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"