choroplethr (version 3.6.3)

state_choropleth: Create a choropleth of US States

Description

The map used is state.map in the package choroplethrMaps. See state.regions in the choroplethrMaps package for a data.frame that can help you coerce your regions into the required format.

Usage

state_choropleth(df, title = "", legend = "", num_colors = 7,
  zoom = NULL, reference_map = FALSE)

Arguments

df

A data.frame with a column named "region" and a column named "value". Elements in the "region" column must exactly match how regions are named in the "region" column in state.map.

title

An optional title for the map.

legend

An optional name for the legend.

num_colors

The number of colors to use on the map. A value of 0 uses a divergent scale (useful for visualizing negative and positive numbers), A value of 1 uses a continuous scale (useful for visualizing outliers), and a value in [2, 9] will use that many quantiles.

zoom

An optional vector of states to zoom in on. Elements of this vector must exactly match the names of states as they appear in the "region" column of ?state.regions.

reference_map

If true, render the choropleth over a reference map from Google Maps.

Examples

Run this code
# NOT RUN {
# default parameters
data(df_pop_state)
state_choropleth(df_pop_state, 
                 title  = "US 2012 State Population Estimates", 
                 legend = "Population")

# choropleth over reference map of continental usa
data(continental_us_states)
state_choropleth(df_pop_state, 
                 title         = "US 2012 State Population Estimates",
                 legend        = "Population",
                 zoom          = continental_us_states, 
                 reference_map = TRUE)

# continuous scale and zoom
data(df_pop_state)
state_choropleth(df_pop_state, 
                 title      = "US 2012 State Population Estimates", 
                 legend     = "Population", 
                 num_colors = 1,
                 zoom       = c("california", "oregon", "washington"))

# demonstrate user creating their own discretization of the input
# demonstrate how choroplethr handles character and factor values
data(df_pop_state)
df_pop_state$str = ""
for (i in 1:nrow(df_pop_state))
{
  if (df_pop_state[i,"value"] < 1000000)
  {
    df_pop_state[i,"str"] = "< 1M"
  } else {
    df_pop_state[i,"str"] = "> 1M"
  }
}
df_pop_state$value = df_pop_state$str
state_choropleth(df_pop_state, title = "Which states have less than 1M people?")

# }

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