R Dataset / Package lattice / environmental

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Embed
<iframe src="https://embed.picostat.com/r-dataset-package-lattice-environmental.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-37302.csv 1.55 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Dataset Help

On this Picostat.com statistics page, you will find information about the environmental data set which pertains to Atmospheric environmental conditions in New York City . The environmental data set is found in the lattice R package. You can load the environmental data set in R by issuing the following command at the console data("environmental"). This will load the data into a variable called environmental. If R says the environmental data set is not found, you can try installing the package by issuing this command install.packages("lattice") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the environmental R data set. The size of this file is about 1,591 bytes.

Documentation

Atmospheric environmental conditions in New York City

Description

Daily measurements of ozone concentration, wind speed, temperature and solar radiation in New York City from May to September of 1973.

Usage

environmental

Format

A data frame with 111 observations on the following 4 variables.

ozone

Average ozone concentration (of hourly measurements) of in parts per billion.

radiation

Solar radiation (from 08:00 to 12:00) in langleys.

temperature

Maximum daily emperature in degrees Fahrenheit.

wind

Average wind speed (at 07:00 and 10:00) in miles per hour.

Author(s)

Documentation contributed by Kevin Wright.

Source

Bruntz, S. M., W. S. Cleveland, B. Kleiner, and J. L. Warner. (1974). The Dependence of Ambient Ozone on Solar Radiation, Wind, Temperature, and Mixing Height. In Symposium on Atmospheric Diffusion and Air Pollution, pages 125–128. American Meterological Society, Boston.

References

Cleveland, William S. (1993) Visualizing Data. Hobart Press, Summit, New Jersey.

Examples

# Scatter plot matrix with loess lines
splom(~environmental,
  panel=function(x,y){
    panel.xyplot(x,y)
    panel.loess(x,y)
  }
)
# Conditioned plot similar to figure 5.3 from Cleveland
attach(environmental)
Temperature <- equal.count(temperature, 4, 1/2)
Wind <- equal.count(wind, 4, 1/2)
xyplot((ozone^(1/3)) ~ radiation | Temperature * Wind,
  aspect=1,
	prepanel = function(x, y) 
		prepanel.loess(x, y, span = 1),
	panel = function(x, y){
		panel.grid(h = 2, v = 2)
		panel.xyplot(x, y, cex = .5)
		panel.loess(x, y, span = 1)
	},
	xlab = "Solar radiation (langleys)",
	ylab = "Ozone (cube root ppb)")
detach()# Similar display using the coplot function
with(environmental,{
  coplot((ozone^.33) ~ radiation | temperature * wind,
  number=c(4,4),
  panel = function(x, y, ...) panel.smooth(x, y, span = .8, ...),
  xlab="Solar radiation (langleys)",
  ylab="Ozone (cube root ppb)")
})
--

Dataset imported from https://www.r-project.org.

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