiondata\nData: Pew American Trends Panel 106") 
save("live_best_life2.png", wd = 9, ht =4)


pew %>% 
  mutate(ev = f_born) %>% 
  mutate(rel = frcode(f_relig == 1 & ev == 1 ~ "Evangelical Protestant", 
                      f_relig == 1 & ev == 2 ~ "Non-Evangelical Prot.",
                      f_relig == 2 ~ "Catholic", 
                      f_relig == 3 | f_relig == 4 | f_relig == 5 | f_relig == 6 | f_relig == 7 | f_relig == 8 ~ "Other World Religions", 
                      f_relig == 9 ~ "Atheist",
                      f_relig == 10 ~ "Agnostic",
                      f_relig == 12 ~ "Nothing in Particular")) %>% 
  group_by(rel) %>% 
  mutate(val = case_when(species_w106 == 1 ~ 1, 
                         species_w106 == 2 ~ 0)) %>% 
  mean_ci(val, wt = weight_w106, ci = .84)


pew %>% 
  mutate(ev = f_born) %>% 
  mutate(rel = frcode(f_relig == 1 & ev == 1 ~ "Evangelical Protestant", 
                      f_relig == 1 & ev == 2 ~ "Non-Evangelical Prot.",
                      f_relig == 2 ~ "Catholic", 
                      f_relig == 3 | f_relig == 4 | f_relig == 5 | f_relig == 6 | f_relig == 7 | f_relig == 8 ~ "Other World Religions", 
                      f_relig == 9 ~ "Atheist",
                      f_relig == 10 ~ "Agnostic",
                      f_relig == 12 ~ "Nothing in Particular")) %>% 
  group_by(rel) %>% 
  mutate(val = case_when(sacredearth1_w106 == 1 ~ 1, 
                         sacredearth1_w106 == 2 ~ 0)) %>% 
  mean_ci(val, wt = weight_w106, ci = .84)


gg <- pew %>% 
  mutate(ev = f_born) %>% 
  mutate(rel = frcode(f_relig == 1 & ev == 1 ~ "Evangelical Protestant", 
                      f_relig == 1 & ev == 2 ~ "Non-Evangelical Prot.",
                      f_relig == 2 ~ "Catholic", 
                      f_relig == 3 | f_relig == 4 | f_relig == 5 | f_relig == 6 | f_relig == 7 | f_relig == 8 ~ "Other World Religions", 
                      f_relig == 9 ~ "Atheist",
                      f_relig == 10 ~ "Agnostic",
                      f_relig == 12 ~ "Nothing in Particular")) %>% 
  mutate(climate = clmsrs1_w106) %>% 
  mutate(climate = frcode(climate == 5 ~ "Not a Problem", 
                          climate == 4 ~ "Not too Serious", 
                          climate == 3 ~ "Somewhat Serious", 
                          climate == 2 ~ "Very Serious", 
                          climate == 1 ~ "Extremely Serious")) %>% 
  group_by(rel) %>% 
  ct(climate, wt = weight_w106, show_na = FALSE)


lvl <- gg %>% 
  filter(climate == "Extremely Serious") %>% 
  select(rel, sort = pct)


gg <- left_join(gg, lvl)

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


gg %>% 
  filter(rel != "NA") %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(climate))) +
  geom_col(color = "black") +
  coord_flip() +
  facet_wrap(~ rel, ncol =1, strip.position = "left") +
  scale_fill_gdocs() +
  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 = "In your view, is global climate change a...", caption = "@ryanburge + @religiondata\nData: Pew American Trends Panel 106") 
save("climate_change_problems.png", wd = 9, ht =4)




gg <- pew %>% 
  mutate(ev = f_born) %>% 
  mutate(rel = frcode(f_relig == 1 & ev == 1 ~ "Evangelical Protestant", 
                      f_relig == 1 & ev == 2 ~ "Non-Evangelical Prot.",
                      f_relig == 2 ~ "Catholic", 
                      f_relig == 3 | f_relig == 4 | f_relig == 5 | f_relig == 6 | f_relig == 7 | f_relig == 8 ~ "Other World Religions", 
                      f_relig == 9 ~ "Atheist",
                      f_relig == 10 ~ "Agnostic",
                      f_relig == 12 ~ "Nothing in Particular")) %>% 
  mutate(pid3 = frcode(f_party_final == 2 ~ "Dem.", 
                       f_party_final == 3 ~ "Ind.", 
                       f_party_final == 1 ~ "Rep.")) %>% 
  mutate(climate = clmsrs1_w106) %>% 
  mutate(climate = case_when(climate == 1 | climate == 2 ~ 1,
                             climate == 3 | climate == 4 | climate == 5 ~ 0)) %>% 
  group_by(rel, pid3) %>% 
  mean_ci(climate, wt = weight_w106, ci = .84) %>% 
  filter(pid3 != "NA")

gg %>% 
  filter(rel != "NA") %>% 
  mutate(lab = round(mean, 2)) %>% 
  ggplot(., aes(x = pid3, y = mean, fill = pid3)) +
  geom_col(color = "black") +
  facet_wrap(~ rel, nrow = 2) +
  pid3_fill() +
  y_pct() +
  theme_rb() + 
  error_bar() +
  lab_bar(top = FALSE, type = lab, pos = .085, sz = 8) +
  labs(x = "", y = "", title = "Share Saying Climate Change is an Extremely/Very Serious Problem", caption = "@ryanburge + @religiondata\nData: Pew American Trends Panel 106")
save("climate_change_pid3_rel.png")
  


gg <- pew %>% 
  mutate(ev = f_born) %>% 
  mutate(rel = frcode(f_relig == 1 & ev == 1 ~ "Evangelical Protestant", 
                      f_relig == 1 & ev == 2 ~ "Non-Evangelical Prot.",
                      f_relig == 2 ~ "Catholic", 
                      f_relig == 3 | f_relig == 4 | f_relig == 5 | f_relig == 6 | f_relig == 7 | f_relig == 8 ~ "Other World Religions", 
                      f_relig == 9 ~ "Atheist",
                      f_relig == 10 ~ "Agnostic",
                      f_relig == 12 ~ "Nothing in Particular")) %>% 
  mutate(pid3 = frcode(f_party_final == 2 ~ "Dem.", 
                       f_party_final == 3 ~ "Ind.", 
                       f_party_final == 1 ~ "Rep.")) %>% 
  mutate(climate = clim1a_w106) %>% 
  mutate(climate = case_when(climate == 1 ~ 1,
                             climate == 2 | climate == 3 ~ 0)) %>% 
  group_by(rel, pid3) %>% 
  mean_ci(climate, wt = weight_w106, ci = .84) %>% 
  filter(pid3 != "NA")


gg %>% 
  filter(rel != "NA") %>% 
  mutate(lab = round(mean, 2)) %>% 
  ggplot(., aes(x = pid3, y = mean, fill = pid3)) +
  geom_col(color = "black") +
  facet_wrap(~ rel, nrow = 2) +
  pid3_fill() +
  y_pct() +
  theme_rb() + 
  error_bar() +
  geom_text(aes(y = .085, label = ifelse(mean < .99, paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 8, family = "font")   +
  geom_text(aes(y = .085, label = ifelse(mean > .99, paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 6, family = "font")   +
  labs(x = "", y = "", title = "The Earth is Getting Warmer Due to Human Activity Such as Burning Fossil Fuels", caption = "@ryanburge + @religiondata\nData: Pew American Trends Panel 106")
save("human_activity_pid3_rel.png")




gg <- pew %>% 
  mutate(ev = f_born) %>% 
  mutate(rel = frcode(f_relig == 1 & ev == 1 ~ "Evangelical Protestant", 
                      f_relig == 1 & ev == 2 ~ "Non-Evangelical Prot.",
                      f_relig == 2 ~ "Catholic", 
                      f_relig == 3 | f_relig == 4 | f_relig == 5 | f_relig == 6 | f_relig == 7 | f_relig == 8 ~ "Other World Religions")) %>% 
  mutate(pid3 = frcode(f_party_final == 2 ~ "Dem.", 
                       f_party_final == 1 ~ "Rep.")) %>% 
  mutate(climate = humntr_a_w106) %>% 
  mutate(climate = frcode(climate == 5 ~ "Not At All", 
                          climate == 4 ~ "A Little Bit", 
                          climate == 3 ~ "Somewhat", 
                          climate == 2 ~ "Mostly", 
                          climate == 1 ~ "Completely")) %>% 
  group_by(rel, pid3) %>% 
  ct(climate, wt = weight_w106, show_na = FALSE) %>% 
  filter(pid3 != "NA")




gg %>% 
  filter(rel != "NA") %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = fct_rev(pid3), y = pct, fill = fct_rev(climate))) +
  geom_col(color = "black") +
  coord_flip() +
  facet_wrap(~ rel, ncol =1, strip.position = "top") +
  scale_fill_gdocs() +
  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()) +
  theme(plot.title = element_text(size = 15)) +
  theme(strip.text = element_text(size = 20)) +
  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 = "God gave humans the right to use the Earth, including the plants and animals, for humanity's benefit", caption = "@ryanburge + @religiondata\nData: Pew American Trends Panel 106") 
save("use_earth.png", wd = 9, ht =6)



gg <- pew %>% 
  mutate(ev = f_born) %>% 
  mutate(rel = frcode(f_relig == 1 & ev == 1 ~ "Evangelical Protestant", 
                      f_relig == 1 & ev == 2 ~ "Non-Evangelical Prot.",
                      f_relig == 2 ~ "Catholic", 
                      f_relig == 3 | f_relig == 4 | f_relig == 5 | f_relig == 6 | f_relig == 7 | f_relig == 8 ~ "Other World Religions")) %>% 
  mutate(pid3 = frcode(f_party_final == 2 ~ "Dem.", 
                       f_party_final == 1 ~ "Rep.")) %>% 
  mutate(climate = humntr_b_w106) %>% 
  mutate(climate = frcode(climate == 5 ~ "Not At All", 
                          climate == 4 ~ "A Little Bit", 
                          climate == 3 ~ "Somewhat", 
                          climate == 2 ~ "Mostly", 
                          climate == 1 ~ "Completely")) %>% 
  group_by(rel, pid3) %>% 
  ct(climate, wt = weight_w106, show_na = FALSE) %>% 
  filter(pid3 != "NA")




gg %>% 
  filter(rel != "NA") %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = fct_rev(pid3), y = pct, fill = fct_rev(climate))) +
  geom_col(color = "black") +
  coord_flip() +
  facet_wrap(~ rel, ncol =1, strip.position = "top") +
  scale_fill_gdocs() +
  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()) +
  theme(plot.title = element_text(size = 15)) +
  theme(strip.text = element_text(size = 20)) +
  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 = "God gave humans a duty to protect and care for the Earth, including the plants and animals", caption = "@ryanburge + @religiondata\nData: Pew American Trends Panel 106") 
save("protect_earth.png", wd = 9, ht =6)



gg1 <- pew %>% 
  mutate(ev = f_born) %>% 
  mutate(rel = frcode(f_relig == 1 & ev == 1 ~ "Evangelical Protestant", 
                      f_relig == 1 & ev == 2 ~ "Non-Evangelical Prot.",
                      f_relig == 2 ~ "Catholic", 
                      f_relig == 3 | f_relig == 4 | f_relig == 5 | f_relig == 6 | f_relig == 7 | f_relig == 8 ~ "Other World Religions", 
                      f_relig == 9 ~ "Atheist",
                      f_relig == 10 ~ "Agnostic",
                      f_relig == 12 ~ "Nothing in Particular")) %>% 
  mutate(pid3 = frcode(f_party_final == 2 ~ "Dem.", 
                       f_party_final == 3 ~ "Ind.", 
                       f_party_final == 1 ~ "Rep.")) %>% 
  mutate(climate = clmsrs1_w106) %>% 
  mutate(climate = case_when(climate == 1 | climate == 2 ~ 1,
                             climate == 3 | climate == 4 | climate == 5 ~ 0)) %>% 
  mutate(age4 = f_agecat) %>% 
  mutate(age4 = frcode(age4 == 1 ~ "18-29", 
                       age4 == 2 ~ "30-49", 
                       age4 == 3 ~ "50-64", 
                       age4 == 4 ~ "65+")) %>% 
  group_by(rel, age4) %>% 
  mean_ci(climate, wt = weight_w106, ci = .84) %>% filter(age4 != "NA")


gg2 <- pew %>% 
  mutate(ev = f_born) %>% 
  mutate(rel = frcode(f_relig == 1 & ev == 1 ~ "Evangelical Protestant", 
                      f_relig == 1 & ev == 2 ~ "Non-Evangelical Prot.",
                      f_relig == 2 ~ "Catholic", 
                      f_relig == 3 | f_relig == 4 | f_relig == 5 | f_relig == 6 | f_relig == 7 | f_relig == 8 ~ "Other World Religions", 
                      f_relig == 9 ~ "Atheist",
                      f_relig == 10 ~ "Agnostic",
                      f_relig == 12 ~ "Nothing in Particular")) %>% 
  mutate(pid3 = frcode(f_party_final == 2 ~ "Dem.", 
                       f_party_final == 3 ~ "Ind.", 
                       f_party_final == 1 ~ "Rep.")) %>% 
  mutate(climate = clmsrs1_w106) %>% 
  mutate(climate = case_when(climate == 1 | climate == 2 ~ 1,
                             climate == 3 | climate == 4 | climate == 5 ~ 0)) %>% 
  mutate(age4 = f_agecat) %>% 
  mutate(age4 = frcode(age4 == 1 ~ "18-29", 
                       age4 == 2 ~ "30-49", 
                       age4 == 3 ~ "50-64", 
                       age4 == 4 ~ "65+")) %>% 
  group_by(age4) %>% 
  mean_ci(climate, wt = weight_w106, ci = .84) %>% filter(age4 != "NA") %>% 
  mutate(rel = "Entire Sample")

gg <- bind_rows(gg1, gg2)

gg$rel <- factor(gg$rel, levels = c("Entire Sample", "Evangelical Protestant", "Non-Evangelical Prot.", "Catholic", "Other World Religions", "Atheist", "Agnostic", "Nothing in Particular"))


gg %>% 
  filter(rel != "NA") %>% 
  mutate(lab = round(mean, 2)) %>% 
  ggplot(., aes(x = age4, y = mean, fill = age4)) +
  geom_col(color = "black") +
  facet_wrap(~ rel, nrow = 2) +
  scale_fill_gdocs() +
  y_pct() +
  theme_rb() + 
  error_bar() +
  lab_bar(top = FALSE, type = lab, pos = .085, sz = 6) +
  labs(x = "", y = "", title = "Share Saying Climate Change is an Extremely/Very Serious Problem", caption = "@ryanburge + @religiondata\nData: Pew American Trends Panel 106")
save("climate_change_age4_rel.png")






gg1 <- pew %>% 
  filter(f_born == 1 & f_relig == 1) %>% 
  filter(f_party_final == 1) %>% 
  mutate(age4 = f_agecat) %>% 
  mutate(age4 = frcode(age4 == 1 ~ "18-29", 
                       age4 == 2 ~ "30-49", 
                       age4 == 3 ~ "50-64", 
                       age4 == 4 ~ "65+")) %>% 
  mutate(climate = clim1a_w106) %>% 
  mutate(climate = frcode(climate == 1 ~ "Mostly Human Activity", 
                          climate == 2 ~ "Natural Weather Patterns", 
                          climate == 3 ~ "No Evidence of Warming", 
                          climate == 8 ~ "Not Sure")) %>% 
  group_by(age4) %>% 
  ct(climate, wt = weight_w106, show_na = FALSE) %>% na.omit() %>% 
  mutate(grp = "Evangelical Republicans")


gg2 <- pew %>% 
  filter(f_party_final == 1) %>% 
  mutate(age4 = f_agecat) %>% 
  mutate(age4 = frcode(age4 == 1 ~ "18-29", 
                       age4 == 2 ~ "30-49", 
                       age4 == 3 ~ "50-64", 
                       age4 == 4 ~ "65+")) %>% 
  mutate(climate = clim1a_w106) %>% 
  mutate(climate = frcode(climate == 1 ~ "Mostly Human Activity", 
                          climate == 2 ~ "Natural Weather Patterns", 
                          climate == 3 ~ "No Evidence of Warming", 
                          climate == 8 ~ "Not Sure")) %>% 
  group_by(age4) %>% 
  ct(climate, wt = weight_w106, show_na = FALSE) %>% na.omit() %>% 
  mutate(grp = "All Republicans")


gg3 <- pew %>% 
  mutate(age4 = f_agecat) %>% 
  mutate(age4 = frcode(age4 == 1 ~ "18-29", 
                       age4 == 2 ~ "30-49", 
                       age4 == 3 ~ "50-64", 
                       age4 == 4 ~ "65+")) %>% 
  mutate(climate = clim1a_w106) %>% 
  mutate(climate = frcode(climate == 1 ~ "Mostly Human Activity", 
                          climate == 2 ~ "Natural Weather Patterns", 
                          climate == 3 ~ "No Evidence of Warming", 
                          climate == 8 ~ "Not Sure")) %>% 
  group_by(age4) %>% 
  ct(climate, wt = weight_w106, show_na = FALSE) %>% na.omit() %>% 
  mutate(grp = "Entire Sample")


gg4 <- pew %>% 
  filter(f_party_final == 2) %>% 
  mutate(age4 = f_agecat) %>% 
  mutate(age4 = frcode(age4 == 1 ~ "18-29", 
                       age4 == 2 ~ "30-49", 
                       age4 == 3 ~ "50-64", 
                       age4 == 4 ~ "65+")) %>% 
  mutate(climate = clim1a_w106) %>% 
  mutate(climate = frcode(climate == 1 ~ "Mostly Human Activity", 
                          climate == 2 ~ "Natural Weather Patterns", 
                          climate == 3 ~ "No Evidence of Warming", 
                          climate == 8 ~ "Not Sure")) %>% 
  group_by(age4) %>% 
  ct(climate, wt = weight_w106, show_na = FALSE) %>% na.omit() %>% 
  mutate(grp = "All Democrats")

all <- bind_rows(gg1, gg2, gg3, gg4)

all$grp <- factor(all$grp, levels = c("Entire Sample", "All Democrats", "All Republicans", "Evangelical Republicans"))


all %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = fct_rev(grp), y = pct, fill = fct_rev(climate))) +
  geom_col(color = "black") +
  coord_flip() +
  facet_wrap(~ age4, ncol =1, strip.position = "top") +
  scale_fill_gdocs() +
  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()) +
  theme(plot.title = element_text(size = 13)) +
  theme(strip.text = element_text(size = 20)) +
  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 = "Which of these three statements about the Earth's temperature comes closest to your view?", caption = "@ryanburge + @religiondata\nData: Pew American Trends Panel 106") 
save("views_warming_age4_grps.png", wd = 9, ht =8)



gg1 <- pew %>% 
  filter(f_born == 1 & f_relig == 1) %>% 
  mutate(age4 = f_agecat) %>% 
  mutate(age4 = frcode(age4 == 1 ~ "18-29", 
                       age4 == 2 ~ "30-49", 
                       age4 == 3 ~ "50-64", 
                       age4 == 4 ~ "65+")) %>% 
  group_by(age4) %>% 
  mutate(future = case_when(ftrper_a_w106 == 1 | ftrper_a_w106 == 2 ~ 1, 
                            ftrper_a_w106 == 3 | ftrper_a_w106 == 3 | ftrper_a_w106 == 5 ~ 0)) %>% 
  mean_ci(future, wt = weight_w106, ci = .84) %>% na.omit() %>% 
  mutate(grp = "Evangelical Republicans")


graph <- pew %>% 
  mutate(ev = f_born) %>% 
  mutate(rel = frcode(f_relig == 1 & ev == 1 ~ "Evangelical Protestant", 
                      f_relig == 1 & ev == 2 ~ "Non-Evangelical Prot.",
                      f_relig == 2 ~ "Catholic", 
                      f_relig == 3 | f_relig == 4 | f_relig == 5 | f_relig == 6 | f_relig == 7 | f_relig == 8 ~ "Other World Religions")) %>% 
  mutate(sermon = sermonclm_w106) %>% 
  mutate(sermon = frcode(sermon == 5 ~ "None", 
                         sermon == 4 ~ "A Little", 
                         sermon == 3 ~ "Some", 
                         sermon == 2 | sermon == 1 ~ "Quite a bit/Great Deal")) %>% 
  group_by(rel) %>% 
  ct(sermon, wt = weight_w106, show_na = FALSE) %>% 
  na.omit()



graph %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(sermon))) +
  geom_col(color = "black") +
  coord_flip() +
  facet_wrap(~ rel, ncol =1, strip.position = "left") +
  scale_fill_gdocs() +
  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()) +
  theme(plot.title = element_text(size = 13)) +
  # theme(strip.text = element_text(size = 20)) +
  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 = "How much discussion of climate change is there in sermons at your house of worship?", caption = "@ryanburge + @religiondata\nData: Pew American Trends Panel 106") 
save("sermons_climate.png", wd = 9, ht =3.5)