similar to: Subsetting problem data, 2

Hello Everyone, I have what I think is a complex text parsing task. I've provided some sample data below. There's a relatively simple version of the coding that needs to be done and a more complex version. If someone could help me out with either version, I'd greatly appreciate it. Here are my sample data. haveData <- structure(list(profile_key = structure(c(1L, 1L, 2L, 2L, 2L,

Hello All, Can anyone tell help me understand why the function below doesn't work and how I can fix it? Below are some sample data, some code that works on individual rows of the data, and my attempt to translate that code into a function. My hope is to get the function working and then to apply it to the larger data frame using ddply() from the plyr package or possibly some other approach.

Hi, I am trying to plot the following data so that it can be visually represented well. I tried the dotchart but I felt it was too spread out. Then I tried the barplot which is good enough for me. Is there a way to give the labels for the y-axis as in the dot chart? Also, I feel the grey level is confusing, so is there options for designs within the bars? I cannot use color as the journal wants

Dear all, Need a help. I would like to count combination of two columns: structure(list(V1 = structure(c(4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("23", "55", "67", "Env"), class = "factor"), V2 = structure(c(9L, 7L, 7L, 7L, 2L, 1L, 11L, 11L, 11L, 11L, 5L, 6L, 6L, 3L, 8L, 2L, 1L, 4L, 4L,

Both of the approx functions work correctly individually, but they are not being distinguished in the for loop by the if statments. Any help would be appreciated. for loop of interest is below x <- (structure(list(Site = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,

Hi All, I have a large data set with many columns of data. One of these columns is a species identifier and the remainder are variables such as temperature or mass. Currently I am carrying out a single regression on subsets of the data set, e.g. separated data sets with only the data from one species at a time. I have been searching for a thread that will help me to understand how best to repeat

dear R-team I need to find the min, max values for each patient from dataset and keep the output of it as a dataframe with the following columns - Patient nr - Region (remains same per patient) - Min score - Max score Patient Region Score Time 1 1 X 19 28 2 1 X 20 126 3 1 X 22 100 4 1 X 25 191 5 2 Y 12 1

Dear R experts, I am trying to analyze data from an article, the data looks like this Patient Age Sex Aura preCSM preFreq preIntensity postFreq postIntensity postOutcome 1 47 F A 4 6 9 2 8 SD 2 40 F A/N 5 8 9 0 0 E 3 49 M N 5 8 9 2 6 SD 4 40 F A 5 3 10 0 0 E 5 42 F N 5 4 9 0 0 E 6 35 F N 5 8 9 12 7 NR 7 38 F A 5 NA 10 2 9 SD 8 44 M A 4 4 10 0 0 E 9 47 M A 4 5 8 2 7 SD 10 53 F A 5 3 10 0 0 E 11

Hadley, I don't know if I am doing something wrong or if it is ggplot please see the two graphs at the bottom of the page (code). melt.nut <- (structure(list(RiverMile = c(119L, 119L, 119L, 119L, 119L, 119L, 119L, 119L, 119L, 148L, 148L, 148L, 148L, 148L, 148L, 148L, 179L, 179L, 179L, 179L, 179L, 179L, 179L, 185L, 185L, 185L, 185L, 185L, 185L, 185L, 190L, 190L, 190L, 190L, 190L, 190L,

Hello All... I gave a task to my students that involved using mclust to look for clusters in some bivariate data of isotopes vs various mining locations. They discovered something I didn?t expect; the data (called tur) is appended below. p <- qplot(x = dD, y = dCu65, data = tur, color = mine) print(p) # simple bivariate plot of the data; looks fine mod1 <- Mclust(tur[,2:3]) mod1$G mod2

Dear everyone I am a bit of a computer imbecile and are having problems with R. I am using R in my research project to do chi-square tests on data imported from excel . However I have som missing data in one of my variables (columns) and I need R to "exclude" these and make chi-square test on the data that I have. I use a formula to make 2x2 tables which is: data <-

Hi, I'm a database admin for a database which manage chromatographic results of products during stability studies. I use R for the reporting of the results in MS Word through R2wd. But now I think I need your help: suppose we have the following data frame: ID rrt Mnd Result 1 0.45 0 0.10 1 0.48 0 0.30 1 1.24 0 0.50 2 0.45 3 0.20 2 0.48 3 0.60 2 1.22 3 0.40 3

Dear R people Could you please help. Basically, there are two variables in my data set. Each patient ('id') may have one or more diseases ('diagnosis'). It looks like id diagnosis 1 ah 2 ah 2 ihd 2 im 3 ah 3 stroke 4 ah 4 ihd 4 angina 5 ihd .............. Q: How to make three data sets: 1. Patients with ah and ihd 2. Patients with ah but no ihd 3. Patients with ihd but no

Dear r-users, I would like to construct 3-day moving average for block maxima series. I tried this: bmthree <- lapply(split(dt, dt$Year), function(x) max(sapply(1:(nrow(x)-2), function(i) with(x, mean(Amount[i:(i+2)],na.rm=TRUE))))) bmthree and got the following output. $`1971` [1] 70.81667 $`1972` [1] 68.94553 $`1973` [1] 102.7236 $`1974` [1] 73.6625 $`1975` [1]

Hello all, I'm new in R, and I have a data-frame like this (dput information below): Specie Fooditem Occurrence Volume 1 Schizodon vegetal 1 0.05 2 Schizodon sediment 1 0.60 3 Schizodon vegetal 1 0.15 4 Schizodon alga 1 0.05 5 Schizodon sediment 1 0.90 6 Schizodon

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 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

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,

I am having difficulty understanding how I would constrain a data set by filtering out 'records' based on certain criteria. Using SQL I could query using 'select * from my.data where LithClass in ('sand', 'clay')' or some such. Using subset, there seem to be ghosts left behind (that is, all of the LithClass *.Labels* remain after subset) > dput(tcc)

I have the following: Time A1 A1 B1 B1 C1 C2 x y x y x y 0 5 6 6 7 7 9 1 3 4 4 3 9 9 2 5 2 6 4 7 4 I want to change it to the following: 0 1 2 x y x y x y A1 5 6 3 4 5 2 B1