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## ----include = FALSE----------------------------------------------------------
# Preview vignette with: devtools::build_rmd("vignettes/biscale.Rmd")
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----setup--------------------------------------------------------------------
library(palettes)
library(ggplot2)
library(patchwork)
library(biscale)
## -----------------------------------------------------------------------------
named_colour_vector <- pal_colour(c(
"1-1" = "#d3d3d3", # low x, low y
"2-1" = "#9e3547", # high x, low y
"1-2" = "#4279b0", # low x, high y
"2-2" = "#311e3b" # high x, high y
))
named_colour_vector
names(named_colour_vector)
## -----------------------------------------------------------------------------
unnamed_colour_vector <- pal_colour(
c("#d3d3d3", "#9e3547", "#4279b0", "#311e3b")
)
names(unnamed_colour_vector)
names(unnamed_colour_vector) <- c("1-1", "2-1", "1-2", "2-2")
names(unnamed_colour_vector)
## -----------------------------------------------------------------------------
bi_pal(named_colour_vector, dim = 2)
## -----------------------------------------------------------------------------
race_income <- bi_class(
stl_race_income,
x = pctWhite,
y = medInc,
dim = 3,
style = "quantile",
keep_factors = TRUE
)
## -----------------------------------------------------------------------------
named_colour_vector <- pal_colour(c(
"1-1" = "#d3d3d3", # low x, low y
"2-1" = "#ba8890",
"3-1" = "#9e3547", # high x, low y
"1-2" = "#8aa6c2",
"2-2" = "#7a6b84", # medium x, medium y
"3-2" = "#682a41",
"1-3" = "#4279b0", # low x, high y
"2-3" = "#3a4e78",
"3-3" = "#311e3b" # high x, high y
))
## -----------------------------------------------------------------------------
# Draw map with a bivariate fill scale
race_income_plot <- ggplot(race_income, aes(fill = bi_class)) +
geom_sf(color = "white", size = 0.1, show.legend = FALSE) +
bi_scale_fill(pal = named_colour_vector, dim = 3) +
labs(
title = "Race and Income in St. Louis, MO",
caption = "Breaks for percent white are 14.0% and 62.0% (range is 0-96.7%).
Breaks for median income are $26,200 and $43,900
(range is $10,500-$74,400)."
) +
bi_theme()
# Draw the bivariate legend
bivariate_legend <- bi_legend(
pal = named_colour_vector,
dim = 3,
xlab = "Higher % White ",
ylab = "Higher Income ",
size = 7
)
# Combine the map and bivariate legend
race_income_plot +
inset_element(
bivariate_legend,
left = 0,
bottom = 0.8,
right = 0.5,
top = 1,
align_to = "plot"
)
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