similar to: splitting matrices

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 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

Dear R users, I??ve got a simple question but somehow I can??t find the solution: I have a data frame with columns 1-5 containing one set of integer values, and columns 6-10 containing another set of integer values. Columns 6-10 contain NA??s at some places. I now want to calculate (1) the number of values in each row of columns 6-10 that were NA??s (2) the sum of all values on columns 1-5

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

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

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

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

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,

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

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 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 <-

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

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

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

I have a dataset of 3 ?columns? and 5 ?rows?. temp<-data.frame(col1=c(5,10,14,56,7),col2=c(4,2,8,3,34),col3=c(28,4,52,34,67)) I wish to convert this to a single ?column?, with column 1 on ?top? and column 3 on ?bottom?. i.e. 5 10 14 56 7 4 2 8 3 34 28 4 52 34 67 Are there any functions that do this, and that will work well on much larger datasets (e.g. 1000 rows, 6000 columns)?

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]]

Dear R commnuity, Thanks a lot for your help. I want to read in tables, the problem is that the table is composed in a difficult way. In ariginal it looks like this: 669 736 842101610481029114711811166124312081128117611221026 9581024 992 685 720 829 925 995 96010241057116611501104106410711092 983 908 989 904 924 896 882 897 909 933 928 907 916 902 546 734 784 868 970 954

Hi, I have a table with column name like col1, col2, col3, col4 ... col10. In rails, after I get the instance of the class, I would like to use a for loop to retrieve values from these columns and put them into a hash. The hash will be used for another find call. Is that possible? Thanks. Arnold -- Posted via http://www.ruby-forum.com/.

Hi all, I have a matrix with 10000 rows and 10 columns. The last columns contains another identifiers but the values are not uniques so that I want to generate another matrix with rows with unique values in the last column. If I did tmp<-unique(my_mat$col10) this will give me 8560 unique entries so the ideal matrix will be 8560X10 columns now then. I tried sub_mat<-my_mat[tmp,] but