Crime, housing and income data for 49 neighborhoods in Columbus, OH, 1980. Textbook example.
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Observations = 49100
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Variables = 20
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Date Range = 1980-01-01 to 1980-01-02
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.