NYC Cencus distributions

#|echo: false
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library(tidyverse)

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library(primer.data)
library(scales)

Attaching package: 'scales'

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    discard

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library(ggplot2)
library(ggbeeswarm)
library(viridis)

Loading required package: viridisLite

Attaching package: 'viridis'

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    viridis_pal

#|echo: false
nyc_tracts<-read_csv(file="./data/nyc_tracts.csv")|>drop_na()

Rows: 2242 Columns: 3
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (2): tract, race
dbl (1): med_income

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

# Create the beeswarm plot with viridis color scale
nyc_tracts|>ggplot(mapping=aes(x = med_income, y = race, color = med_income)) +
  geom_quasirandom(alpha = 0.7, size = 2) +
  scale_x_continuous(labels = scales::dollar_format()) +
  scale_color_viridis(option = "D", direction = 1, name = "Median Household Income") +
  theme_minimal() +
  labs(
    title = "Household income distribution by largest racial/ethnic group",
    subtitle = "Census tracts, New York City",
    x = "Median household income",
    y = "Largest group in Census tract",
    caption = "Data source: 2016-2020 ACS"
  ) +
  theme(
    plot.title = element_text(size = 20, face = "bold"),
    plot.subtitle = element_text(size = 14),
    plot.caption = element_text(size = 10),
    legend.position = "none"
  )

Orientation inferred to be along y-axis; override with
`position_quasirandom(orientation = 'x')`