columbus | R Documentation |
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.
data(columbus)
This data frame contains the following columns:
computed by ArcView
computed by ArcView
internal polygon ID (ignore)
another internal polygon ID (ignore)
yet another polygon ID
neighborhood id value (1-49); conforms to id value used in Spatial Econometrics book.
housing value (in $1,000)
household income (in $1,000)
residential burglaries and vehicle thefts per thousand households in the neighborhood
open space in neighborhood
percentage housing units without plumbing
distance to CBD
x coordinate (in arbitrary digitizing units, not polygon coordinates)
y coordinate (in arbitrary digitizing units, not polygon coordinates)
north-south dummy (North=1)
north-south dummy (North=1)
east-west dummy (East=1)
core-periphery dummy (Core=1)
constant=1,000
NEIG+1,000, alternative neighborhood id value
The row names of columbus
and the region.id
attribute of
polys
are set to columbus$NEIGNO
.
All source data files prepared by Luc Anselin, Spatial Analysis Laboratory, Department of Agricultural and Consumer Economics, University of Illinois, Urbana-Champaign.
Anselin, Luc. 1988. Spatial econometrics: methods and models. Dordrecht: Kluwer Academic, Table 12.1 p. 189.
#library(maptools)
#columbus <- readShapePoly(system.file("etc/shapes/columbus.shp",
# package="spdep")[1])
#col.gal.nb <- read.gal(system.file("etc/weights/columbus.gal",
# package="spdep")[1])
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