similar to: aggregate function / custom column names?

try this: scores.melt = data.frame(grade = floor(runif(100, 1,10)), variable = 'score', value = rnorm(100)); cast(scores.melt, grade ~ variable, fun.aggregate = c(mean, length)) it has the nice column names of: grade score_mean score_length 1 1 0.08788535 8 2 2 0.16720313 15 3 3 0.41046299 7 4 4 0.13928356 13 ... but

Hi, I am trying to aggregate max a Date type column but have weird result, how do I fix this? > a <- rbind( + data.frame(name='Tom', payday=as.Date('1999-01-01')), + data.frame(name='Tom', payday=as.Date('2000-01-01')), + data.frame(name='Pete', payday=as.Date('1998-01-01')), + data.frame(name='Pete',

Hi, When using the aggregate function to aggregate a data.frame by one or more grouping variables I often have the problem, that I want the mean for some numeric variables but the unique value for factor variables. So for example in this data-frame: data <- data.frame(x = rnorm(10,1,2), group = c(rep(1,5), rep(2,5)), gender =c(rep('m',5), rep('f',5))) aggregate(data,

Hi everybody! I'm working on R today so I have a lot of questions (you may have noticed that it's the 3rd email today). I'm new on R, so please excuse the "spam"! I have a dataset "ssfa" with many rows and the column names are: > names(ssfa) [1] "SPECSHOR" "BONE" "TO_POS" "MEASUREM" "FACETTE"

Hi, R function aggregate can only take summary stats functions, can I aggregate text columns? For example, for the dataframe below, > a <- rbind(data.frame(id=1, name='Tom', hobby='fishing'),data.frame(id=1, name='Tom', hobby='reading'),data.frame(id=2, name='Mary', hobby='reading'),data.frame(id=3, name='John',

Dear R-experts: I am using a function called AUC whose arguments are data, time, id, and dv. data is the name of the dataframe, time is the independent variable column name, id is the subject id and dv is the dependent variable. The function computes area under the curve by trapezoidal rule, for each subject id. I would like to embed this in aggregate to further subset by each

Dear Colleagues, does anybody know how to aggregate a data.frame using different functions for different columns? Sincerely ___________________ Markus Preisetanz Consultant Client Vela GmbH Albert-Roßhaupter-Str. 32 81369 München fon: +49 (0) 89 742 17-113 fax: +49 (0) 89 742 17-150 mailto:markus.preisetanz@clientvela.com

Hi, everyone, I have a data.frame named "eva" like this: IND PARTNO VC1 EO1 EO2 EO3 EO4 EO5 114 114001 2 5 4 4 5 4 114 114001 2 4 4 4 4 4 114 114001 2 4 NA NA NA NA 112 112002 2 3 3 6 2 6 112 112002 2 1 1 3 4 4 112 112003 2 6 6 6 5 6 112 112003 2 5 7 6 6 6 112 112003 2 6 6 6 4 5 114 114004 2

I am calculating the mean of each column grouped by the variable 'id'. I do this using aggregate, data.table, and plyr. My aggregate results do not match the other two, and I am trying to figure out what is incorrect with my syntax. Any suggestions? Thanks. Here is the data. myData <- structure(list(var1 = c(31.59, 32.21, 31.78, 31.34, 31.61, 31.61, 30.59, 30.84, 30.98, 30.79, 30.79,

Then you need to rethink your data structure. Use a list instead of a data frame. The components of a list can have different lengths, and the "apply" family of functions (lapply(), etc.) can operate on them. Consult any good R tutorial for details. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it."

Hello -- I posted this question yesterday and for some reason the post seems to be attached to the wrong thread. Also, I extended my test a little and it seems to indicate the problem is with spm. I would appreciate any help. Thanks. ========================================================== library(plyr) library(SemiPar) data <-

Hello -- I would like to know of a more efficient way of writing the following piece of code. Thanks. options(stringsAsFactors=FALSE) orig <- c(rep('11111111',100000),rep('22222222',200000),rep('33333333',300000),rep('44444444',400000)) orig.unique <- unique(orig) system.time(df <- as.data.frame(sapply(orig.unique, function(x) ifelse(orig==x, 1, 0))))

Hi Your example is rather confusing - partly because HTML formating, partly because weird coding. You probably could concatenate your data frames e.g. by rbind or merge and after that you could try to aggregate them somehow. I could construct example data.frames myself but most probably they would be different from yours and also the result would not be necessary the same as you expect. You

Hello, I am trying to plot time-series data with certain weeks highlighted using symbols. require(ggplot2) #plotting time series data timescale <- seq(as.Date("01/01/09","%m/%d/%y"), length.out=12, by=7) data.all <- data.frame( id = c(rep('111',12),rep('222',12),rep('333',12)), week=c(timescale,timescale,timescale),

This relates to a message from Christophe Pallier to r-help some time ago. Like myself, he finds aggregate very useful, but the interface a little cumbersome. I've implemented a more compact formula interface, found at the bottom of this message: data(ToothGrowth) # I used to aggregate like this: aggregate(list(len=ToothGrowth$len),

The documentation for `aggregate` makes it sound like aggregate.formula should behave identically to aggregate.data.frame (apart from the way the parameters are passed). But it looks like aggregate.formula is quietly removing rows where any of the "output" variables (those on the LHS of the formula) are NA. This differs from how aggregate.data.frame works. Is this expected behavior?

Dear all, I want to aggregate() my data based of the classes of a factors, just as in the help file, but how do I define the "Region varable" in the ?aggregate example? Now, the column is just like any other in my data matrix. As I understand it from ?(state), state contains a matrix with the columns Pop, Income etc., but Region is somehow separated. I noted below that as.list() is

Hi, I'm having some problems with the aggregate() function in the {stats} package, and the documentation doesn't address them. 1) Why would the first line work, but the second not? According to the help file, it accepts a "data=" argument. > with(tsrc, aggregate(x=DistRatio, by=list(Condition), FUN=mean)) Group.1 x 1 Congruent 1.741789 2 Mismatch 1.771425

Dear all, I try to summarise my data per category using aggregate, but for some reason I get the error message "sum" not meaningful for factors even though my vector is numeric. The data set is shown below. Could someone please give a hint. Thanks in advance! Sincerely, Tord > names(test) [1] "ObjektID" "tallstubbyta" > is.factor(test$ObjektID);

Hi, I find it a bit annoying that aggregate.default forces the returned object to loose the 'name' of the variable aggregated, replacing it with 'x'. A brief example: > dat <- data.frame(A = runif(100), B = rnorm(100), + Group = gl(4, 25)) > with(dat, aggregate(A, by = list(Group = Group), FUN = mean)) Group x 1 1 0.6523228 2 2