state_choropleth: Create a choropleth map using U.S. state level data

Description

To see the list of allowed state names, see choroplethr::state.regions.

Usage

state_choropleth(
  df,
  geoid.name = "region",
  geoid.type = "auto",
  value.name = "value",
  style = "geographic_bigdc",
  num_colors = 7,
  color.max = NULL,
  color.min = NULL,
  na.color = "grey",
  custom.colors = NULL,
  nbreaks = 5,
  zoom = NULL,
  projection = "albers",
  border_color = "grey15",
  border_thickness = 0.2,
  background_color = "white",
  gridlines = FALSE,
  latlon_ticks = FALSE,
  whitespace = TRUE,
  label = NULL,
  label_text_size = 2.25,
  label_text_color = "black",
  label_box_color = "white",
  ggrepel_options = list(force = 0.01, box.padding = 0.15, label.padding = 0.15,
    max.overlaps = Inf),
  legend = NULL,
  legend_position = "right",
  title = NULL,
  return = "plot"
)

Arguments

df: A dataframe containing U.S. state level data
geoid.name: The variable that identifies each state
geoid.type: How the variable given by geoid.name specifies each state (full name, abbreviation, etc). The allowed geoid.type are given in choroplethr::state.regions. If "auto", the function will try to automatically determine geoid.type.
value.name: The name of the variable you wish to plot.
style: Either "geographic" for a literal map of US states, "geographic_bigdc" to make Washington DC more visible, or "hexgrid" for a stylized hexagonal tile map. Note: projection = 'mercator' is suggested when using the hexgrid map.
num_colors: The number of colors you want in your graph when plotting continuous data. If num_colors > 1, the variable in question will be divided into quantiles and converted into a factor with that many levels. If num_colors = 1, a continuous color gradient will be used; if num_colors = 0, a diverging color gradient will be used (useful for visualizing negative and positive numbers). Use color.max and color.min to control the range of colors displayed. num_colors is ignored when plotting categorical data.
color.max: The color of the highest value in your data. Ignored if the plotted variable is categorical.
color.min: The color of the lowest value in your data. Ignored if the plotted variable is categorical.
na.color: The color you want to assign for regions with missing data
custom.colors: A vector of valid R color terms of the to use for the map when plotting factor variables. The length of this vector must match the number of levels in your factor variable, or num_colors for a continuous variable that will be discretized by the function, and the order should match the order of the levels of in your factor variable.
nbreaks: The number of breaks you wish to show in the legend when using a continuous color scale. Ignored if num_colors > 1.
zoom: An optional vector of states to zoom in on, written in the same manner as geoid.name.
projection: One of the following: "cartesian", "mercator", "robinson", or "albers", for equirectangular, Mercator, Robinson, and Albers Equal Area projections, respectively. When using the Mercator projection for world maps, setting limits_lon is recommended to prevent exaggeration of the size of Antarctica.
border_color: The color of the borders on your map
border_thickness: The thickness of the borders on your map
background_color: The background color of your map
gridlines: Should gridlines appear on your map?
latlon_ticks: Should lat/lon tick marks appear on the edge of your map?
whitespace: Add some blank space to the sides of your map? For some projections, this must be set to FALSE in order for lat/lon ticks and display correctly.
label: The name of variable you wish to use to label your map; must be one of the variables that appears in the spatial dataframe just prior plotting (use return = 'sf' to see this dataframe), and in general, can be any of the allowed geoid.type. This function uses ggplot2::geom_label_repel to create the labels and ensure that they do not overlap.
label_text_size: The size of the text that will appear in each label
label_text_color: The color of the text that will appear in each label
label_box_color: The color of the box around each label
ggrepel_options: A list containing additional arguments to be passed to geom_label_repel (see ?ggplot2::geom_label_repel)
legend: A title for your legend; if NULL, value.name will be used.
legend_position: The position of your legend relative to the rest of the map; can be "top", "bottom", "left", or "right".
title: A title for your plot; if NULL, no title will be added.
return: If "plot", the function will return the requested map as a ggplot object. If "sf", the function will return the spatial dataframe used to draw the map (useful if you wish to customize the map yourself).

Examples

Run this code

# Plot continuous state level data:
data(df_state_demographics)
state_choropleth(df = df_state_demographics,
                 geoid.name = 'region',
                 geoid.type = 'name.lower',
                 value.name = 'population',
                 title  = "U.S. State Population",
                 legend = "Population")

# Plot categorical data with custom colors:
data("df_president")
state_choropleth(df = df_president,
                 geoid.name = 'region',
                 geoid.type = 'name.lower',
                 value.name = 'value',
                 title  = "2012 US Presidential Election Results",
                 legend = "Candidate",
                 custom.colors = c('blue4', 'red3'),
                 border_color = 'lightgrey')

# Label states and pass additional arguments to ggrepel
state_choropleth(df = df_president,
                 geoid.name = 'region',
                 geoid.type = 'name.lower',
                 value.name = 'value',
                 title  = "2012 US Presidential Election Results",
                 legend = "Candidate",
                 custom.colors = c('blue4', 'red3'),
                 border_color = 'lightgrey',
                 label = 'state.abb',
                 label_text_size = 4,
                 ggrepel_options = list(label.r = 0, force = 0.02))
                 
# Use a styled hexagonal tile map instead of actual state shapes:
state_choropleth(df = df_president,
                 style = 'hexgrid',
                 projection = 'mercator',
                 geoid.name = 'region',
                 geoid.type = 'name.lower',
                 value.name = 'value',
                 title  = "2012 US Presidential Election Results",
                 legend = "Candidate",
                 custom.colors = c('blue4', 'red3'),
                 border_color = 'lightgrey',
                 label = 'state.abb',
                 label_text_size = 3)

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