#' Create a county-level choropleth that zooms on counties, not states.
#' @export
#' @importFrom dplyr left_join
#' @include usa.R
CountyZoomChoropleth = R6Class("CountyZoomChoropleth",
inherit = Choropleth,
public = list(
# 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(county.map, package="choroplethrMaps", envir=environment())
data(county.regions, package="choroplethrMaps", envir=environment())
super$initialize(county.map, user.df)
# by default, show all counties on the map
private$zoom = unique(county.map$region)
if (private$has_invalid_regions)
{
warning("Please see ?county.regions for a list of mappable regions")
}
},
render = function()
{
if (length(private$zoom) > 1)
{
super$render()
} else {
self$prepare_map()
ggplot(self$choropleth.df, aes(long, lat, group = group)) +
geom_path(color = "black", size = 1) +
self$theme_clean() +
ggtitle(self$title)
}
}
)
)
#' Create a choropleth of USA Counties, with sensible defaults, that zooms on counties.
#'
#' 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. If you zoom in on a single county, only an outline of the
#' county is shown.
#'
#' @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 county.map.
#' @param title An optional title for the map.
#' @param legend An optional name for the legend. Ignored if zooming in on a single county.
#' @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. Ignored if
#' zooming in on a single county.
#' @param zoom An optional vector of counties to zoom in on. Elements of this vector must exactly
#' match the names of counties as they appear in the "region" column of ?county.regions.
#'
#' @examples
#' \dontrun{
#'
#' library(choroplethrMaps)
#' data(county.regions)
#'
#' library(dplyr)
#'
#' # show the population of the 5 counties (boroughs) that make up New York City
#' nyc_county_names=c("kings", "bronx", "new york", "queens", "richmond")
#' nyc_county_fips = county.regions %>%
#' filter(state.name=="new york" & county.name %in% nyc_county_names) %>%
#' select(region)
#' county_zoom_choropleth(df_pop_county,
#' title="Population of Counties in New York City",
#' legend="Population",
#' buckets=1,
#' zoom=nyc_county_fips$region)
#'
#' # zooming in on a single county shows just an outline.
#' county_zoom_choropleth(df_pop_county,
#' title="Zoom of Manhattan",
#' zoom=36061) # manhattan
#'
#' # population of the 9 counties in the san francisco bay area
#' bay_area_county_names = c("alameda", "contra costa", "marin", "napa", "san francisco",
#' "san mateo", "santa clara", "solano", "sonoma")
#' bay_area_county_fips = county.regions %>%
#' filter(state.name=="california" & county.name %in% bay_area_county_names) %>%
#' select(region)
#' county_zoom_choropleth(df_pop_county,
#' title="Population of Counties in the San Francisco Bay Area",
#' legend="Population",
#' buckets=1,
#' zoom=bay_area_county_fips$region)
#' }
#' @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
county_zoom_choropleth = function(df, title="", legend="", buckets=7, zoom=NULL)
{
c = CountyZoomChoropleth$new(df)
c$title = title
c$legend = legend
c$set_buckets(buckets)
c$set_zoom(zoom)
c$render()
}
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