similar to: efficient matrix element comparison

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

I have a data frame something like: name wrist nLevel emot 1 4094 3.34 1 frustrated 2 4094 3.94 1 frustrated 3 4094 NA 1 frustrated 4 4094 3.51

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 <-

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 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

I am having some trouble getting the colors correct on county maps using the maps package. I have a data.frame that contains coloration data for every county -- it also contains a variable 'mapm' which fits the 'state,county' format used in the mapping package. I use this to define colors from a range of 1:100. The problem is that the colors seem good for some states/counties,

I represent a graph as an adjacency matrix of class "dgCMatrix" (from the Matrix package). > xx 5 x 5 sparse Matrix of class "dgCMatrix" a b c d e a . 1 1 . . b 1 . 1 . . c 1 1 . 1 1 d . . 1 . 1 e . . 1 1 . To check if the matrix defines and undirected graph, I have made the following functions/methods: is.UG <- function (object) { UseMethod("is.UG") }

Hi, I'm trying to create a new S4 class (myMatrix) which for now just extends dgCMatrix (from package Matrix). Then I want to use "[" which is defined in Matrix. Out of the box with "[" (defined in Matrix) I lose the class information and the result is an object of class dgCMatrix. If I specify a "["-method for myMatrix, it is not used because a signature

Dear R list, I came across dgCMatrix. I believe this class is associated with sparse matrix. I see there are 8 attributes to train$data, I am confused why are there so many, some are vectors, what do they do? Here's the R code: library(xgboost) data(agaricus.train, package='xgboost') data(agaricus.test, package='xgboost') train <- agaricus.train test <- agaricus.test

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

In the Matrix package v. 0.995-11 I see that the dgTMatrix Class for compressed, sparse, triplet-form matrices handles Identically indexed data instances by summing their values, e.g., library(Matrix) (Mt <- new("dgTMatrix", i = as.integer(c(0,0,1,1,4)), j = as.integer(c(0,1,2,2,4)), x = as.double(1:5), Dim = as.integer(c(5,5)))) ## 5 x 5 sparse Matrix of class

In the Matrix package v. 0.995-11 I see that the dgTMatrix Class for compressed, sparse, triplet-form matrices handles Identically indexed data instances by summing their values, e.g., library(Matrix) (Mt <- new("dgTMatrix", i = as.integer(c(0,0,1,1,4)), j = as.integer(c(0,1,2,2,4)), x = as.double(1:5), Dim = as.integer(c(5,5)))) ## 5 x 5 sparse Matrix of class

I want to create a sparse matrix of type "dgCMatrix" using the Matrix package (and the matrix must be of this type even if other more compact representations may exist). I do > library(Matrix) > m1<-Matrix(rep(1,4),nrow=2,ncol=2,sparse=T) > m1 2 x 2 sparse Matrix of class "dsCMatrix" [1,] 1 1 [2,] 1 1 To convert m1, I do > as(m1, "dgCMatrix")

Thank you for your responses. I guess I don't feel alone. I don't find the documentation go into any detail. I also find it surprising that, > object.size(train$data) 1730904 bytes > object.size(as.matrix(train$data)) 6575016 bytes the dgCMatrix actually takes less memory, though it *looks* like the opposite. Cheers! On Fri, Oct 20, 2017 at 3:22 PM, David Winsemius

Using the Matrix package, how can I create a row-oriented sparse Matrix from scratch populated with some data? By default a column-oriented one is created and I'm aware of the note that the package is optimized for column-oriented ones, but I'm only interested in using it for holding my sparse row-oriented data and doing basic subsetting by rows (even using drop=FALSE). Here is what I

Subsetting using [] vs. head(), gives different results. R code: > head(train$data, 5) [1] 0 0 1 0 0 > train$data[1:5, 1:5] 5 x 5 sparse Matrix of class "dgCMatrix" cap-shape=bell cap-shape=conical cap-shape=convex [1,] . . 1 [2,] . . 1 [3,] 1 .

> On Oct 20, 2017, at 11:11 AM, C W <tmrsg11 at gmail.com> wrote: > > Dear R list, > > I came across dgCMatrix. I believe this class is associated with sparse > matrix. Yes. See: help('dgCMatrix-class', pack=Matrix) If Martin Maechler happens to respond to this you should listen to him rather than anything I write. Much of what the Matrix package does appears

This is a Request For Comment, also BCCed to 390 package maintainers of reverse dependencies of the Matrix package. Most users and package authors working with our 'Matrix' package will be using it for numerical computations, and so will be using "dMatrix" (d : double precision) matrix objects M, and indirectly, e.g., for M >= c will also use "lMatrix" (l:

> On Oct 21, 2017, at 7:50 AM, Martin Maechler <maechler at stat.math.ethz.ch> wrote: > >>>>>> C W <tmrsg11 at gmail.com> >>>>>> on Fri, 20 Oct 2017 15:51:16 -0400 writes: > >> Thank you for your responses. I guess I don't feel >> alone. I don't find the documentation go into any detail. > >> I also find

>>>>> C W <tmrsg11 at gmail.com> >>>>> on Fri, 20 Oct 2017 15:51:16 -0400 writes: > Thank you for your responses. I guess I don't feel > alone. I don't find the documentation go into any detail. > I also find it surprising that, >> object.size(train$data) > 1730904 bytes >>