“fReE sTuFf fRoM tHe gOvErnMeNt dOeS nOt pLaY wElL iN tHe mIdWeSt.”

1-dont-bring-boilerplate-centrist-talking-points-to-a-data-fight-claire.R

library(tidyverse)
library(stevemisc)

GSS <- readRDS("~/Dropbox/data/gss/GSS_spss-2018/gss7218.rds")

GSS %>%
  mutate(regioncondensed = NA,
         regioncondensed = ifelse(region == 8 | region == 9, "West", regioncondensed),
         regioncondensed = ifelse(region == 3 | region == 4, "Midwest", regioncondensed),
         regioncondensed = ifelse(region == 5 | region == 6 | region == 7, "South", regioncondensed),
         regioncondensed = ifelse(region == 1 | region == 2, "Northeast", regioncondensed)) %>%
  select(year, regioncondensed, natheal, natsoc) %>%
  mutate(nathealtm = carr(natheal, "1:2=0; 3=1"),
         natsoctm = carr(natsoc, "1:2=0; 3=1"),
         nathealtl = carr(natheal, "2:3=0; 1=1"),
         natsoctl = carr(natsoc, "2:3=0; 1=1"),) -> McCaskill

McCaskill %>%  
  group_by(regioncondensed, year) %>%
  summarize(perchealtm = mean(nathealtm, na.rm=T),
            percsoctm = mean(natsoctm, na.rm=T)) %>% 
  group_by(regioncondensed, year) %>%
  gather(Category, value, 3:4) %>%
  mutate(Category = ifelse(Category == "perchealtm",
                           "Spending Too Much on Health Care",
                           "Spending Too Much on Social Security")) %>%
  ggplot(.,aes(year, value, color=Category, linetype=Category)) +
  theme_steve_web() +
  geom_line(size=1.1) + facet_wrap(~regioncondensed) +
  scale_y_continuous(labels=scales::percent) +
  scale_x_continuous(breaks = seq(1970, 2020, by=4)) +
  scale_color_brewer(palette="Set1") +
  labs(x = "Year",
       y = "Percent of Respondents in a Given Year Who Think the U.S. is Spending Too Much on this Public Good",
       title = "Only About Five Percent of Americans, by Region, Think the U.S. Spends Too Much on Health Care and Social Security",
       subtitle = "Unsurprisingly, the spikes on the health care item in 2010 are entirely Obamacare freakouts that propelled the Tea Party to power.",
       caption = "Data: General Social Survey, 1972-2018")


  
McCaskill %>%  
  group_by(regioncondensed, year) %>%
  summarize(perchealtl = mean(nathealtl, na.rm=T),
            percsoctl = mean(natsoctl, na.rm=T)) %>% 
  group_by(regioncondensed, year) %>%
  gather(Category, value, 3:4) %>%
  mutate(Category = ifelse(Category == "perchealtl",
                           "Spending Too Little on Health Care",
                           "Spending Too Little on Social Security")) %>%
  ggplot(.,aes(year, value, color=Category, linetype=Category)) +
  theme_steve_web() +
  geom_line(size=1.1) + facet_wrap(~regioncondensed) +
  scale_y_continuous(labels=scales::percent) +
  scale_x_continuous(breaks = seq(1970, 2020, by=4)) +
  scale_color_brewer(palette="Set1") +
  labs(x = "Year",
       y = "Percent of Respondents in a Given Year Who Think the U.S. is Spending Too Little on this Public Good",
       title = "About 60-70% of Americans, by Region, Think the U.S. Spends Too Little on Health Care and Social Security",
       subtitle = "Unsurprisingly, the dips on the health care item in 2010 are entirely Obamacare freakouts that propelled the Tea Party to power.",
       caption = "Data: General Social Survey, 1972-2018")