similar to: Can somebody help me with following data manipulation?

I think the subject says it all. I want to make a simple lattice plot, using xyplot with the argument type=c("l","a"). The problem then is that in the resulting plot it is difficult/impossible to see which plot corresponds to the average and which to the individual profiles. I triedthings like extra arguments lwd=c(1,3) or col=c("blue","red") hoping

Hi R Helpers, I have been looking for an example of how to execute different dplyr mutate statements on the same dataframe in a single step. I show how to do what I want to do by going from df0 to df1 to df2 to df3 by applying a mutate statement to each dataframe in sequence, but I would like to know if there is a way to execute this in a single step; so simply go from df0 to df1 while executing

?s 22:50 de 17/10/2024, Sparks, John escreveu: > Hi R Helpers, > > I have been looking for an example of how to execute different dplyr mutate statements on the same dataframe in a single step. I show how to do what I want to do by going from df0 to df1 to df2 to df3 by applying a mutate statement to each dataframe in sequence, but I would like to know if there is a way to execute this

d <- structure(list(Site = structure(c(8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L,

I would like to preform a t.test to each of the measured variables (sand.silt etc.) with a mean and sd for each of the treatments (up or down), and out put this as a table.... I am having a hard time starting- maybe it is to close to lunch. Any suggestions would be greatly appreciated. Stephen Sefick x <- (structure(list(sample. = structure(c(1L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 2L, 3L,

Hello- I have a dataset which basically looks like this: Location Sex Date Time Verbal Self harm Violence_objects Violence A 1 1-4-2007 1800 3 0 1 3 A 1 1-4-2007 1230 2 1 2 4 D 2 2-4-2007 1100 0

I have a dataframe df with columns x, y, and height. I want to create a heatmap-like plot that creates a grid of x by y, and then color codes the grid depending on the value of height. Is there a ggplot2 object to do this? I'm able to easily do this in Excel with pivot tables and conditional formatting so I'm including an image that is close to the output I want. I want to be able to

# hi all, # I'm trying to plot temperatures by date in a trellis plot by their stations # I'm plotting the following data.frame library(lattice) h <- structure(list(station_name = structure(c(3L, 4L, 2L, 10L, 11L, 12L, 6L, 7L, 5L, 8L, 9L, 3L, 4L, 2L, 10L, 11L, 12L, 6L, 7L, 5L, 8L, 9L, 3L, 4L, 2L, 10L, 11L, 12L, 6L, 7L), .Label = c("Ashqelon", "Beer Sheva",

Hi, I just tried to upgrade Nixpkgs to R 3.5.0, but unfortunately the new version fails its regression test suite. We configure the build using the flags "--without-recommended-packages", in case that's relevant. You can see a complete build log with all relevant information at [1]. Anyway, the test failures look like this: | make[3]: Entering directory

Dear William and Ben, Thank you for your replies and elegant solutions. I am having trouble with the fact that two of the previous locations do not appear in current locations (that is no one moved to OKC and Dallas from other cities), so these two cities are not being included in the output. I have provided a better sample of the data and the ideal output (wide form - a 10x10 bilateral matrix)

Dear all, I am facing some problem with how to fit a "Baseline category Logit model" with R. Basically I am considering famous "Alligator" data as discussed by Agresti. This data can also be found here: https://onlinecourses.science.psu.edu/stat504/node/174 (there is also an accompanying R file, however the underlying R code could not load the data properly!!!) Below are

Hi Keep your messages in the list, you increase your chance to get some answer. I changed your data to groupedData object (see below), but I did not find any problem in it. plot(wlg) gives reasonable picture and I am not such expert to see any problem with data. Seems to me, that something has to be wrong with nlsList function. > wheat.list <- nlsList(Prop ~ SSlogis(end,Asym, xmid,

R experts, I am working with a fairly large data set comprised of 563 rows by 116 columns including several different modes. I have been unable to read in the data set completely using the read.table function and the RGui (i.e. nearly half the total number of rows are missing from the data set along with the column names). The data does read in fully using Tinn-R's Rterm; however, at several

Hi R-Help, data at bottom I've been struggling with a problem where I need to order based on 1) the Frequency "Freq" and 2) keeping each group of 3 of the same type together "Var2" but I want across all groups it to go "high to low" based on the earn factor. Thank you! structure(list(Var1 = structure(c(1L, 3L, 2L, 1L, 2L, 3L, 1L, 3L, 2L, 3L, 1L, 2L, 3L, 1L,

Dear List I am trying to fit a multinomial model using the mlogit package. Attempting to load the data into mlogit presents the following error. MLOG<-mlogit.data(Mult3,shape="long",choice="CHOICE",alt.var="mode.ids",indivs = "set3",chid.var = "obs") Error in `row.names<-.data.frame`(`*tmp*`, value = c("1.1", "1.2",

Hello- I have rather a messy SPSS file which I have imported to R, I've dput'd some of the columns at the end of this message. I wish to get rid of all the labels and have numeric values using as.numeric. The funny thing is it works like this: as.numeric(mydata[,2]) # generates correct numbers however, if I pass the whole dataframe at once like this: apply(mydata, 1:2, function(x)

Hello, I have a question about modelling via glm. I have a dataset (see dput) that looks like as if it where poisson distributed (actually I would appreciate that) but it isnt because mean unequals var. > mean (x) [1] 901.7827 > var (x) [1] 132439.3 Anyway, I tried to model it via poisson and quasipoisson. Actually, just to get an impression how glm works. But I dont know how to

Hi all, I have the following data and I have a histogram for mms like ggplot(hist,aes(x=hist$mms))+ geom_histogram(binwidth=1,fill="white",color="black")and then I want to fill the color of histogram by probable=1 and probable=0, could anyone help me in this? My data: structure(list(probable = c(1L, 0L, 1L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 1L, 1L,

Hello all, I'm sorry if my question seems basic. Im studying a responses (Yes,No) in a survey and, thanks to GLM I obtain the following relation with my variables : (Yes,No)~ ?0 + Age We note this this certain type of (Yes,No) response is linked to age (p<0.05 in glm) . After that we calculated : model1=glm(cbind(Yes,No) ~ Age + Times + Type, family=binomial) summary(model1)

Dear all, I was wondering if anyone could help solve a problem of a missing interaction effect!! I carried out a 2 x 2 factorial experiment to see if eggs from 2 different locations (Origin = 1 or 2) had different hatching success under 2 different incubation schedules (Treat = 1 or 2). Six eggs were taken from 10 females (random = Female) at each location and split between the treatments,