Peter--
That's it exactly! Thanks.
--Chris
Christopher W. Ryan, MD
SUNY Upstate Medical University Clinical Campus at Binghamton
425 Robinson Street, Binghamton, NY 13904
cryanatbinghamtondotedu
"Observation is a more powerful force than you could possibly reckon.
The invisible, the overlooked, and the unobserved are the most in danger
of reaching the end of the spectrum. They lose the last of their light.
From there, anything can happen . . ." [God, in "Joan of Arcadia,"
episode entitled, "The Uncertainty Principle."]
Peter Ehlers wrote:
On 2011-03-22 12:12, Christopher W Ryan wrote:
I have a dataframe that looks like this:
> str(chr)
'data.frame': 84 obs. of 7 variables:
$ county: Factor w/ 3 levels "Broome","Nassau",..: 3 3 3 3 3 3 3 3 3 3
...
$ item : Factor w/ 28 levels "Access to healthy foods",..: 21 19 20
18 16 3 2 6 17 8 ...
$ value : num 8644 15 3.5 3.9 7.7 ...
$ low : num 7897 9 2.5 2.6 7 ...
$ high : num 9390 22 4.5 5.2 8.4 37 30 23 24 101 ...
$ target: num 5034 11 2.7 2.6 6.1 ...
$ nys : num 6099 16 3.5 3.3 8 ...
head(chr)
county item value low high target nys
1 Sullivan Premature death 8644.0 7897.0 9390.0 5034.0 6099.0
2 Sullivan Poor or fair health 15.0 9.0 22.0 11.0 16.0
3 Sullivan Poor physical health days 3.5 2.5 4.5 2.7 3.5
4 Sullivan Poor mental health days 3.9 2.6 5.2 2.6 3.3
5 Sullivan Low birthweight 7.7 7.0 8.4 6.1 8.0
6 Sullivan Adult smoking 29.0 22.0 37.0 15.0 20.0
I'd like to graph high and low for "Premature death" for each of the
three counties, with 3 vertical line segments, one connecting those
two points for each county. I can get the two points for each county:
xyplot(low+high ~ county, data=subset(chr, item=="Premature death"))
but I have not yet been able to figure out how to draw the 3 vertical
line segments. Been struggling to understand panel functions, but no
success so far. I'd be grateful for any advice.
For lattice, I usually prefer the long version of a dataset.
Try this:
dd <- data.frame(county = letters[1:3],
lo = c(5,2,3),
hi = c(9,5,10))
## convert to 'long' format (you can use the reshape() function in stats
or the reshape package:
require(reshape)
dd.long <- melt(dd, id = "county")
dd.long
require(lattice)
xyplot(value ~ county, data = dd.long, groups = county,
pch = 19, type = 'b', cex = 2, lwd = 5, col = 2:4)
Peter Ehlers
Thanks.
--Chris Ryan
SUNY Upstate Medical University
Clinical Campus at Binghamton
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