similar to: "apply" question

R 2.15.1 OS X Colleagues, I am reading a 1 GB file into R using read.table. The file consists of 100 tables, each of which is headed by two lines of characters. The first of these lines is: TABLE NO. 1 The second is a list of column headers. For example: TABLE NO. 1 COL1 COL2 COL3 COL4 COL5 COL6 COL7 COL8 COL9 COL10

Dear useRs, i want to split a matrix having 1116rows and 12 columns. i want to split that matrix into 36 small matrices each having 12 columns and 31 rows. The big matrix should be splitted row wise. which means that the first small matrix should copy values which are in first 31 rows and 12 columns of the big matrix. similarly 2nd small matrix should contain values from 32nd to 63rd row of the

dear useRs, i have a list containing 16 matrices. i want to calculate the column mean of each of them. i tried >sr <- lapply(s,function(x) colMeans(x, na.rm=TRUE)) but i am getting the following error >Error in colMeans(x, na.rm = TRUE) : 'x' must be numeric can it be done in any other way? and why i am getting this error?? thanks in advance.. elisa [[alternative

Hi, is there a way I can calculate a summary statistics for a columns matrix let say we have this matrix x <- matrix(sample(1:8000),nrow=100) colnames(x)<- paste("Col",1:ncol(x),sep="") if I used summary summary(x) i get the output for each column but I need the output to be in matrix with rownames and all the columns beside it this how I want it

Hello, colnames seems to be not optimized well for data.frame. It escapes processing for data.frame in if (is.data.frame(x) && do.NULL) return(names(x)) but only when do.NULL true. This makes huge difference when do.NULL false. Minimal edit to `colnames`: if (is.data.frame(x)) { nm <- names(x) if (do.NULL || !is.null(nm)) return(nm) else

Hi, In a function, I compute 10 (un-named) vectors of reasonable length (4471 in the particular example I have to hand) that I want to combine into a data frame object, that the function will return. This is very slow, so *I'm* doing something wrong if I want it to be quick and efficient, though I'm not sure what the best way to do this would be. I know it is the combining into data

Full_Name: Robert Pusz Version: 2.2.1 OS: Windows Submission from: (NULL) (157.25.9.126) Hello, In my opinion something is wrong with 'weights' option in glm. My code is following: ###begin of the code#### cl <- c(5012, 106, 3410, 5655, 1092, 1513, 557, 1351, 3133, 2063, 3257, 4179, 5582, 5900, 8473, 4932, 3463, 5596, 2262, 0, 2638, 1111, 4881, 4211, 6271, 5257, 6926, 6165, 0, 0,

Hello List ! I'm a bright new R user, and I encounter a problem when trying to use the neuralnet package. I have a training set with 8 inputs, and there are 3 outputs (I need 3 distinct neurones as output). Although I read the examples, and the package article, I don't know how to tell R there are 3 outputs (3 outputs neurones). Here is my actual code : # All = input data All <-

Greetings! I am just now learning to use R for my dissertation project. I need to manipulate a lot of text and numeric data. I created a data frame that has 7 columns and 127 unique rows. Now I need to replicate each line 6 times and then later change values in the first 2 columns. I am trying to figure out how to accomplish this. I think that I need to use rep(my.df, each=6) but it does

Hello, my question is about the data handling. I have a data set that is lined as: 4 1 17 1 1 -5.1536 -0.1668 -2.3412 -0.5062 0.9621 0.3640 0.3678 -0.5081 -0.2227 0.8142 -0.0389 -0.0445 -0.0578 -0.1175 -0.1232 0.8673 -0.1033 -0.0796 -0.0341 -0.1716 -0.1801 -0.7014 0.6578 0.5611 4 1 17 2 1 -5.1536 -0.1668 -2.3412 -0.5062 0.9621 0.3640 0.3678 -0.5081 -0.2227 0.8142 -0.0389 -0.0445

Hi everybody! I am sorry to bother you with a question so simple but I think there might be a better solution: I have a matrix of size 360x501 where I want to check the value of each 5th column of each row and replace it (and the 6th, 7th, 8th column) by zero if the value is less than 1000. I have written a double loop to do that but that requires a lot of time. Is there a faster way to

Hello R users -- If I have a dataframe such as the following, named "frame" with the columns intended to be named col1 through col6, > frame col1 col2 cmlo3 col4 col5 col6 [1,] 3 10 2 6 5 7 [2,] 6 8 4 10 7 1 [3,] 7 5 1 3 1 8 [4,] 10 6 5 4 9 2 and I want to correct or otherwise change the

> myfit1 <- gls(col1 ~ col2+col3+col4+col5+col6-1, data=data2, corr=corAR1( 0.3202), method='ML') Error: cannot allocate vector of size 199712 Kb if I get rid of the "corr=corAR1(0.3202)" option, it works okay... can anybody help me? thanks a lot! [[alternative HTML version deleted]]

Hi: Can anyone advice me on how to loop and perform a calculation through all the columns. here's my data xd<- c(2.2024,2.4216,1.4672,1.4817,1.4957,1.4431,1.5676) pd<- c(0.017046,0.018504,0.012157,0.012253,0.012348,0.011997,0.012825) td<- c(160524,163565,143973,111956,89677,95269,81558) mydf<-data.frame(xd,pd,td) trans<-t(mydf) trans I have these values that I need to

Hi all, I'm making a PCA plot with eight variables (columns taken from a larger data frame "fieldTrial0809[idx,c(39:46)]"). I then want the symbols in the plot to be colored as a gradient from red to blue, depending on the value of another column in "fieldTrial0809[idx, c(48)]" containg temperatures from -12.1 to -5.4. I don't want to use the heat.colors(n)

Hello * i have to rename a lot of variables, and, given that they have regular name constructs, I would like to use regexps. Here's a dump of my head(names(df)) varnames <- c("id.quest", "txt.1.3", "col1.1.3", "col2.1.3", "col3.1.3", "col4.1.3", "col5.1.3", "txt.2.3", "col1.2.3",

Hi there, Any update on this? Should I create bugzilla ticket and submit patch? Regards Jan Gorecki On 20 December 2016 at 01:27, Jan Gorecki <J.Gorecki at wit.edu.pl> wrote: > Hello, > > colnames seems to be not optimized well for data.frame. It escapes > processing for data.frame in > > if (is.data.frame(x) && do.NULL) > return(names(x)) > > but

Hello, I have an input file: http://r.789695.n4.nabble.com/file/n3700031/testOut.txt testOut.txt where col 1 is chromosome, column2 is start of region, column 3 is end of region, column 4 and 5 is base position, column 6 is total reads, column 7 is methylation data, and column 8 is the strand. I would like a summary output file such as:

I am new to R, can anyone help with boxplot for a dataset like: file1 col1 col2 col3 col4 col5 050350005 101 56.625 48.318 RED 051010002 106 50.625 46.990 GREEN 051190007 25 65.875 74.545 BLUE 051191002 246 52.875 57.070 RED 220050004 55 70 80.274 BLUE 220150008 75 67.750 62.749 RED 220170001 77 65.750 54.307 GREEN file2 col1 col2 col3 col4 col5 050350005 101 56.625 57 RED 051010002 106 50.625 77

Hi, I'm still trying to figure out that GLM procedure in SAS. Let's start with the simple example: PROC GLM; MODEL col1 col3 col5 col7 col9 col11 col13 col15 col17 col19 col21 col23 =/nouni; repeated roi 6, ord 2/nom mean; TITLE 'ABDERUS lat ACC 300-500'; That's the same setup that I had in my last email. I have three factors: facSubj,facCond and facRoi. I had this pretty