R/baltimore.R

In spData: Datasets for Spatial Analysis

#' @name baltimore
#' @aliases baltimore
#' @title House sales prices, Baltimore, MD 1978
#'
#' @description House sales price and characteristics for a spatial hedonic regression, Baltimore, MD 1978. X,Y on Maryland grid, projection type unknown.
#' 
#' @format A data frame with 211 observations on the following 17 variables.
#' \itemize{
#'         \item{STATION} {a numeric vector}
#'         \item{PRICE} {a numeric vector}
#'         \item{NROOM} {a numeric vector}
#'         \item{DWELL} {a numeric vector}
#'         \item{NBATH} {a numeric vector}
#'         \item{PATIO} {a numeric vector}
#'         \item{FIREPL} {a numeric vector}
#'         \item{AC} {a numeric vector}
#'         \item{BMENT} {a numeric vector}
#'         \item{NSTOR} {a numeric vector}
#'         \item{GAR} {a numeric vector}
#'         \item{AGE} {a numeric vector}
#'         \item{CITCOU} {a numeric vector}
#'         \item{LOTSZ} {a numeric vector}
#'         \item{SQFT} {a numeric vector}
#'         \item{X} {a numeric vector}
#'         \item{Y} {a numeric vector}
#' }
#' 
#' @source Prepared by Luc Anselin. Original data made available by Robin Dubin, Weatherhead School of Management, Case Western Research University, Cleveland, OH. http://sal.agecon.uiuc.edu/datasets/baltimore.zip
#' @references Dubin, Robin A. (1992). Spatial autocorrelation and neighborhood quality. Regional Science and Urban Economics 22(3), 433-452.
#' @docType data
#' @keywords datasets sf
#' 
#' @examples 
#' data(baltimore)
#' str(baltimore)
#' 
#' if (requireNamespace("sf", quietly = TRUE)) {
#'   library(sf)
#'   baltimore_sf <- baltimore %>% st_as_sf(., coords = c("X","Y"))
#'   plot(baltimore_sf["PRICE"])
#' }
"baltimore"