baltimore: House sales prices, Baltimore, MD 1978

Description Usage Format Source References Examples

Description

House sales price and characteristics for a spatial hedonic regression, Baltimore, MD 1978. X,Y on Maryland grid, projection type unknown.

Usage

1

Format

A data frame with 211 observations on the following 17 variables.

Source

Prepared by Luc Anselin. Original data made available by Robin Dubin, Weatherhead School of Management, Case Western Research University, Cleveland, OH. http://sal.agecon.uiuc.edu/datasets/baltimore.zip

References

Dubin, Robin A. (1992). Spatial autocorrelation and neighborhood quality. Regional Science and Urban Economics 22(3), 433-452.

Examples

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data(baltimore)
str(baltimore)

if (requireNamespace("sf", quietly = TRUE)) {
  library(sf)
  baltimore_sf <- baltimore %>% st_as_sf(., coords = c("X","Y"))
  plot(baltimore_sf["PRICE"])
}

Example output

To access larger datasets in this package, install the spDataLarge
package with: `install.packages('spDataLarge')`
'data.frame':	211 obs. of  17 variables:
 $ STATION: int  1 2 3 4 5 6 7 8 9 10 ...
 $ PRICE  : num  47 113 165 104.3 62.5 ...
 $ NROOM  : num  4 7 7 7 7 6 6 8 6 7 ...
 $ DWELL  : num  0 1 1 1 1 1 1 1 1 1 ...
 $ NBATH  : num  1 2.5 2.5 2.5 1.5 2.5 2.5 1.5 1 2.5 ...
 $ PATIO  : num  0 1 1 1 1 1 1 1 1 1 ...
 $ FIREPL : num  0 1 1 1 1 1 1 0 1 1 ...
 $ AC     : num  0 1 0 1 0 0 1 0 1 1 ...
 $ BMENT  : num  2 2 3 2 2 3 3 0 3 3 ...
 $ NSTOR  : num  3 2 2 2 2 3 1 3 2 2 ...
 $ GAR    : num  0 2 2 2 0 1 2 0 0 2 ...
 $ AGE    : num  148 9 23 5 19 20 20 22 22 4 ...
 $ CITCOU : num  0 1 1 1 1 1 1 1 1 1 ...
 $ LOTSZ  : num  5.7 279.5 70.6 174.6 107.8 ...
 $ SQFT   : num  11.2 28.9 30.6 26.1 22 ...
 $ X      : num  907 922 920 923 918 900 918 907 918 897 ...
 $ Y      : num  534 574 581 578 574 577 576 576 562 576 ...

spData documentation built on Oct. 14, 2021, 5:06 p.m.