ct_selection_untitled-87B197EB.R

one <- gss %>% 
  filter(year >= 1990) %>% 
  filter(year <= 2020) %>% 
  mutate(decades = frcode(year >= 1970 & year <= 1979 ~ "1970s",
                          year >= 1980 & year <= 1989 ~ "1980s",
                          year >= 1990 & year <= 1999 ~ "1990s",
                          year >= 2000 & year <= 2009 ~ "2000s",
                          year >= 2010 & year <= 2019 ~ "2010s", 
                          year >= 2020 ~ "2020s")) %>% 
  mutate(gd = frcode(god == 1 ~ "Don't Believe",
                     god == 2 ~ "No Way to Find Out",
                     god == 3 ~ "Some Higher Power",
                     god == 4 ~ "Believe Sometimes",
                     god == 5 ~ "Believe But Doubts",
                     god == 6 ~ "Believe No Doubts")) %>% 
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  filter(pid3 == "Republican" | pid3 == "Democrat") %>% 
  group_by(decades, pid3) %>% 
  ct(gd, wt = wtssall, show_na = FALSE) 


two <- gss %>% 
  filter(year >= 2020) %>% 
  mutate(decades = frcode(year >= 1970 & year <= 1979 ~ "1970s",
                          year >= 1980 & year <= 1989 ~ "1980s",
                          year >= 1990 & year <= 1999 ~ "1990s",
                          year >= 2000 & year <= 2009 ~ "2000s",
                          year >= 2010 & year <= 2019 ~ "2010s", 
                          year >= 2020 ~ "2020s")) %>% 
  mutate(gd = frcode(god == 1 ~ "Don't Believe",
                     god == 2 ~ "No Way to Find Out",
                     god == 3 ~ "Some Higher Power",
                     god == 4 ~ "Believe Sometimes",
                     god == 5 ~ "Believe But Doubts",
                     god == 6 ~ "Believe No Doubts")) %>% 
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  filter(pid3 == "Republican" | pid3 == "Democrat") %>% 
  group_by(decades, pid3) %>% 
  ct(gd, wt = wtssnrps, show_na = FALSE) 


belief <- bind_rows(one, two)
  

belief %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = fct_rev(pid3), y = pct, fill = fct_rev(gd))) +
  geom_col(color = "black") + 
  coord_flip() +
  facet_wrap(~ decades, ncol =1, strip.position = "top") +
  theme_rb() +
  scale_fill_manual(values = c(moma.colors("Connors", 6))) +
  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(gd == "Believe No Doubts" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 9, family = "font", color = "white") +
  geom_text(aes(label = ifelse(gd != "Believe No Doubts" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 9, family = "font", color = "black") +
  # geom_text(aes(label = ifelse(age2 == "36-44", paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "white") +
  theme(plot.title = element_text(size = 24)) +
  theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) +
  theme(strip.text.x.top = element_text(size = 20)) +
  theme(legend.text = element_text(size = 10)) +
  labs(x = "", y = "", title = "What Do You Believe About God", caption = "@ryanburge\nData: General Social Survey, 1990-2022") 
save("pid2_belief_god.png", wd = 9, ht = 8)


one <- gss %>% 
  filter(year <= 2020) %>% 
  mutate(decades = frcode(year >= 1970 & year <= 1979 ~ "1970s",
                          year >= 1980 & year <= 1989 ~ "1980s",
                          year >= 1990 & year <= 1999 ~ "1990s",
                          year >= 2000 & year <= 2009 ~ "2000s",
                          year >= 2010 & year <= 2019 ~ "2010s", 
                          year >= 2020 ~ "2020s")) %>% 
  gss_attend(attend) %>% 
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  filter(pid3 == "Republican" | pid3 == "Democrat") %>% 
  group_by(decades, pid3) %>% 
  ct(att, wt = wtssall, show_na = FALSE) 


two <- gss %>% 
  filter(year >= 2020) %>% 
  mutate(decades = frcode(year >= 1970 & year <= 1979 ~ "1970s",
                          year >= 1980 & year <= 1989 ~ "1980s",
                          year >= 1990 & year <= 1999 ~ "1990s",
                          year >= 2000 & year <= 2009 ~ "2000s",
                          year >= 2010 & year <= 2019 ~ "2010s", 
                          year >= 2020 ~ "2020s")) %>% 
  gss_attend(attend) %>% 
  
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  filter(pid3 == "Republican" | pid3 == "Democrat") %>% 
  group_by(decades, pid3) %>% 
  ct(att, wt = wtssnrps, show_na = FALSE) 


attend <- bind_rows(one, two)


attend %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = fct_rev(pid3), y = pct, fill = fct_rev(att))) +
  geom_col(color = "black") + 
  coord_flip() +
  facet_wrap(~ decades, ncol =1, strip.position = "top") +
  theme_rb() +
  scale_fill_manual(values = c(moma.colors("ustwo", 5))) +
  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 > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 9, family = "font", color = "black") +
  # geom_text(aes(label = ifelse(gd != "Believe No Doubts" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 9, family = "font", color = "black") +
  # geom_text(aes(label = ifelse(age2 == "36-44", paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "white") +
  theme(plot.title = element_text(size = 24)) +
  theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) +
  theme(strip.text.x.top = element_text(size = 20)) +
  theme(legend.text = element_text(size = 10)) +
  labs(x = "", y = "", title = "How Often Do You Attend Religious Services?", caption = "@ryanburge\nData: General Social Survey, 1972-2022") 
save("pid2_attend_gss.png", wd = 9, ht = 10)




one <- gss %>% 
  filter(year <= 2020) %>% 
  mutate(decades = frcode(year >= 1970 & year <= 1979 ~ "1970s",
                          year >= 1980 & year <= 1989 ~ "1980s",
                          year >= 1990 & year <= 1999 ~ "1990s",
                          year >= 2000 & year <= 2009 ~ "2000s",
                          year >= 2010 & year <= 2019 ~ "2010s", 
                          year >= 2020 ~ "2020s")) %>% 
  mutate(rel = frcode(relig == 1 ~ "Protestant", 
                      relig == 2 ~ "Catholic", 
                      relig == 4 ~ "No Religion", 
                      TRUE ~ "Something Else")) %>%  
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  filter(pid3 == "Republican" | pid3 == "Democrat") %>% 
  group_by(decades, pid3) %>% 
  ct(rel, wt = wtssall, show_na = FALSE) 


two <- gss %>% 
  filter(year >= 2020) %>% 
  mutate(decades = frcode(year >= 1970 & year <= 1979 ~ "1970s",
                          year >= 1980 & year <= 1989 ~ "1980s",
                          year >= 1990 & year <= 1999 ~ "1990s",
                          year >= 2000 & year <= 2009 ~ "2000s",
                          year >= 2010 & year <= 2019 ~ "2010s", 
                          year >= 2020 ~ "2020s")) %>% 
  mutate(rel = frcode(relig == 1 ~ "Protestant", 
                      relig == 2 ~ "Catholic", 
                      relig == 4 ~ "No Religion", 
                      TRUE ~ "Something Else")) %>%  
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  filter(pid3 == "Republican" | pid3 == "Democrat") %>% 
  group_by(decades, pid3) %>% 
  ct(rel, wt = wtssnrps, show_na = FALSE) 


belong <- bind_rows(one, two)


belong %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = fct_rev(pid3), y = pct, fill = fct_rev(rel))) +
  geom_col(color = "black") + 
  coord_flip() +
  facet_wrap(~ decades, ncol =1, strip.position = "top") +
  theme_rb() +
  scale_fill_manual(values = c(moma.colors("Budnitz", 4))) +
  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 > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 9, family = "font", color = "black") +
  # geom_text(aes(label = ifelse(gd != "Believe No Doubts" & pct > .05, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 9, family = "font", color = "black") +
  # geom_text(aes(label = ifelse(age2 == "36-44", paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "white") +
  theme(plot.title = element_text(size = 24)) +
  theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) +
  theme(strip.text.x.top = element_text(size = 20)) +
  theme(legend.text = element_text(size = 10)) +
  labs(x = "", y = "", title = "What is Your Present Religion", caption = "@ryanburge\nData: General Social Survey, 1972-2022") 
save("pid2_belonging_gss.png", wd = 9, ht = 10)



gg1 <- gss %>% 
  filter(partyid == 0 | partyid == 1 | partyid == 2) %>% 
  filter(year <= 2018) %>% 
  mutate(belief = case_when(god == 1 | god == 2 ~ 1, 
                            god == 3 | god == 4 | god == 5 | god == 6 ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(belief, wt = wtssall, ci = .84) %>% 
  na.omit()

gg2 <- gss %>% 
  filter(partyid == 0 | partyid == 1 | partyid == 2) %>% 
  filter(year > 2018) %>% 
  mutate(belief = case_when(god == 1 | god == 2 ~ 1, 
                            god == 3 | god == 4 | god == 5 | god == 6 ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(belief, wt = wtssnrps, ci = .84) %>% 
  na.omit()

bel <- bind_rows(gg1, gg2) %>% mutate(type = "Atheist/Agnostic Belief")

gg1 <- gss %>% 
  filter(partyid == 0 | partyid == 1 | partyid == 2) %>% 
  filter(year <= 2018) %>% 
  mutate(never = case_when(attend == 0 ~ 1, 
                           attend <= 8 ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(never, wt = wtssall, ci = .84) %>% 
  na.omit()

gg2 <- gss %>% 
  filter(year > 2018) %>% 
  filter(partyid == 0 | partyid == 1 | partyid == 2) %>% 
  mutate(never = case_when(attend == 0 ~ 1, 
                           attend <= 8 ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(never, wt = wtssnrps, ci = .84) %>% 
  na.omit()

att <- bind_rows(gg1, gg2) %>% mutate(type = "Never Attend")


gg1 <- gss %>% 
  filter(partyid == 0 | partyid == 1 | partyid == 2) %>% 
  filter(year <= 2018) %>% 
  mutate(none = case_when(relig == 4 ~ 1, 
                          TRUE ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(none, wt = wtssall, ci = .84) %>% 
  na.omit()

gg2 <- gss %>% 
  filter(partyid == 0 | partyid == 1 | partyid == 2) %>% 
  filter(year > 2018) %>% 
  mutate(none = case_when(relig == 4 ~ 1, 
                          TRUE ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(none, wt = wtssnrps, ci = .84) %>% 
  na.omit()

belong <- bind_rows(gg1, gg2)%>% mutate(type = "No Religious Affiliation")

dem <- bind_rows(bel, att, belong) %>% 
  mutate(pid2 = "Democrats")



gg1 <- gss %>% 
  filter(partyid == 4 | partyid == 5 | partyid == 6) %>% 
  filter(year <= 2018) %>% 
  mutate(belief = case_when(god == 1 | god == 2 ~ 1, 
                            god == 3 | god == 4 | god == 5 | god == 6 ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(belief, wt = wtssall, ci = .84) %>% 
  na.omit()

gg2 <- gss %>% 
  filter(partyid == 4 | partyid == 5 | partyid == 6) %>% 
  filter(year > 2018) %>% 
  mutate(belief = case_when(god == 1 | god == 2 ~ 1, 
                            god == 3 | god == 4 | god == 5 | god == 6 ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(belief, wt = wtssnrps, ci = .84) %>% 
  na.omit()

bel <- bind_rows(gg1, gg2) %>% mutate(type = "Atheist/Agnostic Belief")

gg1 <- gss %>% 
  filter(partyid == 4 | partyid == 5 | partyid == 6) %>% 
  filter(year <= 2018) %>% 
  mutate(never = case_when(attend == 0 ~ 1, 
                           attend <= 8 ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(never, wt = wtssall, ci = .84) %>% 
  na.omit()

gg2 <- gss %>% 
  filter(year > 2018) %>% 
  filter(partyid == 4 | partyid == 5 | partyid == 6) %>% 
  mutate(never = case_when(attend == 0 ~ 1, 
                           attend <= 8 ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(never, wt = wtssnrps, ci = .84) %>% 
  na.omit()

att <- bind_rows(gg1, gg2) %>% mutate(type = "Never Attend")


gg1 <- gss %>% 
  filter(partyid == 4 | partyid == 5 | partyid == 6) %>% 
  filter(year <= 2018) %>% 
  mutate(none = case_when(relig == 4 ~ 1, 
                          TRUE ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(none, wt = wtssall, ci = .84) %>% 
  na.omit()

gg2 <- gss %>% 
  filter(partyid == 4 | partyid == 5 | partyid == 6) %>% 
  filter(year > 2018) %>% 
  mutate(none = case_when(relig == 4 ~ 1, 
                          TRUE ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(none, wt = wtssnrps, ci = .84) %>% 
  na.omit()

belong <- bind_rows(gg1, gg2)%>% mutate(type = "No Religious Affiliation")

rep <- bind_rows(bel, att, belong) %>% 
  mutate(pid2 = "Republicans")

both <- bind_rows(dem, rep)

both %>% 
  ggplot(., aes(x = year, y = mean, color = pid2, group = pid2)) +
  geom_point(stroke = .25, shape = 21) +
  geom_smooth(se = FALSE) +
  facet_wrap(~ type) +
  scale_color_manual(values = c("dodgerblue3", 'firebrick3')) +
  scale_y_continuous(labels = percent, limits = c(0, .35)) +
  theme_rb(legend = TRUE) + 
  theme(strip.text = element_text(size = 20)) +
  labs(x = "", y = "", title = "Behavior, Belief, and Belonging in Democrats versus Republicans", caption = "@ryanburge\nData: General Social Survey, 1972-2022")
save("three_b_two_pid_new22.png")



gg1 <- gss %>% 
  filter(year <= 2018) %>% 
  filter(year != 1982) %>% 
  filter(year != 1987) %>% 
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  mutate(white = case_when(race == 1 ~ 1, TRUE ~ 0)) %>% 
  mutate(xtn = case_when(relig == 1 | relig == 2 | relig == 10 | relig == 11 ~ 1,
                         TRUE ~0)) %>% 
  mutate(both = xtn + white) %>% 
  mutate(both = case_when(both == 2 ~ 1, 
                          both <= 1 ~ 0)) %>% 
  group_by(pid3, year) %>% 
  mean_ci(both, wt = wtssall)

gg2 <- gss %>% 
  filter(year == 1982  | year == 1987) %>% 
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  mutate(white = case_when(race == 1 ~ 1, TRUE ~ 0)) %>% 
  mutate(xtn = case_when(relig == 1 | relig == 2 | relig == 10 | relig == 11 ~ 1,
                         TRUE ~0)) %>% 
  mutate(both = xtn + white) %>% 
  mutate(both = case_when(both == 2 ~ 1, 
                          both <= 1 ~ 0)) %>% 
  group_by(pid3, year) %>% 
  mean_ci(both, wt = oversamp)

gg3 <- gss %>% 
  filter(year >= 2020) %>% 
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  mutate(white = case_when(race == 1 ~ 1, TRUE ~ 0)) %>% 
  mutate(xtn = case_when(relig == 1 | relig == 2 | relig == 10 | relig == 11 ~ 1,
                         TRUE ~0)) %>% 
  mutate(both = xtn + white) %>% 
  mutate(both = case_when(both == 2 ~ 1, 
                          both <= 1 ~ 0)) %>% 
  group_by(pid3, year) %>% 
  mean_ci(both, wt = wtssnrps)

both <- bind_rows(gg1, gg2, gg3) %>% filter(pid3 != "NA")

both %>% 
  ggplot(., aes(x = year, y = mean, color = pid3, group = pid3)) +
  geom_point(stroke = .5, shape = 21) +
  geom_labelsmooth(aes(label = pid3),  method = "loess", formula = y ~ x, family = "font", linewidth = 1, text_smoothing = 30, size = 6, linewidth = 1, boxlinewidth = 0.3, hjust = .75) +
  pid3_color() +
  theme_rb() + 
  y_pct() + 
  add_text(x = 1972, y = .935, word = "91%", sz = 6) +
  add_text(x = 1972, y = .79, word = "77%", sz = 6) +
  add_text(x = 1972, y = .68, word = "71%", sz = 6) +
  add_text(x = 2022, y = .31, word = "33%", sz = 6) +
  add_text(x = 2022, y = .40, word = "38%", sz = 6) +
  add_text(x = 2022, y = .75, word = "73%", sz = 6) +
  labs(x = "Year",  y = "", title = "Share of Each Party That is White and Christian", caption = "@ryanburge\nData: General Social Survey, 1972-2022")
save("gss_pid3_wxtn22.png")