YaleEnergy: Monthly energy consumption of Yale residential colleges.

Description

The data set contains monthly energy time series for Yale residential college, from July 1999 through July 2006

Usage

data(YaleEnergy)

Arguments

Format

A data frame with 1020 observations on the following 18 variables.

name: a factor with levels BERKELEY BRANFORD CALHOUN DAVENPORT EZRA STILES JONATHAN EDWARDS MORSE PIERSON SAYBROOK SILLIMAN TIMOTHY DWIGHT TRUMBULL
address: a factor with levels 189 ELM ST. 205 ELM ST. 241 ELM ST. 242 ELM ST. 248 YORK ST. 261 PARK ST. 302 YORK ST. 345 TEMPLE ST. 505 COLLEGE ST. 70 HIGH ST. 74 HIGH ST.
gsf: gross square footage of the college
EL: electrical consumption in kilowatt hours
ELSQFT: electrical consumption per square foot
CHW: chilled water consumption in tons
SQFTCHW: square feet per ton of chilled water
STEAM: steam consumption in pounds
STEAMSQFT: steam per square foot
MBTU: million British Thermal Units (BTU) from chilled water and steam
MBTUSQFT: million BTUs per square foot
year: year of the record
month: month of the record
lon: degrees longitude of the college
lat: degrees latitude

Examples

Run this code

# NOT RUN {
data(YaleEnergy)
whatis(YaleEnergy)

y <- YaleEnergy             # This is just for convenience.
esqft <- list(data.frame(y[y$name==y$name[1],"ELSQFT"]),
              data.frame(y[y$name==y$name[2],"ELSQFT"]),
              data.frame(y[y$name==y$name[3],"ELSQFT"]),
              data.frame(y[y$name==y$name[4],"ELSQFT"]),
              data.frame(y[y$name==y$name[5],"ELSQFT"]),
              data.frame(y[y$name==y$name[6],"ELSQFT"]),
              data.frame(y[y$name==y$name[7],"ELSQFT"]),
              data.frame(y[y$name==y$name[8],"ELSQFT"]),
              data.frame(y[y$name==y$name[9],"ELSQFT"]),
              data.frame(y[y$name==y$name[10],"ELSQFT"]),
              data.frame(y[y$name==y$name[11],"ELSQFT"]),
              data.frame(y[y$name==y$name[12],"ELSQFT"]))

# The sparkmat() command does most of the work:
sparkmat(esqft, locs=data.frame(y$lon, y$lat), new=TRUE,
         w=0.002, h=0.0002, just=c("left", "top"))

# We'll add some text for a nice finished product:
grid.text(y[1:12,1], unit(y$lon[1:12]+0.001, "native"),
          unit(y$lat[1:12]+0.00003, "native"),
          just=c("center", "bottom"), gp=gpar(cex=0.7))
grid.text("Degrees Longitude", 0.5, unit(-2.5, "lines"))
grid.text("Degrees Latitude", unit(-4.5, "lines"), 0.5, rot=90)
grid.text("Monthly Electrical Consumption (KwH/SqFt) of Yale Colleges",
          0.5, 0.8, gp=gpar(cex=1, font=2))
grid.text("July 1999 - July 2006",
          0.5, 0.74, gp=gpar(cex=1, font=2))
# }

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