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Crime, housing and income data for 49 neighborhoods in Columbus, OH, 1980. Textbook example.

Source

Anselin, Luc (1988). Spatial Econometrics. Boston, Kluwer Academic, Table 12.1, p. 189.Brunsdon, C. and Dykes, J. (2007). Geographically weighted visualization: interactive graphics for scale-varying exploratory analysis. Geographical Information Science Research Conference (GISRUK 07), NUI Maynooth, Ireland, April, 2007.

Variable Description
AREA neighborhood area (computed by ArcView)
PERIMETER neighborhood perimeter (computed by ArcView)
COLUMBUS_ internal polygon ID (generated by ArcView)
COLUMBUS_I internal polygon ID (geneated by ArcView)
POLYID neighborhood ID, used in GeoDa User’s Guide and tutorials
NEIG neighborhood ID, used in Spatial Econometrics examples
HOVAL housing value (in $1,000)
INC household income (in $1,000)
CRIME residential burglaries and vehicle thefts per 1000 households
OPEN open space (area)
PLUMB percent housing units without plumbing
DISCBD distance to CBD
X centroid x coordinate (in arbitrary digitizing units)
Y centroid y coordinate (in arbitrary digitizing units)
NSA north-south indicator variable (North = 1)
NSB other north-south indicator variable (North = 1)
EW east-west indicator variable (East = 1)
CP core-periphery indicator variable (Core = 1)
THOUS constant (= 1000)
NEIGNO another neighborhood ID variable (NEIG + 1000)

Prepared by Luc Anselin. Last updated 2003-06-16. Data provided “as is,” no warranties.