similar to: rowSums - am I getting something wrong?

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

I think I posted this patch before, but it looks like it was in December 2012 (!). 1/1 libxl: introduce an option for disabling the non-O_DIRECT workaround Ideally it would go into 4.4, at least. Provided the corresponding qemu part has gone into qemu-xen, which I think it has. Can anyone confirm ?

How do I completely remove the first column? (x <- matrix(c(1, 44, 124, 80, 254, 70, 190, 0, 2, 35, 110, 70, 240, 73, 216, 0, 3, 41, 114, 80, 279, 68, 178, 0, 4, 31, 100, 80, 284, 68, 149, 0, 5, 61, 190, 110, 315, 68, 182, 1, 6, 61, 130, 88, 250, 70, 185, 0, 7, 44, 130, 94, 298, 68, 161, 0, 8, 58, 110, 74, 384, 67, 175, 0, 9, 52, 120, 80, 310, 66, 144, 0, 10, 52, 120, 80, 337, 67, 130, 0, 11,

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

The example here puzzles me. It seems like the < operator doesn't work as expected. > l <- 0.6 > u <- seq(0.4, 0.7, 0.1) > u [1] 0.4 0.5 0.6 0.7 > mygrid <- expand.grid("l" = l, "u" = u) > mygrid l u 1 0.6 0.4 2 0.6 0.5 3 0.6 0.6 4 0.6 0.7 > mygridcollapsed <- mygrid[mygrid$l < mygrid$u, ] > mygridcollapsed l u 3 0.6 0.6 4

Hello, It's an alternative to use SAS by function in R? I want to plot d histograms by plot.from example bellow: Thank you! plot d 1 1 16.3 2 1 25.0 3 1 57.8 4 1 17.0 5 2 10.8 13 2 96.4 17 3 76.0 18 3 32.0 19 3 11.0 20 3 11.0 24 3 106.0 25 3 12.5 21 4 19.3 22 4 12.0 26 4 15.0 27 5 99.3 32 7 11.0 36

On Mon, Jun 19, 2017 at 12:06 PM, Mehdi AMINI <joker.eph at gmail.com> wrote: > Hi, > > 2017-06-19 8:45 GMT-07:00 Andrew Kelley via llvm-dev < > llvm-dev at lists.llvm.org>: > >> Greetings, >> >> I have a Zig implementation of ceil which is emitted into LLVM IR like >> this: >> >> ; Function Attrs: nobuiltin nounwind >> define

Hi Eik, thank you so much - it works perfectly! Thank you and best wishes Alain   Eik Vettorazzi <E.Vettorazzi@uke.de> hat am 6. Februar 2013 um 17:01 geschrieben: > Hi Alain, > here is a one-liner for a df without the rowSum column > >

Hi, how can I replace NA value with 0: 1991 217 119 103 109 137 202 283 240 146 NA 1992 270 174 149 144 166 239 278 237 275 NA 1993 146 111 104 89 98 131 153 148 175 NA 1994 177 123 146 124 121 200 266 191 240 106 1995 145 98 95 89 95 130 183 161 164 129 1996 145 98 89 90 93 138 158 131 161 161 1991 217 119 103 109 137 202 283 240 146 0 1992 270 174 149 144 166 239 278 237

Hi everyone, I've tried the below on R 1.9.1 and the 2004-08-30 builds of R 1.9.1 Patched and R 2.0.0 on Windows 2000, and the results are consistent. > seq(0.5, 0, by = -0.1) [1] 0.5 0.4 0.3 0.2 0.1 0.0 > seq(0.7, 0, by = -0.1) [1] 7.000000e-01 6.000000e-01 5.000000e-01 4.000000e-01 3.000000e-01 2.000000e-01 1.000000e-01 -1.110223e-16 Is this really the intended behaviour?

Hi, I have a matrix HR(9x27). I would like to make a single vector with elements: t(HR[,1]) followed by t(HR[,2]) and then t(HR[,3] ... etc. Is there any neat way of converting this matrix into a vector rather doing something like c(t(HR[,1]), t(HR[,2]), t(HR[,3]) ..)? Thanks in Advance. Kind regards, Ezhil ____________________________________________________________________________________

This is day one on R for me, I am trying to figure out how to do simple computations. For example I have a data set with 200 observations. I am trying to compute the mean and variance in r for 1:25 (first 25 observations); 1:50 (first 50 obs) ; 1:100th observation etc. Here is the dataset: Id value 1 2.2338 2 3.13597 3 1.98685 4 4.35593 5 2.43963 6 4.20262 7 3.12131 8 4.79583 9 3.13937 10

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

Dear all I am a BEGINNER and have R on my Mac. I saved my excel file as .txt file, I have just one column with first row as the column name. My file when read by R looks like this. After reading the table I try to make a histogram by hist(dbh), it says object dbh not found. What am I doing wrong? thanks dbh 1 11.53 2 16.05 3 7.36 4 16.05 5 8.66 6 12.74 7 22.93 8 7.55 9

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

Hi I am trying to calculate the row sums of a matrix i have created The matrix ( FeaturePresenceMatrix) has been created by 1) Read csv 2) Removing unnecesarry data using [-1:4,] command 3) replacing all the NA values with as.numeric(0) and all others with as.numeric (1) When I carry out the command TotalFeature <- rowrowSums(FeaturePresenceMatrix, na.rm = TRUE) I get the following