Hi, very new to R here... I have a data frame called 'set' with 100k+ rows in it that looks like this:
subject timestamp yvalue traceabs subjtrace 1 1 1992-07-12 06:05:00 12 1 1-1 2 1 1992-07-12 06:10:00 15 1 1-1 3 1 1992-07-12 06:15:00 17 1 1-1 4 1 1992-07-12 06:20:00 20 1 1-1 5 1 1992-07-12 06:25:00 24 1 1-1 .... There are 89 subjects, each of which have a different number of traces -- it's time series data. There are, in total, around 180 traces. The "subjtrace" variable is just a concatenation of the subject number, a hyphen, and the relative trace number. For instance, the first trace for subject 46 is "46-1" but the traceabs value for the same trace is 71. I need to perform simple statistics on each subject and on each trace. I also need to graph each trace. It seems like the easy approach to identifying the variables would be to use the split() function to create groups: > temp <- split(set, set$subject) When I then try, for example: > summary(temp[1]) all I get as a result is: Length Class Mode 1 5 data.frame list So I went with: > lapply(temp[1], summary) That works, but I'm unable to do something like: > lapply(temp[1]$yvalue, mean) because the result returned is: list() Ultimately, I'm trying to run the exact same code on each group, as defined by the subject number, and each trace. I would like to display something like the following: Subject # and Summary Statistics -- Graph of a trace belonging to the subject -- Summary statistics for the trace -- Graph of the next trace belonging to the subject -- Summary statistics for the trace -- etc... My intention is to dump this all into a .pdf file with Sweave and LaTeX. Questions: - Is split() the best function to use to create the proper groups? or should I look to create a separate variable for each group using subset, like: temp.46 <- subset(set, subject==46,select=c(subject, timestamp, yvalue, subjtrace)) - How do I call functions on data within the groups created by split()? Like... lapply(temp[1]$yvalue, sd) - In an effort to try to learn the proper way to approach this, what would be the best practice for iterating through the data and pushing it to .pdf? Thanks! ______________________________________________ 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.
