similar to: Error in rowSums

For the query below I have also included the follwing information. Thanks for your replies > str(FeaturePresenceMatrix) chr [1:65530, 1:40] "0" "0" "0" "0" "1" "0" "0" "0" "0" ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:65530] "4" "5" "6" "7" ...

Working with an NxMxO sized matrix, currently I can do this in my code: if (max(colSums(array)) >= number) But to get an equivalent result using rowSums, I have to do: for (i in 1:10) { if (max(rowSums(array[,,i])) >= number) } I'm running both in a much larger loop that loops millions of times, so speed and such is quite a big factor for me. Currently, the colSums line uses about

Hi, I'm using colSums and rowSums to sum the first dimensions of arrays. It works ok but the resulting object is different. See > a3d <- array(rnorm(120, mean=2), dim=c(20,6,1)) > dim(colSums(a3d)) [1] 6 1 > dim(rowSums(a3d)) NULL > class(colSums(a3d)) [1] "matrix" > class(rowSums(a3d)) [1] "numeric" I was expecting rowSums to preserve the array

Hi [R-2.6.0, macOSX 10.4.10]. The helppage says that rowSums() and colSums() are equivalent to 'apply' with 'FUN = sum'. But I came across this: > a <- matrix(1:30,5,6) > is.integer(apply(a,1,sum)) [1] TRUE > is.integer(rowSums(a)) [1] FALSE > so rowSums() returns a float. Why is this? -- Robin Hankin Uncertainty Analyst National Oceanography Centre,

Hi R-users, I have a list a <- list(one=matrix(rnorm(20), 5, 4), two=matrix(rnorm(20, 3, 0.5),5,4)) How to add rowSums (calculated using lapply) to corresponding matrix in this list lapply(a, function(x) rowSums(x)) ?? -Lauri

I have a question on RowSums. Lets say i have a timeSeries table A B C 1/1/90 NA 1 1 1/2/90 NA 1 1 1/3/90 NA 1 1 1/4/90 NA 1 1 1/5/90 1 1 1 1/6/90 1 1 1 if i use RowSums, i will get 1/5/90 3 1/6/90 3 but i want 1/1/90 2 1/2/90 2 1/3/90 2 1/4/90 2 1/5/90 3 1/6/90 3 I cant

Hi all I have a data frame with duplicate columns and i want to remove duplicates by adding rows in each group of duplicates, but have lots of NA's. Data: dfrm <- data.frame(a = 1:4, b= 1:4, cc= 1:4, dd=1:10, ee=1:4) names(dfrm) <- c("a", "a", "b", "b", "b") dfrm[3,2:3]<-NA dfrm a a b b b 1 1 1 1 1 1 2 2 2 2 2 2 3

Say I have the following data: testDat <- data.frame(A = c(1,NA,3), B = c(NA, NA, 3)) > testDat A B 1 1 NA 2 NA NA 3 3 3 rowsums() with na.rm=TRUE generates the following, which is not desired: > rowSums(testDat[, c('A', 'B')], na.rm=T) [1] 1 0 6 rowsums() with na.rm=F generates the following, which is also not desired: > rowSums(testDat[, c('A',

Dear R-help community, If I have a data.frame df as follows: > df x1 x2 x3 x4 x5 x6 1 5 5 1 1 2 1 2 5 5 5 5 1 5 3 1 5 5 5 5 5 4 5 5 1 4 5 5 5 5 1 5 2 4 1 6 5 1 5 4 5 1 7 5 1 5 4 4 5 8 5 1 1 1 1 5 9 1 5 1 1 2 5 10 5 1 5 4 5 5 11 1 5 5 2 1 1 12 5 5 5 4 4 1 13 1 5 1 4 4 1 14 1 1 5 4 5 5 15 1 5 5 4

Greetings, My goal is to create a Markov transition matrix (probability of moving from one state to another) with the 'highest traffic' portion of the matrix occupying the top-left section. Consider the following sample: inputData <- c( c(5, 3, 1, 6, 7), c(9, 7, 3, 10, 11), c(1, 2, 3, 4, 5), c(2, 4, 6, 8, 10), c(9, 5, 2, 1, 1) ) MAT <- matrix(inputData,

I'm having a very frustrating problem, trying to find the inverse distance squared weighted interpolants of some weather data. I have a data frame of weights, which sum to 1. I have attached the weights data. I also have a data frame of temperatures at 48 grid points, which I have also attached. Now, all I need to do is multiply all of the rows of the temperature data frame by the weights

Dear All, It's Eszter again from Hungary. I could not solve my problem form yesterday, so I still have to ask your help. I have a binary dataset of vegetation samples and species as a comma separated file. I would like to calculate the Jaccard distance of the dataset. I have the following error message: Error in rowSums(x, prod(dn), p, na.rm) : 'x' must be numeric In addition:

Hello I would appreciate your help on the followig. I want to generate random binary matrices but I need to discard those with all-1 rows. That is, for a 10x10 matrix with five 1's [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 0 0 0 0 0 0 0 0 0 1 [2,] 0 0 0 0 0 0 1 0 0 0 [3,] 0 0 0 0 0 0 1

I am trying to construct a data set with some sequences for example: a = seq(0,1,0.1) m = matrix(nrow = 1331, ncol = 3) m[,1] = rep(a,121) m[,2] = rep(a,11,each = 11) m[,3] = rep(a,1,each = 121) I realize that there may be better ways of doing this, but this approach demonstrates the problem I'm having. I then want to get the sum of the rows and delete any row with a sum of greater than 1.

Dear R-List, I am sure there must be a very simple way to do this - I just do not know how... This is what I want to do: #my dataframe df<-data.frame(id=c("x01","x02","x03","x04","x05","x06"),a=c(1,2,NA,4,5,6),b=c(2,4,6,8,10,NA),c=c(NA,3,9,12,NA,NA),sum=c(3,9,15,24,15,6))    id    a     b     c   sum 1 x01  1     2    NA   3 2

Hi... I have a dataframe with n columns and n rows. I need to find how many rows contains zero raw read count across all column. Thanks -- *Yogesh Gupta* *Postdoctoral Researcher* *Department of Biological Science* *Seoul National University* *Seoul, South Korea* [[alternative HTML version deleted]]

(a) In R 2.12.2 rowsum can overflow if given an integer input: > rowsum(c(2e9L, 2e9L), c("a", "a")) [,1] a -294967296 > 2^32 + .Last.value [,1] a 4e+09 Should it be changed to coerce its x argument to numeric (double precision) so it always returns a numeric output? (b) When rowsum is given an x containing both NaN and NA it appears to use the last

Dear list, I have some trouble generating a frequency table over a number of vectors. Creating these tables over simple numbers is no problem with table() > table(c(1,1,1,3,4,5)) 1 3 4 5 3 1 1 1 , but how can i for example turn: 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 0 into 0 0 1 1 1 0 0 2 0 1 0 3 My second problem is, sorting rows and columns of a matrix by the rowSums/colSums. I did it

##I want to remove the rows where the row sums are zero and this is as far as I have gotten ffg <- (structure(list(CD = c(0, 0, 0, 0, 3.125, 0, 0, 0, 0, 1.6, 3.125, 0, 0, 6.25, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.125, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.125, 0, 0, 0, 0, 0, 0, 0, 0,

> with the entirely different rowSums, but it has been around > for a long time.) A lot longer than rowSums ... > Bill Dunlap > Spotfire, TIBCO Software --- This made me smile. The rowsums function was originally an internal part of the survival package, used for fast computation of certain sums when there is a cluster() statement. It was Statistical