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.
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
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.
Anselin, Luc. 1988. Spatial econometrics: methods and models. Dordrecht: Kluwer Academic, Table 12.1 p. 189.
if (requireNamespace("sf", quietly = TRUE)) {
columbus <- sf::st_read(system.file("shapes/columbus.gpkg", package="spData")[1])
plot(sf::st_geometry(columbus))
}
if (requireNamespace("spdep", quietly = TRUE)) {
library(spdep)
col.gal.nb <- read.gal(system.file("weights/columbus.gal", package="spData")[1])
}
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