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Creates a choropleth map from census data with sensible defaults.

Source: R/plotting.R
plot_map.Rd

Creates a choropleth map from census data with sensible defaults.

Usage

plot_map(
  data,
  fill_var,
  title = NULL,
  subtitle = NULL,
  legend_title = NULL,
  palette = "viridis",
  reverse = FALSE,
  direction = NULL,
  na_color = "grey80",
  show_state_boundaries = FALSE,
  state_boundary_color = "black",
  state_boundary_width = 0.3,
  trans = "identity",
  limits = NULL,
  breaks = NULL,
  labels = NULL
)

Arguments

data

An sf object or data frame with geometry attached via attach_geometry

fill_var

The variable to map to fill color (unquoted or string)

title

Optional title for the map

subtitle

Optional subtitle for the map

legend_title

Title for the legend

palette

Color palette. Options include:

  • "viridis" - Perceptually uniform, colorblind-friendly (default)

  • "red_blue" - Diverging red to blue (red = high)

  • "blue_red" - Diverging blue to red (blue = high)

  • "greens" - Sequential green palette

  • "oranges" - Sequential orange palette

  • "reds" - Sequential red palette

  • "blues" - Sequential blue palette

  • "purple_green" - Diverging purple to green

reverse

Logical. Reverse the color palette direction? Default FALSE.

direction

Numeric. Alternative to reverse: use -1 to reverse, 1 for default. If both reverse and direction are specified, direction takes precedence.

na_color

Color for missing values. Default is "grey80"

show_state_boundaries

Logical. Overlay state boundaries?

state_boundary_color

Color for state boundaries. Default is "black"

state_boundary_width

Width of state boundary lines. Default is 0.3

trans

Transformation for the color scale (e.g., "log10", "sqrt"). Default is "identity" (no transformation)

limits

Optional limits for the color scale as c(min, max)

breaks

Optional breaks for the legend

labels

Optional labels for the legend breaks

Value

A ggplot2 object

Examples

if (FALSE) { # \dontrun{
# Load 2011 PCA data
data(census_2011_pca)

# Calculate ST percentage and attach geometry
st_data <- census_2011_pca |>
  dplyr::mutate(st_pct = 100 * st_population / population_total) |>
  attach_geometry(2011)

# Create a basic map
plot_map(st_data, st_pct, title = "ST Population %")

# With red-blue palette and state boundaries
plot_map(st_data, st_pct,
  title = "ST Population % (2011)",
  palette = "red_blue",
  show_state_boundaries = TRUE
)
} # }