similar to: xyplot: Can I identify groups but not use them for regression?

I wish to create a multipanel plot (map) from several datasets ("d" and "q" in the example below). I can condition the main xyplot statement on the "site" variable, but I don't know how to pass a conditioning variable to panel.xyplot plot so that the x-y coordinates from dataset q are only plotted at the appropriate site. library(lattice) d <-

I have a data set similar to this: P1id Veg1 Veg2 AreaPoly2 P2ID 1 p p 1 1 1 p p 1.5 2 2 p p 2 3 2 p h 3.5 4 For each group of "Poly1id" records, I wish to output (subset) the record which has largest "AreaPoly2" value, but only if

I would like to use POSIX classes to store dates and extract components of dates. Following the example in Spector ("Data Manipulation in R"), I create a date > mydate = as. POSIXlt('2005-4-19 7:01:00') I then successfully extract the day with the command > mydate$day [1] 19 But when I try to extract the month > mydate$mon [1] 3 it returns the wrong month. And

How can I eliminate the border drawn by default around a wireframe plot? I've tried using border=NA and box=FALSE to no avail. Scott Waichler Pacific Northwest National Laboratory scott.waichler at pnl.gov

I wish to display a single-panel Lattice figure with grouped data and fitted regression lines. I don't seem to be able to get the individual regression lines to display, e.g.; d <- data.frame(q = rep(1:6, each=10), cc = rep(seq(10,100, 10),6)) # create data frame with group identifier 'q', independent variable cc d$ba = d$q*0.1*d$cc + 5*rnorm(nrow(d))

I have a moderately complex graph with three panels. There are data points plotted, and fitted lines are added using a panel function, which includes "with(alt.data[[which.packet()[1]]]" statements. It all graphs out beautifully, but none of the usual tricks to get the proper legend to plot are working, i.e., using auto.key, key, etc. One message I keep getting is Error in

Friends: I wish to overlay data points on a contour graph. The following example produces a nice contour plot, but I have not mastered the concept of using panel functions to modify plots. Can someone show me how to overlay the data points (given after contour plot statement) on the contourplot? --Seth model <- function(a,b,c,X1,X2) # provide model function for contour

I have a list that is made of lists of varying length. I wish to create a new vector that contains the last element of each list. So far I have used sapply to determine the length of each list, but I'm stymied at the part where I index the list to make a new vector containing only the last item of each list mylist =

I'm writing an expression that requires searching a vector according to group. As an example, I want to find the maximum value in each of 5 groups. group=rep(1:5, each=5) # create grouping variable variable=rnorm(25) # generate data d <- data.frame(group,variable) # make data frame

I would like to eliminate the outer box around a lattice wireframe graph, but the usual recommended solution, which is to assign a color of 'transparent' to the axis.line parameter, eliminates ticks if the 'arrows=F' command is used, as shown in the following example: test = data.frame(expand.grid(c(1:10), c(1:10))) z = test[,1] + test[,2] test = cbind(test, z) names(test) =

I would like to remove the outermost box from my wireframe plots -- this is the box that is automatically generated, and is not the inner cube that frames the data. There was a thread on this 4 yrs ago but none of the fixes work (e.g., grid.newpage(), grid.lines(gp = gpar(col = NA)) or par.box=list(col=1),col=NA. These just make the data or the cube disappear. Has anyone solved this issue?

I'm working on a contourplot( ) graph, the subject of several previous posts to this list. The contours express probabilities from 0 - 1, but the key that is automatically generated by contourplot pads the probability scale with values that are impossible (i.e, range goes from -0.2 to 1.2), which will be confusing to those who view the plot. How can I get the scale to just run from 0 - 1?

Dear r-help, I need to draw xyplot() graphs with several regression lines: one line for the whole range of x (the variable on the horizontal axis) and two additional lines for subranges of x. Is it possible to make first regression line (panel.lmline(x,y,...);) to be drawn on the whole graph and regression lines of the subsets to be drawn only over their subsets? I have defined

Thanks to all that replied. I had just looked through the httr code and sure enough for a .csv mime time it calls readr::read_csv(). The httr::content docs suggest not using automatic parsing in a package, rather to determine mime type and parse yourself and Ben's suggestion also works if I do: junk <- readr::read_csv(r1$content, col_types = cols()) Perfect. Using httr rather than

Hi All: I am using httr to download files form a service, in this case a .csv file. When I use httr::content on the result, I get a message. Since this will be in a package. I want to suppress the message, but haven't figured out how to do so. The following should reproduce the result: myURL <-

Hi, I am trying to produce an xyplot with a regression line. The data should be represented as log/log but when I fit the lmline I receive an error message - the plot is fine without the log transformation, but the then the plot is meaningless. I know it must be something simple, but I just can't see it. Hope someone can help... Thanks. xyplot(log(Pk)~log(k),data=rwpk,cex=1,

Ahoy! That's a message generated by the readr::read_table() function (or it's friends). You can suppress it a number of ways, but this should work as httr::content() will pass through arguments, like col_types = cols(), to the file reader. junk <- httr::content(r1, col_types = cols()) See more here... https://blog.rstudio.com/2016/08/05/readr-1-0-0/

Dear R Users, I have an xyplot() where different plotting symbols are used for subgroups (originally used within S-Plus, but hopefully it?s also applicable to R users). How can I fit separate regression lines for every subgroup? So far, I can only plot the overall fitted line. The code looks like this: trellis.device() sps<-trellis.par.get("superpose.symbol") sps$pch<-1:7

Does identify work in lattice plots? I tried this in R 1.4.1 (original release) on my Win2000 machine with lattice 0.4-0 and grid 0.5-1. > xyplot(y ~ x, + panel=function(x, y, ...){ + panel.xyplot(x, y, col=2, pch=20, ...) + panel.lmline(x, y, type = "l") + identify(x, y) + }) I get a change of cursor after the data points and the LS line are plotted

Page 140 of MASS uses the function xyplot. But I don't find it in R. Is there a package that I should load to use xyplot. Or there is a function with a different name in R that does the same thing as xyplot in S. xyplot(Gas ~ Temp | Insul, whiteside, panel = function(x, y, ...) { panel.xyplot(x, y, ...) panel.lmline(x, y, ...) }, xlab = "Average external temperature (deg. C)", ylab