county_choropleth: Create a choropleth of USA Counties with sensible defaults.

In trulia/choroplethr: Simplify the Creation of Choropleth Maps in R

Description

The map used is county.map in the choroplethrMaps package. See country.regions in the choroplethrMaps package for an object which can help you coerce your regions into the required format.

Usage

county_choropleth(df, title = "", legend = "", buckets = 7, zoom = NULL)

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 county.map.
title	An optional title for the map.
legend	An optional name for the legend.
buckets	The number of equally sized buckets to places the values in. A value of 1 will use a continuous scale, and a value in [2, 9] will use that many buckets.
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.

Examples

## Not run: 
# demonstrate default parameters - visualization using 7 equally sized buckets
data(df_pop_county)
county_choropleth(df_pop_county, title="US 2012 County Population Estimates", legend="Population")

#' # demonstrate continuous scale and zoom
data(df_pop_county)
county_choropleth(df_pop_county,
                 title="US 2012 County Population Estimates",
                 legend="Population",
                 buckets=1,
                 zoom=c("california", "oregon", "washington"))

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

## End(Not run)

trulia/choroplethr documentation built on June 1, 2019, 1:52 a.m.