similar to: Efficient Cartesian product of data.frames

I'm confused, hope someone can point out what is not obvious to me. I thought I was creating a new data frame by 'deleting' rows from an existing dataframe - I've tried 2 methods. But this new data frame seems to remember values from its parent - even though there are no occurences. Where does it get the values versicolor and virginica from and give then a count of 0? What

Dear R-help, This is about randomForest's handling of NA and NaNs in test set data. Currently, if the test set data contains an NA or NaN then predict.randomForest will skip that row in the output. I would like to change that behavior to outputting an NA. Can this be done with flags to randomForest? If not can some sort of wrapper be built to put the NAs back in? thanks, Clayton

I require some help in debugging this code  library(neuralnet) ir<-read.table(file="iris_data.txt",header=TRUE,row.names=NULL) ir1 <- data.frame(ir[1:100,2:6]) ir2 <- data.frame(ifelse(ir1$Species=="setosa",1,ifelse(ir1$Species=="versicolor",0,""))) colnames(ir2)<-("Output") ir3 <- data.frame(rbind(ir1[1:4],ir2))

Hi all (I'm sure this question has been asked before, but I cant find it). If I have two character vectors: > x <- c("aaa","bbb","ccc") > y <- c("1","2","3") How can I get the cartesian product of the string values? > expand.grid(x,y) Gives me a data frame with separate columns...however, I cant seem to get *apply

Hi, I'm looking for a function that will take a list of columns or data.frame and corvert it to cartesian pairlist. For example for this data.frame (see below), I'd like to get a list of all possible pairs: > sound cs rs ns 7 5 2 4 5 4 6 3 1 8 4 1 6 4 2 6 7 1 2 2 5 9 2 5 how can I get this? > mylist ((cs,rs), (cs,ns), (rs,ns))

Hi all, I'm trying to plot this two curves in a single cartesian plane, but when I plot the first one, the plot appears with no negative "y" value. When I plot the second curve, it almost does not apear in the graph. I was trying the plot.window but with no success. Can someone help me with this? If possible, I'd like to plot this curves in a perfect cartesian plane. f =

Is there packaged code to convert geographical coordinates (e.g., longitude, latitude, elevation) to Cartesian coordinates in 3-space? I can see how to do this using 1. a spherical-to-Cartesian conversion like pracma::sph2cart(tpr) http://cran.r-project.org/web/packages/pracma/ 2. a geographical-to-spherical conversion. This seems to involve (in roughly increasing order of difficulty or

The following command produces red axis line in a pairs plot: pairs(iris[1:4], main = "Anderson's Iris Data -- 3 species", pch = "+", col = c("red", "green3", "blue")[unclass(iris$Species)]) Trying to fool pairs in the following way produces the same plot as above: pairs(iris[1:4], main = "Anderson's Iris Data -- 3

I have the following data from an image analysis program, in which the x and y co-ordinates are locations of the centroids of shapes on a 2 dimensional plot. The Y co-ordinates were positive, but I changed them to negative as the resulting scatterplot was upside down (the image analysis program reads from the top of the image to the bottom, so it seems) I now need these as point pattern data, as I

Hi list, not sure if this is the wanted behavior, but running the following code: > version platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 2 minor 1.1 year 2005 month 06 day 20 language R > n <- 500 > d <- 4 > m <- matrix(runif(n*d, -1, 1), ncol=d) > c <- hsv(apply(m, 1, function(x) {sum(x*x)/d}),

Hi list, not sure if this is the wanted behavior, but running the following code: > version platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 2 minor 1.1 year 2005 month 06 day 20 language R > n <- 500 > d <- 4 > m <- matrix(runif(n*d, -1, 1), ncol=d) > c <- hsv(apply(m, 1, function(x) {sum(x*x)/d}),

/src/main/attrib.c contains this comment in row_names_gets(): /* This should not happen, but if a careless user dput()s a data frame and sources the result, it will */ which svn blame says Prof Ripley placed there in r39830 with the commit message "correct the work of dput() on the row names of a data frame with compact representation." Is there a problem / better way to

Given a data set with a group factor, I want to translate the numeric variables to their centroid, by subtracting out the group means (adding back the grand means). The following gives what I want, but there must be an easier way using sweep or apply or some such. iris2 <- iris[,c(1,2,5)] means <- colMeans(iris2[,1:2]) pooled <- lm(cbind(Sepal.Length, Sepal.Width) ~ Species,

Hi, I'd like to make a pairwise comparison of a data.frame and I'm looking for a function that will take a list of columns or data.frame and corvert it to cartesian pairlist. For example for this data.frame (see below), I'd like to get a list of all possible pairs: > sound cs rs ns 7 5 2 4 5 4 6 3 1 8 4 1 6 4 2 6 7 1 2 2 5 9 2 5 how can I get

My routine (below) works OK but misbehaves if the on-screen plot is made wider using the mouse. The problem is caused by using par("usr")[1] - 0.07 * (par("usr")[2] - par("usr")[1]) to locate two items on the y-axis. The rest of the labeling is controlled by the "line=0" parameter setting. Of course resizing changes the absolute plot width, and

I try to perform a clustering using an existing dissimilarity matrix that I calculated using distance (analogue) I tried two different things. One of them worked and one not and I don`t understand why. Here the code: not working example library(cluster) library(analogue) iris2<-as.data.frame(iris) str(iris2) 'data.frame': 150 obs. of 5 variables: $ Sepal.Length: num 5.1 4.9 4.7

Hi all, I'd be grateful for your help. I am a new user struggling with a barplot issue. I am plotting categories (X axis) and their mean count (Y axies) with barplot(). The first call to barplot works fine. I remove records from the dataframe using final=[!final$varname == "some value",] I echo the dataframe and the records are no longer in the dataframe. When I call plot again

All: I am trying to fit a mixture of 2 normals with > 110 million observations. I am running R 2.5.1 on a box with 1gb RAM running 32-bit windows and I continue to run out of memory. Does anyone have any suggestions. Thanks so much, Tim [[alternative HTML version deleted]]

Hello! I'm a newcomer to R hoping to replace some convoluted database code with an R script. Unfortunately, I haven't been able to figure out how to implement the following logic. Essentially, we have a database of transactions that are coded with a geographic locale and a type. These are being loaded into a data.frame with named variables city, type, and price. E.g., trans$city

I have many very large dataframes with 20 columns each. In order to conserve memory, I wish to separate the data frame into 20 vectors, each named the name of the dataframe followed by .1,.2,.3 .20. (For example purposes, one data frame is named ?testa?.) e.g. testa.1, testa.2, testa.3 I have written the code to do this (see below). I am trying to convert this into a function that I can reuse.