#' Create a state-level choropleth
#' @export
#' @importFrom dplyr left_join
#' @include usa.R
StateChoropleth = R6Class("StateChoropleth",
inherit = USAChoropleth,
public = list(
show_labels = TRUE,
# initialize with us state map
initialize = function(user.df)
{
if (!requireNamespace("choroplethrMaps", quietly = TRUE)) {
stop("Package choroplethrMaps is needed for this function to work. Please install it.", call. = FALSE)
}
data(state.map, package="choroplethrMaps", envir=environment())
state.map$state = state.map$region
super$initialize(state.map, user.df)
if (private$has_invalid_regions)
{
warning("Please see ?state.regions for a list of mappable regions")
}
},
render = function()
{
choropleth = super$render()
# by default, add labels for the lower 48 states
if (self$show_labels) {
df_state_labels = data.frame(long = state.center$x, lat = state.center$y, name=tolower(state.name), label = state.abb)
df_state_labels = df_state_labels[!df_state_labels$name %in% c("alaska", "hawaii"), ]
df_state_labels = df_state_labels[df_state_labels$name %in% private$zoom, ]
choropleth = choropleth + geom_text(data = df_state_labels, aes(long, lat, label = label, group = NULL), color = 'black')
}
choropleth
}
)
)
#' Create a choropleth of US States with sensible defaults.
#'
#' The map used is state.map in the package choroplethrMaps. See state.regions in
#' the choroplethrMaps package for a data.frame that can help you coerce your regions
#' into the required format.
#'
#' @param df A data.frame with a column named "region" and a column named "value". Elements in
#' the "region" column must exactly match how regions are named in the "region" column in state.map.
#' @param title An optional title for the map.
#' @param legend An optional name for the legend.
#' @param buckets The number of equally sized buckets to places the values in. A value of 1
#' will use a continuous scale, and a value in [2, 9] will use that many buckets.
#' @param zoom An optional vector of states to zoom in on. Elements of this vector must exactly
#' match the names of states as they appear in the "region" column of ?state.regions.
#'
#' @examples
#' # demonstrate default parameters - visualization using 7 equally sized buckets
#' data(df_pop_state)
#' state_choropleth(df_pop_state, title="US 2012 State Population Estimates", legend="Population")
#'
#' # demonstrate continuous scale and zoom
#' data(df_pop_state)
#' state_choropleth(df_pop_state,
#' title="US 2012 State Population Estimates",
#' legend="Population",
#' buckets=1,
#' zoom=c("california", "oregon", "washington"))
#'
#' # demonstrate how choroplethr handles character and factor values
#' # demonstrate user creating their own discretization of the input
#' data(df_pop_state)
#' df_pop_state$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?")
#'
#' @export
#' @importFrom Hmisc cut2
#' @importFrom stringr str_extract_all
#' @importFrom ggplot2 ggplot aes geom_polygon scale_fill_brewer ggtitle theme theme_grey element_blank geom_text
#' @importFrom ggplot2 scale_fill_continuous scale_colour_brewer
#' @importFrom scales comma
#' @importFrom grid unit
state_choropleth = function(df, title="", legend="", buckets=7, zoom=NULL)
{
c = StateChoropleth$new(df)
c$title = title
c$legend = legend
c$set_buckets(buckets)
c$set_zoom(zoom)
c$render()
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.