The Data

The data on registered Nurses comes from Data.World.

nurses <- read_csv("nurses.csv") %>%
  janitor::clean_names() %>%
  mutate(st = state.abb[match(state, state.name)]) %>%
  mutate(st = ifelse(state == "District of Columbia", "DC", st)) %>%
  drop_na(st) %>%
  bi_class(x=hourly_wage_median, y=total_employed_rn, style="quantile",dim=3)

Wrangling

nurses %>%
  filter(year == 2004) %>%
  ggplot() + 
  geom_histogram(aes(x = annual_salary_median))

nurses %>%
  ggplot() + 
  geom_histogram(aes(x = annual_salary_median)) +
  facet_wrap(~year)

Data Viz

I’m going to try to make a US plot that is colored by two variables and changes over time. The main plot is due entirely to @leeolney3 at https://gist.github.com/leeolney3/7ff6c982d7928a554ad70fc8a367cea8 and https://twitter.com/leeolney3/status/1445196349889290241?s=20.

I can’t get the map and the legend to show up as part of the same gif, so the legend is plotted in the chunk below the US map. The coloring isn’t as descriptive as I’d like because number of nurses going up is probably a proxy for population numbers going up. And hourly wage is likely due to inflation.

nurses %>%
  #filter(year == "2020") %>%
  mutate(x = 1) %>% 
  mutate(label_y = .5) %>%  
  mutate(label_x = 1) %>% 
  ggplot() +
  geom_bar(mapping=aes(x=x, fill=bi_class, frame = year), width=.4)  +
    facet_geo(~ st, grid="us_state_grid1") +
    labs(title=paste(), subtitle=, caption="") +
    geom_text(aes(x=label_x, y=label_y, label=st, color=bi_class),
              size=3, show.legend=F, family="sans") +
  bi_scale_fill(pal="DkCyan",dim=3, guide="none") +
  scale_color_manual(values=c("grey10","grey10","white","white","white","white","white","white","white")) +
  theme_void(base_size=10, base_family = "sans") + 
  transition_states(year) +
  theme(strip.text.x = element_blank(),
        plot.margin = unit(c(.5,4,.5,2), "cm"),
        plot.title=element_text(size=14, face="bold", color="#012a4a"),
        plot.subtitle=ggtext::element_markdown(size=8, color="#011c31", margin=margin(t=5,b=18)),
        legend.title=element_text(size=9),
        plot.caption = ggtext::element_markdown(size=5.6, color="#011c31",margin=margin(t=30), lineheight=1.5, hjust=0)) + 
  guides(fill = guide_colorbar(title="Count",
                              title.position = "top", 
                              barwidth = unit(.5, "lines"), 
                              barheight = unit(10, "lines"))) +
  labs(title = "Number of nurses and hourly wage over time",
       subtitle = "{closest_state}")
The US map shows that over time, hourly wage has gone up and number of nurses in the state has also gone up.

Heatmap colored by two variables: number of nurses in the state and hourly wage. 

#p1_gif <- animate(p1, renderer = magick_renderer())
#p1_mgif <- image_read(p1_gif)


# legend                              
bi_legend(pal = "DkCyan", 
            dim = 3,
            ylab = "Total employed",
            xlab = "Median hourly wage",
            size = 2.5) + 
  theme(panel.border = element_blank(),
        axis.text = element_blank(),
        axis.title.x = element_text(size = 6, family="sans",
                                    color = "#011c31", margin=margin(t=-5)),
        axis.title.y = element_text(size = 6, family="sans",
                                    color = "#011c31", margin=margin(r=-5)),
        legend.text = element_text(size = 6),
        plot.background = element_blank(),
        legend.text.align = 0)
The US map shows that over time, hourly wage has gone up and number of nurses in the state has also gone up.

Heatmap colored by two variables: number of nurses in the state and hourly wage.

This chunk doesn’t work.

new_gif <- image_append(c(p1_gif[1], p2))
for(i in 2:23){
  combined <- image_append(c(p1_gif[i], p2))
  new_gif <- c(new_gif, combined)
}
praise()
## [1] "You are unreal!"