ct_selection_untitled-218FB984.R

aaa1 <- gss %>% 
  filter(year == 1989 | year == 1990 | year == 1991 | year == 1993) %>% 
  group_by(age) %>% 
  mutate(never = case_when(sexfreq == 2 | sexfreq == 3 | sexfreq == 4 | sexfreq == 5 | sexfreq == 6 ~ 1, 
                           sexfreq == 0 | sexfreq == 1 ~ 0)) %>% 
  group_by(age) %>% 
  mean_ci(never, wt = wtssall, ci = .84) %>% 
  na.omit() %>% 
  mutate(year = "1989 to 1993")


one <- gss %>% 
  filter(year == 2016 | year == 2018) %>% 
  select(age, sexfreq, weight = wtssall)

two <- gss %>% 
  filter(year == 2021 | year == 2022) %>% 
  select(age, sexfreq, weight = wtssnrps)

both <- bind_rows(one, two)

aaa2 <- both %>% 
  mutate(never = case_when(sexfreq == 2 | sexfreq == 3 | sexfreq == 4 | sexfreq == 5 | sexfreq == 6 ~ 1, 
                           sexfreq == 0 | sexfreq == 1 ~ 0)) %>% 
  group_by(age) %>% 
  mean_ci(never, wt = weight, ci = .84) %>% 
  na.omit() %>% 
  mutate(year = "2016 to 2022")


graph <- bind_rows(aaa1, aaa2)

graph %>% 
  filter(age <= 65) %>% 
  ggplot(., aes(x = age, y = mean, color = year, group = year)) +
  geom_point(stroke = .5, shape = 21, alpha = .5) +
  geom_labelsmooth(aes(label = year),  method = "loess", formula = y ~ x, family = "font", linewidth = 1, text_smoothing = 30, size = 4, linewidth = 1, boxlinewidth = 0.3) +
  scale_color_calc() + 
  theme_rb() +
  y_pct() + 
  labs(x = "Age", y = "", title = "Share Having Sex At Least Once a Month Over the Last Year", caption = "@ryanburge\nData: General Social Survey, 1989-2022")
save("gss_age_sex_freq.png")


yyy1 <- gss %>% 
  gss_reltrad6(reltrad) %>% 
  filter(year <= 2018) %>% 
  group_by(year, reltrad) %>% 
  mutate(never = case_when(sexfreq == 2 | sexfreq == 3 | sexfreq == 4 | sexfreq == 5 | sexfreq == 6 ~ 1, 
                           sexfreq == 0 | sexfreq == 1 ~ 0)) %>% 
  mean_ci(never, wt = wtssall, ci = .84) %>% 
  na.omit()

yyy2 <- gss %>% 
  gss_reltrad6(reltrad) %>% 
  filter(year >= 2021) %>% 
  group_by(year, reltrad) %>% 
  mutate(never = case_when(sexfreq == 2 | sexfreq == 3 | sexfreq == 4 | sexfreq == 5 | sexfreq == 6 ~ 1, 
                           sexfreq == 0 | sexfreq == 1 ~ 0)) %>% 
  mean_ci(never, wt = wtssnrps, ci = .84) %>% 
  na.omit()

graph <- bind_rows(yyy1, yyy2)

graph %>% 
  mutate(lab = round(mean, 2)) %>% 
  filter(year == 1989 | year == 2008 | year == 2018 | year == 2021 | year == 2022) %>% 
  ggplot(., aes(x = factor(year), y = mean, fill = factor(year))) +
  geom_col(color = "black", position = "dodge") +
  error_bar() +
  facet_wrap(~ reltrad) +
  y_pct() + 
  scale_fill_manual(values = c(moma.colors("OKeeffe", 5))) +
  lab_bar(top = FALSE, type = lab, pos = .065, sz = 6) + 
  geom_text(aes(y = .065, label = ifelse(year == 2021 | year == 2022, paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 6, family = "font", color = "white") +   
  theme_rb() +
  labs(x = "Year", y = "", title = "Share Having Sex At Least Once a Month Over the Last Year", caption = "@ryanburge\nData: GSS 1989-2022")
save("monthly_sex22.png")


## 74% in 1989
## 72% in 2008
## 67% in 2018
## 63% in 2021
## 65% in 2022


aaa1 <- gss %>% 
  filter(year == 1989 | year == 1990 | year == 1991 | year == 1993) %>% 
  filter(age >= 25 & age <= 50) %>% 
  gss_reltrad6(reltrad) %>% 
  group_by(reltrad) %>% 
  mutate(never = case_when(sexfreq == 2 | sexfreq == 3 | sexfreq == 4 | sexfreq == 5 | sexfreq == 6 ~ 1, 
                           sexfreq == 0 | sexfreq == 1 ~ 0)) %>% 
  mean_ci(never, wt = wtssall, ci = .84) %>% 
  na.omit() %>% 
  mutate(year = "1989-\n1993")


one <- gss %>% 
  filter(year == 2016 | year == 2018) %>% 
  select(age, sexfreq, weight = wtssall, reltrad)

two <- gss %>% 
  filter(year == 2021 | year == 2022) %>% 
  select(age, sexfreq, weight = wtssnrps, reltrad)

both <- bind_rows(one, two)


aaa2 <- both %>% 
  filter(age >= 25 & age <= 50) %>% 
  gss_reltrad6(reltrad) %>% 
  group_by(reltrad) %>% 
  mutate(never = case_when(sexfreq == 2 | sexfreq == 3 | sexfreq == 4 | sexfreq == 5 | sexfreq == 6 ~ 1, 
                           sexfreq == 0 | sexfreq == 1 ~ 0)) %>% 
  mean_ci(never, wt = weight, ci = .84) %>% 
  na.omit() %>% 
  mutate(year = "2016-\n2022")

graph <- bind_rows(aaa1, aaa2)

graph %>% 
  mutate(lab = round(mean, 2)) %>% 
  ggplot(., aes(x = year, y = mean, fill= year)) +
  geom_col(color = "black") +
  facet_wrap(~ reltrad) +
  theme_rb() + 
  scale_fill_d3() +
  error_bar() + 
  y_pct() + 
  lab_bar(top = FALSE, type = lab, pos = .085, sz = 7) + 
  geom_text(aes(y = .085, label = ifelse(year == "1989-\n1993", paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 7, family = "font", color = "white") +   
  theme(plot.title = element_text(size = 13)) +
  labs(x = "Years", y = "", title = "Share Having Sex At Least Once a Month Over the Last Year", subtitle = "25-50 Year Olds", caption = "@ryanburge\nData: GSS 1989-2022")
save("sex_freq_reltrad.png", wd = 5)


aaa1 <- gss %>% 
  filter(year == 1989 | year == 1990 | year == 1991 | year == 1993) %>% 
  filter(age >= 25 & age <= 50) %>% 
  gss_attend(attend) %>% 
  group_by(att) %>% 
  mutate(never = case_when(sexfreq == 2 | sexfreq == 3 | sexfreq == 4 | sexfreq == 5 | sexfreq == 6 ~ 1, 
                           sexfreq == 0 | sexfreq == 1 ~ 0)) %>% 
  mean_ci(never, wt = wtssall, ci = .84) %>% 
  na.omit() %>% 
  mutate(year = "1989-\n1993")


one <- gss %>% 
  filter(year == 2016 | year == 2018) %>% 
  select(age, sexfreq, weight = wtssall, attend)

two <- gss %>% 
  filter(year == 2021 | year == 2022) %>% 
  select(age, sexfreq, weight = wtssnrps, attend)

both <- bind_rows(one, two)


aaa2 <- both %>% 
  filter(age >= 25 & age <= 50) %>% 
  gss_attend(attend) %>% 
  group_by(att) %>% 
  mutate(never = case_when(sexfreq == 2 | sexfreq == 3 | sexfreq == 4 | sexfreq == 5 | sexfreq == 6 ~ 1, 
                           sexfreq == 0 | sexfreq == 1 ~ 0)) %>% 
  mean_ci(never, wt = weight, ci = .84) %>% 
  na.omit() %>% 
  mutate(year = "2016-\n2022")

graph <- bind_rows(aaa1, aaa2)

graph %>% 
  mutate(lab = round(mean, 2)) %>% 
  ggplot(., aes(x = year, y = mean, fill= year)) +
  geom_col(color = "black") +
  facet_wrap(~ att) +
  theme_rb() + 
  scale_fill_calc() +
  error_bar() + 
  y_pct() + 
  lab_bar(top = FALSE, type = lab, pos = .085, sz = 7) + 
  geom_text(aes(y = .085, label = ifelse(year == "1989-\n1993", paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 7, family = "font", color = "white") +   
  theme(plot.title = element_text(size = 13)) +
  labs(x = "Years", y = "", title = "Share Having Sex At Least Once a Month Over the Last Year", subtitle = "25-50 Year Olds", caption = "@ryanburge\nData: GSS 1989-2022")
save("sex_freq_att.png", wd = 5)



aaa1 <- gss %>% 
  mutate(mar = frcode(marital == 1 ~ "Married", 
                      marital == 2 | marital == 3 | marital == 4 | marital == 5 ~ "Not Married")) %>% 
  filter(year == 1989 | year == 1990 | year == 1991 | year == 1993) %>% 
  group_by(age) %>% 
  mutate(never = case_when(sexfreq == 2 | sexfreq == 3 | sexfreq == 4 | sexfreq == 5 | sexfreq == 6 ~ 1, 
                           sexfreq == 0 | sexfreq == 1 ~ 0)) %>% 
  group_by(age, mar) %>% 
  mean_ci(never, wt = wtssall, ci = .84) %>% 
  na.omit() %>% 
  mutate(year = "1989 to 1993")


one <- gss %>% 
  filter(year == 2016 | year == 2018) %>% 
  select(age, sexfreq, weight = wtssall, marital)

two <- gss %>% 
  filter(year == 2021 | year == 2022) %>% 
  select(age, sexfreq, weight = wtssnrps, marital)

both <- bind_rows(one, two)

aaa2 <- both %>% 
  mutate(mar = frcode(marital == 1 ~ "Married", 
                      marital == 2 | marital == 3 | marital == 4 | marital == 5 ~ "Not Married")) %>% 
  mutate(never = case_when(sexfreq == 2 | sexfreq == 3 | sexfreq == 4 | sexfreq == 5 | sexfreq == 6 ~ 1, 
                           sexfreq == 0 | sexfreq == 1 ~ 0)) %>% 
  group_by(age, mar) %>% 
  mean_ci(never, wt = weight, ci = .84) %>% 
  na.omit() %>% 
  mutate(year = "2016 to 2022")


graph <- bind_rows(aaa1, aaa2)

graph %>% 
  filter(age <= 65) %>% 
  ggplot(., aes(x = age, y = mean, color = year, group = year)) +
  geom_point(stroke = .5, shape = 21, alpha = .5) +
  geom_smooth(se = FALSE) +
  scale_color_calc() + 
  facet_wrap(~ mar) +
  theme_rb(legend = TRUE) +
  y_pct() + 
  theme(strip.text = element_text(size = 20)) +
  labs(x = "Age", y = "", title = "Share Having Sex At Least Once a Month Over the Last Year", caption = "@ryanburge\nData: General Social Survey, 1989-2022")
save("gss_age_sex_freq_marital.png")