Hi Jim, Some example data would help us. I typically think of a histogram as the frequency of values falling within a certain range (determined by bins). Since they are univariate plots, I'm not sure how you are planning on adding a line graph to that. If you just want bars of the average gasoline price at different years, perhaps something along these lines would work for you:
## Load required packages require(lattice) require(latticeExtra) ## Sample Data dat <- data.frame(year = 1996:2010, x1 = rnorm(15, 3, .2), x2 = rnorm(15, 200, 1)) ## Base xyplot (not a histogram) adding a layer with different y axis xyplot(x1 ~ year, data = dat, type = "h") + as.layer(xyplot(x2 ~ year, data = dat, type = "l", col = "black"), y.same = FALSE) ## See ?xyplot ?as.layer ?hist # for info about histograms HTH, Josh On Sun, Jan 9, 2011 at 5:13 PM, Jim Burke <j.bu...@earthlink.net> wrote: > Hello everyone, > > I have a simple histogram of gasoline prices going back a few years that I > want to insert a line graph of consumer price index (cpi) over the > histogram. I have looked through the "Lattice" book by Deepayan Sarkar but > don't see anything there. How might this be done? An example would be > wonderful. > > Current code snippet follows. For example additional field to add as a line > graph would be a cpi calculation like "gas_data$regular * (2010_cpi / > gas_data$year )". > > xyplot( regular ~ as.Date(gas_data$dates,"%b %d, %Y") , data = gas_data, > type = c("g", "h" )) > > Thanks, > Jim Burke > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Joshua Wiley Ph.D. Student, Health Psychology University of California, Los Angeles http://www.joshuawiley.com/ ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.