similar to: subset on data frame

Hi, there. I have two matrix with identical dimentions. matrix A contains information of 0 and 1, and matrix B contains data. I only want the data in matrix B where matrix A has 1's. the places where matrix A has 0's, I want NA's in matrix B. How do I do that?? Thank you very much. Lei Jiang Department of Chemsitry University of Washington Box 351700 Seattle, WA 98195 Phone:

Hi, there. I am trying to read multiple files into R, but I got following message Error in file(file, "r"): All connections are in use. I clean up memory everytime I read in one file. Do i have to somehow release file connection everytime i read in one?? Thanks. Lei Department of Chemsitry University of Washington Box 351700 Seattle, WA 98195 Phone: 206-616-6882 Fax: 206-685-8665

I am completely new to R, but have some bg in cs and stat. since R has an interactive programming environment, I thought I could write my command in a file and run it in batch mode in the Rgui. but it didnt work. I checked the doc. it said Rcmd BATCH inputfile. it didnt work either. Can someone help? thank you. thank you. also if you can shed some light on passing command line arguements (like

I want to subset the dataframe based on certain values in a row. for each row in my dataframe if ANY one value of a particular set of columns satisfies cond append a logical value true at the end of the row else append a false at the end of the row in the end I want to be able to subset the whole data based on the appended true or false value. I could literally code like this, but I think

I'm having trouble using split on a very large data-set with ~1400 levels of the factor to be split. Unfortunately, I can't reproduce it with the simple self-contained example below. As you can see, splitting the artificial dataframe of size ~13MB results in a split dataframe of ~ 144MB, with an increase memory allocation of ~10 fold for the split object. If split scales linearly, then my

Listers, I have a question regarding correlation matrices. It is fairly straight forward to build a correlation matrix of an entire data frame. I simply use the command cor(MyDataFrame). However, what I would like to do is construct a smaller correlation matrix using just three of the variable out of my data set. When I run this: cor(MyDataFrame$variable1,

Hi guys, here is a list of names that I have: MyList: > myList<-list("A", "B","C","D") > myList [[1]] [1] "A" [[2]] [1] "B" [[3]] [1] "C" [[4]] [1] "D" I want to turn this list into a matrix of 1 row and 4 columns with those four components (A, B, C, D) so here is what I do: myDataFrame <-

Hi All, I'm looking for ways to compute aggregate statistics (with the aggregate function) but with an option for sorting and selecting a subset of the data frame. For example, I have would like to turn this : aggregate(myDataframe$TargetValue,list(SomeFactor = myDataframe$SomeFactor),mean) into something like aggregate(myDataframe$TargetValue,list(SomeFactor =

Hi! as my subject says I am struggling with the different of a two-way ANOVA and a (two-way) ANCOVA. I found the following examples from this webpage: http://www.statmethods.net/stats/anova.html # One Way Anova (Completely Randomized Design) fit <- aov(y ~ A, data=mydataframe) # Randomized Block Design (B is the blocking factor) fit <- aov(y ~ A + B, data=mydataframe) # Two Way

hello R-Users, I have this simple but not for me question: I do: > res<-dbSendQuery(con, "SELECT * FROM tabellaProva") > myDataFrame<-fetch(res) > myDataMatrix<-as.matrix(myDataFrame[,-1]) > namerows(myDataMatrix)<-as.character(myDataFrame[,1]) and I have: io tu io "0" "1" tu "1" "0" my problem is that the

I'm trying to bootstrap resample from a repeated measures dataset. I sample a vector of "ID"'s from my dataframe with replacement. Then I merge this back with my dataframe. I'm re-sampling subjects in the dataset rather than rows of the data. I thought I could use the left/right join features of the merge to select the records I want from the dataframe (mydataframe), like

This doesn't seem right; I'm using R version 2.4.1 (2006-12-18) on Mac OS and Win XP and find the same issue: > mydataframe <- data.frame(ppi=c(.5,.5),mmu=c(5,10)) > dput(mydataframe,"mydataframe.txt") > dget("mydataframe.txt") Error in attributes(.Data) <- c(attributes(.Data), attrib) : row names must be 'character' or 'integer', not

Hi All, I'm trying to use R2wd to send a dataframe to Word. The dataframe isn't huge - 300 rows, 12 variables, although it has some long strings in it. Using: wdTable(format(myDataFrame)) or wdTable(myDataFrame) Produces a very complex table, which Word struggles to process and layout. (I can't work out what the table is - it seems to be nested tables. Converting to text gives

Dear people, I am including an example of a dataframe: mydataframe<-data.frame(X=c(1:4),total_bill=c(16.99,10.34,21.01,23.68),tip=c(1.01,1.66,3.50,3.31),sex=c("Male","Male","Male","Female")) When I use the sapply function getting the information about the factors works: sapply(mydataframe,function(x)is.factor(x)) X total_bill tip

In a .Rnw file I want to insert the R command pairs(mydataframe) and achieve the following effects 1. the command itseld is echoed into the tex document generated by Sweave <<fig=TRUE,echo=TRUE>>= 2. The graphics generated appears in the tex document, with the graphics centred. 3. The R command > pairs(mydataframe) is not centered. Sweave-manual.pdf gives the following code chunk

Hi, I am working with R version 2.1.0, and I seem to have run into what looks like a bug. I get the same error message when I run R on Windows as well as when I run it on Linux. When I call anova to do a LR test from inside a function, I get an error. The same call works outside of a function. It appears to not find the right environment when called from inside a function. I have provided

Hi I am relatively new to R and am trying to figure out to plot 3d scatter plot using defined colors based on x-axis and y-axis values. Right now in the code below, I assign colors based on certain values in the names of the x-axis. Now if I want to extend the condition to assign a color based on the names of both x-axis and y-axis values, what should I be doing? Any help or ideas would be

Dear list, is it possible that method dispatch checks for superclasses/virtual classes before checking "ANY"? I'd like to build a generic initialization method for all my Reference Class (say "MyDataFrame") objects by having them inherit from class, say "MyRefClassVirtual" (which would have to be a virtual S4 class; there are no virtual Reference Classes,

Hello. I'm using as.ffdf(mydataframe) to create ffdf objects inside an lapply loop and returning that. I then use crbind to combine the lapply results into allData. So...simplified flow looks like this. res <- lapply(1:nchunks, function(n) { blah blah with nth chunk mydataframe <- data.frame(blah blah) dat <-

Hi, I was trying to make a density plot with 13 samples. To distinguish each sample, it would be good if each color is as different as possible from the other colors. I could use the built in function, but that does not do more than 8 colors and then goes back to recycling the cols. If I use a palette, then it is really difficult to distinguish between the colors. So, is there a way that I can