Artists in the US

Author

Jo Hardin

Published

September 27, 2022

The Data

The data this week comes from arts.gov by way of Data is Plural.

artists <- read_csv("artists.csv")
architects <- artists %>%
  filter(type == "Architects")

top_st_arch <- architects %>%
  group_by(state) %>%
  summarize(state_n = sum(artists_n, na.rm = TRUE)) %>%
  slice_max(state_n, n = 20) 

architects %>%
  right_join(top_st_arch, by = "state") %>%
  ungroup() %>%
  ggplot(aes(y = factor(race,   
                  levels = c("Other", "White", "Asian", "Hispanic", "African-American")), 
             x = artists_n)) + 
  ggdist::geom_dots(aes(fill = factor(race,   
                  levels = c("African-American", "Hispanic",  "Asian", "White","Other")),
                  color = factor(race,   
                  levels = c("African-American", "Hispanic",  "Asian", "White","Other"))),
                  size = .05) + 
  scale_color_manual(values = ggthemes::colorblind_pal()(8)[c(1,2,3,4,8)]) +
  scale_fill_manual(values = ggthemes::colorblind_pal()(8)[c(1,2,3,4,8)]) +
  #geofacet::facet_geo(~ state, grid = "us_state_grid1") +
  scale_x_log10() +
  theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
        axis.text.y = element_text(size = 8)) +
  labs(title = "Number of architects, broken down by race and state",
       subtitle = "for the 20 states with the most architects",
       x = "number of architects",
       y = "",
       caption = "Tidy Tuesday Plot: @hardin47 | Data: Artists in the US via arts.gov",
       fill = "race",
       color = "race") +
  facet_wrap(~state)

Twenty different plots, one for each fo the 20 states with the most architects. On each plot, the x-axis is the number of architects, the y-axis is the race, there are five dots on each plot (for each of African-American, Hispanic, Asian, White and Other). — For each of the 20 states with the most architects, the plot gives the number of architects, broken down by race.