The 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 polylist
object polys
with the boundaries of the neighbourhoods, a matrix of polygon centroids coords
, and col.gal.nb
, the neighbours list from an original GAL-format file. The matrix bbs
is DEPRECATED, but retained for other packages using this data set.
columbus
This data frame contains the following columns:
AREA computed by ArcView
PERIMETER computed by ArcView
COLUMBUS_ internal polygon ID (ignore)
COLUMBUS_I another internal polygon ID (ignore)
POLYID yet another polygon ID
NEIG neighborhood id value (1-49); conforms to id value used in Spatial Econometrics book.
HOVAL housing value (in 1,000 USD)
INC household income (in 1,000 USD)
CRIME residential burglaries and vehicle thefts per thousand households in the neighborhood
OPEN open space in neighborhood
PLUMB percentage housing units without plumbing
DISCBD distance to CBD
X x coordinate (in arbitrary digitizing units, not polygon coordinates)
Y y coordinate (in arbitrary digitizing units, not polygon coordinates)
NSA north-south dummy (North=1)
NSB north-south dummy (North=1)
EW east-west dummy (East=1)
CP core-periphery dummy (Core=1)
THOUS constant=1,000
NEIGNO NEIG+1,000, alternative neighborhood id value
Anselin, Luc. 1988. Spatial econometrics: methods and models. Dordrecht: Kluwer Academic, Table 12.1 p. 189.
The row names of columbus
and the region.id
attribute of polys
are set to columbus$NEIGNO
.
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.
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)
}
#> Reading layer `columbus' from data source
#> `/home/runner/work/_temp/Library/spData/shapes/columbus.shp'
#> using driver `ESRI Shapefile'
#> Simple feature collection with 49 features and 20 fields
#> Geometry type: POLYGON
#> Dimension: XY
#> Bounding box: xmin: 5.874907 ymin: 10.78863 xmax: 11.28742 ymax: 14.74245
#> CRS: NA
if (requireNamespace("spdep", quietly = TRUE)) {
library(spdep)
col.gal.nb <- read.gal(system.file("weights/columbus.gal", package="spData")[1])
}