similar to: dput/dget when a data frame has 2 rows (PR#9627)

Full_Name: David States Version: 2.6.0 OS: Windows XP64 Submission from: (NULL) (141.211.38.9) # The pair of commands # # dput(object, "file.dput") # object = dget("file.dput") # # should be a no op, but this is not working correctly for all objects. # # Simple example: # # make a simple object of class "hclust" cl = hclust(dist(matrix(nrow=4,ncol=4, c(1:16)))) #

I am seeking advice about dput() and dget(). We are using the ascii format supported by these functions as a way to write data from other programs that can be read into R easily. We are able to save complicated results (in the form of an R list) to a single file that can be read trivially into R or S-Plus. My question is whether that format can be considered a safe one for medium-term (say

Hi, I seem to be unable to get a mixed legend that has lines *or* polygons (not both). For example: ppi <- seq(0,2*pi,length.out=21)[-21] frame() plot.window(ylim=c(-5,5),xlim=c(-5,5),asp=1) polygon(cos(ppi)*4+rnorm(20,sd=.2),sin(ppi)*4+rnorm(20,sd=.2), col="green",border=FALSE) polygon(cos(ppi)*2+rnorm(20,sd=.1),sin(ppi)*2+rnorm(20,sd=.1), col="blue",border=FALSE)

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

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

I have a data frame. And I'd like to subset according to rownames. subset(mydataframe, rownames(mydataframe) == myrow, select = mycols) it turned out that "myrow" cannot be a vector. But I have multiple rows to pick. Is there a way to get around this problem?? Thank you for your help!! Lei Jiang Department of Chemsitry University of Washington Box 351700 Seattle, WA 98195

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,

Full_Name: Knut krueger Version: 2.1.1 OS: xp Home Submission from: (NULL) (149.225.134.34) In the png function the value res seems to be inactive: bmp(filename = "c:/r/Rplot%03d.bmp", width = 1920, height = 1920, pointsize = 48, bg = "white", res = 2400) result: witdh/heigth = 1920 <> 20.32 mm ppi=2400 Results as expected png(filename =

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 <-

Hello, I've noticed that dget() is much slower in the current and devel R versions than in previous versions. In 2.15 reading a 10000-row data.frame takes less than half a second: > (which.r <- R.Version()$version.string) [1] "R version 2.15.2 (2012-10-26)" > x <- data.frame(matrix(sample(letters, 100000, replace = TRUE), ncol = 10)) > dput(x, which.r) >

1- mixedorder does not work in a "do.call(mixedorder, mydataframe)" call like the order function does This is tangential, but do.call(order, mydataframe) is not safe to use in a general purpose function either - you need to remove the names from the second argument: > d <- data.frame(method=c("New","New","Old","Old","Old"),