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columbus.R
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columbus.R
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#' @name columbus
#' @aliases columbus col.gal.nb coords polys bbs
#' @title Columbus OH spatial analysis data set
#'
#' @description The \code{columbus} data frame has 49 rows and 22 columns. Unit of analysis: 49 neighbourhoods in Columbus, OH, 1980 data. In addition the data set includes a \code{polylist} object \code{polys} with the boundaries of the neighbourhoods, a matrix of polygon centroids \code{coords}, and \code{col.gal.nb}, the neighbours list from an original GAL-format file. The matrix \code{bbs} is DEPRECATED, but retained for other packages using this data set.
#'
#' @format This data frame contains the following columns:
#' \itemize{
#' \item{AREA} {computed by ArcView}
#' \item{PERIMETER} {computed by ArcView}
#' \item{COLUMBUS_} {internal polygon ID (ignore)}
#' \item{COLUMBUS_I} {another internal polygon ID (ignore)}
#' \item{POLYID} {yet another polygon ID}
#' \item{NEIG} {neighborhood id value (1-49);
#' conforms to id value used in Spatial Econometrics book.}
#' \item{HOVAL} {housing value (in 1,000 USD)}
#' \item{INC} {household income (in 1,000 USD)}
#' \item{CRIME} {residential burglaries and vehicle thefts per thousand
#' households in the neighborhood}
#' \item{OPEN} {open space in neighborhood}
#' \item{PLUMB} {percentage housing units without plumbing}
#' \item{DISCBD} {distance to CBD}
#' \item{X} {x coordinate (in arbitrary digitizing units, not polygon coordinates)}
#' \item{Y} {y coordinate (in arbitrary digitizing units, not polygon coordinates)}
#' \item{NSA} {north-south dummy (North=1)}
#' \item{NSB} {north-south dummy (North=1)}
#' \item{EW} {east-west dummy (East=1)}
#' \item{CP} {core-periphery dummy (Core=1)}
#' \item{THOUS} {constant=1,000}
#' \item{NEIGNO} {NEIG+1,000, alternative neighborhood id value}
#' }
#' @details The row names of \code{columbus} and the \code{region.id} attribute of \code{polys} are set to \code{columbus$NEIGNO}.
#' @source Anselin, Luc. 1988. Spatial econometrics: methods and models. Dordrecht: Kluwer Academic, Table 12.1 p. 189.
#' @note All source data files prepared by Luc Anselin, Spatial Analysis Laboratory, Department of Agricultural and Consumer Economics, University of Illinois, Urbana-Champaign, http://sal.agecon.uiuc.edu/datasets/columbus.zip.
#' @docType data
#' @keywords datasets sp spdep
#'
#' @examples
#' if (requireNamespace("sf", quietly = TRUE)) {
#' library(sp)
#' columbus <- sf::st_read(system.file("shapes/columbus.shp", package="spData")[1])
#' columbus <- as(columbus, "Spatial")
#' plot(columbus)
#' }
#'
#' if (requireNamespace("spdep", quietly = TRUE)) {
#' library(spdep)
#' col.gal.nb <- read.gal(system.file("weights/columbus.gal", package="spData")[1])
#' }
"columbus"