London house price data set (sf)

A house price data set with 18 hedonic variables for London in 2001.

Usage

data(LondonHP)

Format

A sf object (proj4string set to "+init=epsg:27700 +datum=OSGB36").

The "data" slot is a data frame with 372 observations on the following 21 variables.

X

a numeric vector, X coordinate

Y

a numeric vector, Y coordinate

PURCHASE

a numeric vector, the purchase price of the property

FLOORSZ

a numeric vector, floor area of the property in square metres

TYPEDETCH

a numeric vector, 1 if the property is detached (i.e. it is a stand-alone house), 0 otherwise

TPSEMIDTCH

a numeric vector, 1 if the property is semi detached, 0 otherwise

TYPETRRD

a numeric vector, 1 if the property is in a terrace of similar houses (commonly referred to as a 'row house' in the USA), 0 otherwise

TYPEBNGLW

a numeric vector, if the property is a bungalow (i.e. it has only one floor), 0 otherwise

TYPEFLAT

a numeric vector, if the property is a flat (or 'apartment' in the USA), 0 otherwise

BLDPWW1

a numeric vector, 1 if the property was built prior to 1914, 0 otherwise

BLDPOSTW

a numeric vector, 1 if the property was built between 1940 and 1959, 0 otherwise

BLD60S

a numeric vector, 1 if the property was built between 1960 and 1969, 0 otherwise

BLD70S

a numeric vector, 1 if the property was built between 1970 and 1979, 0 otherwise

BLD80S

a numeric vector, 1 if the property was built between 1980 and 1989, 0 otherwise

BLD90S

a numeric vector, 1 if the property was built between 1990 and 2000, 0 otherwise

BATH2

a numeric vector, 1 if the property has more than 2 bathrooms, 0 otherwise

GARAGE

a numeric vector,1 if the house has a garage, 0 otherwise

CENTHEAT

a numeric vector, 1 if the house has central heating, 0 otherwise

BEDS2

a numeric vector, 1 if the property has more than 2 bedrooms, 0 otherwise

UNEMPLOY

a numeric vector, the rate of unemployment in the census ward in which the house is located

PROF

a numeric vector, the proportion of the workforce in professional or managerial occupations in the census ward in which the house is located

References

Fotheringham, A.S., Brunsdon, C., and Charlton, M.E. (2002), Geographically Weighted Regression: The Analysis of Spatially Varying Relationships, Chichester: Wiley.

Lu, B, Charlton, M, Harris, P, Fotheringham, AS (2014) Geographically weighted regression with a non-Euclidean distance metric: a case study using hedonic house price data. International Journal of Geographical Information Science 28(4): 660-681

Author

Binbin Lu binbinlu@whu.edu.cn

Examples

library(sf)
data(LondonHP)
data(LondonBorough)
plot(LondonBorough$geometry)
plot(LondonHP["PURCHASE"], add = TRUE)