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I want to use aggregate with the mean function on specific columns gender <- factor(c("m", "m", "f", "f", "m")) student <- c(0001, 0002, 0003, 0003, 0001) score <- c(50, 60, 70, 65, 60) basicSub <- data.frame(student, gender, score) basicSubMean <- aggregate(basicSub, by=list(basicSub$student), FUN=mean, na.rm=TRUE) This

basically I need to create a sliding window in a string. a way to explain this is: > v <-

It is a simple problem in that I simply want to convert the For loop to a more efficient method. It simply loops through a large vector checking if the numeric element is not equal to the index of that element. The following example demonstrates a simplified example: > rows <- 10 > collusionM <- Matrix(0,10,10,sparse=TRUE) > matchM <- matrix(c(1,2,3,4,4,6,7,9,9,10)) > >

I have a data frame with two columns, a factor and a numeric. I want to create data frame with the factor, its frequency and the median of the numeric column > head(motifList) events score 1 aeijm -0.25000000 2 begjm -0.25000000 3 afgjm -0.25000000 4 afhjm -0.25000000 5 aeijm -0.25000000 6 aehjm 0.08333333 To get the frequency table of events: > motifTable <-

...ith reshaping the data frame I think I had some success with the melt x = melt .data .frame(bsub,id.vars=c("name","nLevel","emot"),measure.vars=c("wrist")) But I can't figure out the cast to get the wrist values in the rows. Thanks ds David H. Shanabrook dhshanab@acad.umass.edu 256-1019 (home) [[alternative HTML version deleted]]

How can I get a substring based on the index into the string? strM <- c("abcde", "cdefg") ind <- c(1,3,5) I want to use ind to index into the strings so the result is: strMind <- c("ace", "ceg")

I am using color2D.matplot to plot a matrix about 400 by 200. The values in the matrix are 0:5 and NA. The resulting plot is not color, but shaded b/w. I tried to figure out how to add colors, I would like something like c(blue, green, red, cyan, green) #example motifx <- matrix(NA, nrow=100,ncol=20) motifx[,1:5] <- 1 motifx[,6:10] <- 2 motifx[,11:15] <- 3 motifx[,15:19] <- 4

I am working with a large sparse matrix trying replace all 1 values with 0. The normal method doesn't work. Here is a small example: > x <- Matrix(0,nrow=10,ncol=10,sparse=TRUE) > x[,1] <- 1:2 > x 10 x 10 sparse Matrix of class "dgCMatrix" [1,] 1 . . . . . . . . . [2,] 2 . . . . . . . . . [3,] 1 . . . . . . . . . [4,] 2 . . . . . . . . . [5,] 1 . . . . . . . . .

I wrote something to check for duplicate rows in a data frame, but it is too inefficient. Is there a way to do this without the nested loops? This code correctly indicates rows 1-7, 1-8, 2-9 and 7-8 are duplicates. > m <- matrix(c(1,1,1,1,1, 2,2,2,2,2, 6,6,6,6,6, 3,3,3,3,3, 4,4,4,4,4, 5,5,5,5,5, 1,1,1,1,1, 1,1,1,1,1, 2,2,2,2,2, 7,7,7,7,7), ncol=5, byrow=TRUE) > df <- data.frame(m)

I need to increment cells of a matrix (collusionM). The indexes to increment are in an index (matchIndex). This is some of the code for (j in 1:(rows-1)) matchIndex[[j]] <- which(mx[j]==mx) for (j in 1:(rows-1)) collisionM[j,matchIndex[[j]]] <- collisionM[j,matchIndex[[j]]] + 1 I could put them in the same loop but this is slower. The first for statement is fine. It finds the matches