similar to: Create a data frame of all possible unique combinations of factors

Hi there, I have a vector and would like to create a data frame, which contains all unique combination of two elements, regardless of order. myVec <- c(1,2,3) what expand.grid does: 1,1 1,2 1,3 2,1 2,2 2,3 3,1 3,2 3,3 what I would like to have 1,1 1,2 1,3 2,2 2,3 3,3 Can anybody help?

Hi, I used to use reshape and moved to reshape2 (R 2.15.1). Now I tried some of my older scripts and was surprised that my cast function wasn't working like before. What I did/want to do: 1) Melt a dataframe based on a vector specifying column names as measure.vars. Thats working so far: dfm <- melt(df, measure.vars=n, variable_name = "species", na.rm = FALSE) 2) Recast the

Ein eingebundener Text mit undefiniertem Zeichensatz wurde abgetrennt. Name: nicht verf?gbar URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20120422/bb638d28/attachment.pl>

I am calculating the mean of each column grouped by the variable 'id'. I do this using aggregate, data.table, and plyr. My aggregate results do not match the other two, and I am trying to figure out what is incorrect with my syntax. Any suggestions? Thanks. Here is the data. myData <- structure(list(var1 = c(31.59, 32.21, 31.78, 31.34, 31.61, 31.61, 30.59, 30.84, 30.98, 30.79, 30.79,

Is there a way to apply a function, say cor(), to each combination of some number of variables, and this, without using loops? For example, I have day, hour, var1 and var2. How could I compute cor(var1,var2) for each day*hour combination and obtain a matrix with day, hour and the cor value for each combination? Thanks for your time, Marc =================== Marc Bélisle Professeur adjoint

Hello everyone, I am looking at the joint spatial distribution of 2 kinds of organisms (estimated on a grid of points) and want to test for significant association or dissociation. My first question is: do you know a nice technique to do that, considering that I have a limited number of points (36) but that they are repeated (4 times)? I did GLMs to test for correlations between the

Dear R-users, I would like to add a legend at the bottom of pairs plots (it's my first use of this function). With the plot function, I usually add some additional space at the bottom when I define the size of the graphical device (using mar); grid functions then allows me to draw my legend as I want. Unfortunatley, this technique does not seem to work with the pairs function as the

Let say, I have a matrix with 8 rows and 6 columns:  >  df1  <- matrix(NA, 8, 4)  > df1       [,1] [,2] [,3] [,4]  [1,]   NA   NA   NA   NA  [2,]   NA   NA   NA   NA  [3,]   NA   NA   NA   NA  [4,]   NA   NA   NA   NA  [5,]   NA   NA   NA   NA  [6,]   NA   NA   NA   NA  [7,]   NA   NA   NA   NA  [8,]   NA   NA   NA   NA  Now I want to get **all possible** ways to fetch 6 cells at a

Hello! # I have 3 vectors of values: values1<-rnorm(10) values2<-rnorm(10) values3<-rnorm(10) # In real life, all 3 vectors have a length of 25 # I create all possible combinations of 4 based on 10 elements: mycombos<-expand.grid(1:10,1:10,1:10,1:10) dim(mycombos) # Removing rows that contain pairs of identical values in any 2 of these columns: mycombos<-mycombos[!(mycombos$Var1

Dear all, How should I add several variables to a data frame without losing the attributes of the df? Consider the following: > require(Hmisc) > Xa <- iris > label(Xa, self=T) <- "Some df label" > str(Xa) 'data.frame': 150 obs. of 5 variables: $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ... $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9

Hey All, So, I am confused how exactly to use nesting loop functions in R to spit out data frames. I've managed to create a working function for my data set that generates a data frame for a given set of Year i and Location j; but how would I do it for all Years and Locations? Here is my working function: test<-function(i,j){ a<-x[which(x$Year==i & x$Location==j),]

Dear all, i try to plot with ggplot2. Therefor I have an matrix with 3 colums. With cbind I add an additional column called "col". I need this column "col" because in a later step and want to specify here some plot details which I will get from another analysis If I want to plot with this code, I have the problem that the legend is wrong. Blue changed to green and green to

I have my data in a table table <- table(test2$Filename, test2$PREDICT) I need to convert this table so it keeps the same structure, but is a different format. The current output is count data by Filename and I want to get the max for each Filename. Columns are: Filename, 1, 2, 3, 4, 5, 6, 7 When I try to convert it to a data.frame it reverts to Var1(Filename), Var2(1:7), Freq. My end goal

Hi, I am trying to simultaneously remove duplicate variables from two or more variables in a small R data.frame. I am trying to reproduce the SAS statements from a Proc Sort with Nodupkey for those familiar with SAS. Here's my example data : test <- read.csv("test.csv", sep=",", as.is=TRUE) > test date var1 var2 num1 num2 1 28/01/11 a 1 213 71 2

Gracias a los tres, Raúl, Marcelino y Carlos. Lo del "get" de Marcelino me da la respuesta a lo que yo exactamente preguntaba, y funciona, pero ahora tengo problemas con el for, por lo que probablemente recurra al eval parse de Raúl o Carlos, que ya tienen el for. Aún así, lo intento 1º con el get. Con subset(df, subset=get(GT[i])>0) el problema es que en el for hago un

Dear all, I am using expand.grid for calculating all the possible values between four pairs. I would like to ask you if it is possible to filter the result out, so to keep all unique pairs. In my algorithm the input c(1,2) produces the same results as the c(2,1) so for example in the following code below > expand.grid(c(1,2,3),c(1,2,3))   Var1 Var2 1    1    1 2    2    1 3    3    1 4   

Hi, I am trying to generate all unordered combinations of a set of numbers / characters, and I can only find a (very) clumsy way of doing this using expand.grid. For example, all unordered combinations of the numbers 0, 1, 2 are: 0, 0, 0 0, 0, 1 0, 0, 2 0, 1, 1 0, 1, 2 0, 2, 2 1, 1, 1 1, 1, 2 1, 2, 2 2, 2, 2 (I have not included, for example, 1, 0, 0, since it is equivalent to 0, 0, 1). I have

Muy buenas. Quiero hacer un loop en el que en cada iteración se hace un subset con el que se queda con las muestras para la que cierta variable es positiva. Si hago esto, sale bien: df2<-subset(df, subset = var1>0) Pero he probado así (y de no sé cuantas formas más), antes de hacer el for, y no sale: GT<- c("var1","var2", ? ) df2<-subset(df,

Dear List, Several times I use this package I get the error message shown below. When I work out simple examples, it turns out to be fine, but when working with real and moderate size data sets I always get the same error. Do you know what could be the cause of the problem? Error in apply(mod.matrix[, components], 1, prod) : subscript out of bounds Error in

Hi folks, I have a dataframe df.vars with the follwing structure: var1 var2 var3 group Group is a factor. Now I want to standardize the vars 1-3 (actually - there are many more) by class, so I define z.mean.sd <- function(data){ return.values <- (data - mean(data)) / (sd(data)) return(return.values) } now I can call for each var z.var1 <- by(df.vars$var1, group,