similar to: get mean of same elements in a data.frame

Hi, I need to aggregate rows of a data.frame by computing the mean for rows with the same factor-level on one factor-variable; here is the sample code: x <- data.frame(rep(letters,2), rnorm(52), rnorm(52), rnorm(52)) aggregate(x, list(x[,1]), mean) Now my problem is, that the actual data-set is much bigger (120 rows and approximately 100.000 columns) ? and it takes very very long

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, I have a vector full of strings like; xy_100_ab xy_101_ab xy_102_ab xy_103_ab I want to seperate each string in three pieces and the separator should be the "_" at the end I want a data.frame like: column1 column2 column3 xy 100 ab xy 101 ab xy 102 ab xy 103 ab I tried strsplit but I couldn't figure out how to convert the list I get into a data.frame. I just

Hi, I have multiple three dimensional arrays. Like this: x1 <- array(rnorm(1000, 1, 2), dim=c(10, 10, 10)) x2 <- array(rnorm(1000, 1, 2), dim=c(10, 10, 10)) x3 <- array(rnorm(1000, 1, 2), dim=c(10, 10, 10)) Now I would like to compute the mean for each corresponding cell. As a result I want to get one 3D array (10 x 10 x 10) in which at position x, y, z is the mean of the

Hi, I have a data.frame that looks like this: Subject <- c(rep(1,4), rep(2,4), rep(3,4)) y <- rnorm(12, 3, 2) gender <- c(rep("w",4), rep("m",4), rep("w",4)) comment <- c(rep("comment A",4), rep("comment B",4), rep("comment C",4)) data <- data.frame(Subject,y,gender,comment) data Subject y gender

Dear R-Users, I have a problem with an algorithm that iteratively goes over a data.frame and exclude n-columns each step based on a statistical criterion. So that the 'column-space' gets smaller and smaller with each iteration (like when you do stepwise regression). The problem is that in every round I use a new subset of my data.frame. However, as soon as I "generate" this

Hi, I have a vector like: r <- runif(100) Now I would like to split r into 10 pieces (each with 10 elements) ? but the 'pieces' should be roughly similar with regard to mean and sd. what is an efficient way to do this in R? thanks!

Hi, is there a way to replicate a data.frame like you can replicate the entries of a vector (with the repeat-function)? I want to do this: x <- data.frame(x, x) (where x is a data.frame). but n times. And it should be as cpu / memory efficient as possible, since n is pretty big in my case. thanks for any suggestions!

Hi, I have the following problem: I have two vectors: i <- c('a','c','g','h','b','d','f','k','l','e','i') j <- c('a', 'b', 'c') now I would like to generate a vector with the length of i that has zeros where i[x] != any element of j and 1 where i[x] == any element of j.

Hi, I have a somewhat abstract and tricky problem (at least for me). Perhaps someone here can help me: I would like to convert: x <- c(0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0) into x <- c(0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4) every 1 in x marks kind of a 'border' which is separated in different 'regions' in the

Hello again, let say we have following data: Dat1 <- structure(list(factor.sample.LETTERS.1.3...6..replace...T.. = structure(c(1L, 3L, 2L, 1L, 3L, 3L), .Label = c("A", "B", "C"), class = "factor"), factor.sample.letters.1.2...6..replace...T.. = structure(c(2L, 2L, 1L, 1L, 2L, 1L), .Label = c("a", "b"), class =

Dear Colleagues, Apologies for a long email to ask what I feel may be a very simple question; I figure it's better to overspecify my situation. I was asked a question, recently, by a colleague in my department about pre-aggregating variables, i.e., computing the mean of defined subsets of a data frame. Naturally, I thought of the 'by' and 'tapply' functions, as

Hi, I am still struggling with three dimensional arrays. Now I would like to convert a three dimensional array into a data-frame with the coordinate-columns: x, y, z and a value-column. And I definitely don't want to loop over every element, since this would be very resource intensive for the actual data-set. Are there any specific functions that are helpful for this task?

Hi, I would like to cut a vector of values in parts. Each part should have an equal number of elements. for example: x <- (rnorm(500)^2) now I want 5 vectors each with 100 elements. The first vector should include the 100 lowest values of x and so on (so that the fifth vector contains the 100 highest values of x). thanks for any help!

> n=10;t=3 > d<-cbind(id=rep(1:n,each=t),y=rnorm(n*t),x=rnorm(n*t),z=rnorm(n*t)) > head(d) id y x z [1,] 1 -2.1725379 0.07629954 -0.3985258 [2,] 1 -1.2383038 -2.49667038 0.6966127 [3,] 1 -1.2642401 -0.50613307 0.4895856 [4,] 2 0.2171246 0.86711864 -0.6660036 [5,] 2 2.2765760 -0.48547142 -1.4496664 [6,] 2 0.5985345 -1.06427035 2.1761071

Dear all, let say I have following data frame: > data.frame(x=rnorm(18), y=rep(c("a", "b", "c"), each=6)) x y 1 -1.072152537 a 2 0.382985265 a 3 0.058877377 a 4 -0.006911939 a 5 -2.355269051 a 6 -0.303095553 a 7 0.484038422 b 8 0.733928931 b 9 -1.136014346 b 10 0.503552090 b 11 1.708609658 b 12 -0.294599403 b 13

hi, I have two data.frames each with two columns; x1 1 4 1 3 1 6 2 9 2 2 2 5 3 6 3 7 3 4 x2 1 -3 1 -7 2 -3 2 -2 2 -8 3 -1 3 -2 3 -1 now I want to merge this data.frames to one data.frame. The problem is, that sometimes there is a different number of elements per category. (like above x1 has 3 values for the value 1 in the first row, but x2 has only 2 values for the value 1 in the

Dear R-Users, I have the following two vectors: data <- rnorm(40, 0, 2) positions <- c(3, 4, 5, 8, 9, 10, 20, 21, 22, 30, 31, 32) now I would like to calculate the mean of every chunk of data-points (of the data-vector) as defined by the positions-vector. So I would like to get a vector with the mean of element 3 to 5 of the data-vector, 8 to 10, 20 to 22 and so

Hi, I would like to fit lm-models to a matrix with 'samples' of a dependent variable (each row represents one sample of the dependent variable). The independent variable is a vector that stays the same: y <- c(1:10) x <- matrix(rnorm(5*10,0,1), 5, 10) now I would like to avoid looping over the rows, since my original matrix is much larger; for(t in 1:dim(x)[1]) {

Hi, I have the following problem: I have a list of entries with vehicles going from some places to others and the time that they need. e.g. Vehicle Start End Time 1 A B 5 2 A C 4 3 A C 3 4 B A 6 5 B C 4 6 B C 6 7 C B 2 8 C B 4 9