similar to: How to force aggregate to exclude NA ?

Hi all, This is my first post to the developers list. As I understand it, aggregate() currently repeats a function across cells in a dataframe but is only able to handle functions with single value returns. Aggregate() also lacks the ability to retain the names given to the returned value. I've created an agg() function (pasted below) that is apparently backwards compatible (i.e.

Hi, everyone, I have a data.frame named "eva" like this: IND PARTNO VC1 EO1 EO2 EO3 EO4 EO5 114 114001 2 5 4 4 5 4 114 114001 2 4 4 4 4 4 114 114001 2 4 NA NA NA NA 112 112002 2 3 3 6 2 6 112 112002 2 1 1 3 4 4 112 112003 2 6 6 6 5 6 112 112003 2 5 7 6 6 6 112 112003 2 6 6 6 4 5 114 114004 2

I tried aggregate, apply etc, but can't get the right result. For example, m <- cbind(c(LETTERS[1:5]), c("aa", "bb", "cc", "aa", "cc")) [,1] [,2][1,] "A" "aa"[2,] "B" "bb"[3,] "C" "cc"[4,] "D" "aa"[5,] "E" "cc" how to obtain

For example, strings <- c("aaaa", "bbbb","ccba"). How to get "aaaa", "bbbb" that do not contain "ba" ? _________________________________________________________________ [[alternative HTML version deleted]]

For example, c("dog.is.an.animal", "cat.is.an.animal", "rat.is.an.animal"). How can I identify the common prefix is ".is.an.animal" and delete it to give c("dog", "cat", "rat") ? Thanks _________________________________________________________________ [[alternative HTML version deleted]]

Any better solution than this ? sum(strsplit("TCGGGGGACAATCGGTAACCCGTCT", "")[[1]] == "G") _________________________________________________________________ [[alternative HTML version deleted]]

Hi, I am casting a dataframe from long to wide format. The same codes that works for a smaller dataframe would take a long time (more than two hours and still running) for a longer dataframe of 2495227 rows and ten different predictors. How to make it more efficient ? wer <- data.frame(Name=c(1:5, 4:5), Type=c(letters[1:5], letters[4:5]), Predictor=c("A", "A",

Hi, How do I collapse (average in the simplest case) the values of those duplicated ids (i.e., 2, 5, 6, 9) to give a table of unique ids ? t <- cbind(id=c(1:10, 2,5,6,9), value=rnorm(14)) _________________________________________________________________ [[alternative HTML version deleted]]

I am generating a report containing several R scripts in the appendix. Is there any way to "beautify" the R source codes in microsoft word, similar to what we see in tinn-R ? Thanks _________________________________________________________________ [[alternative HTML version deleted]]

I am trying to use the aggregate function to run a function, catsbydat2, that produces the mean, minimum, maximum, and number of observations of the values in a dataframe, inJan2Test, by levels of the dataframe variable MyDay. The output should be in the form of a dataframe. #my code: # This function should process a data frame and return a data frame # containing the mean, minimum, maximum, and

Dear all, I am including in a plot 6 different lines (?lines) with 6 different line types. The problem is that I have so dense information that the line types are not visible any more.   In the code below myLength<-length(currentSet) plot(seq(from=1,to=myMax,length.out=myLength),currentSet, type="l",xlim=c(1,myMax),axes=F,...) the myLength is 100.000+ elements. I would like to ask

I have a folder full of pngs and jpgs, and would like to consolidate them into a pdf with appropriate title and labels. Can this be done via R ? _________________________________________________________________ Easily publish your photos to your Spaces with Photo Gallery. [[alternative HTML version deleted]]

I'm having difficulty finding a solution to my problem that without using a for loop. For the amount of data I (will) have, the for loop will probably be too slow. I tried searching around before posting and couldn't find anything, hopefully it's not embarrassingly easy. Consider the data.frame, Data, below Data Sub Tr IA FixInx FixTime p1 t1 1 1 200 p1 t1 2

Dear all, I have a function that predicts DV based on one predictor pred: pred<-c(0,3000000,7800000,15600000,23400000,131200000) DV<-c(0,500,1000,1400,1700,1900) ## I define Function 1 that computes the predicted value based on pred values and parameters a and b: calc_DV_pred <- function(a,b) { DV_pred <- rep(0,(length(pred))) for(i in 1:length(DV_pred)){ DV_pred[i] <- a *

I am fairly new to R and would like help with the problem below. I am trying to sum and count several rows in the data frame yy below. All works well as in example 1. When I try to add the columns, with an NA in Q21, I get as NA as mySum. I would like NA to be treated as O, or igored. I wrote a function to try to count an NA element as 0, Example 3 function. It works with a few warnings,

Hi, I have developed some scripts that basically ask for input tab-limited format files, do some processing, and output several pictures or csv. Now I need to have some gui to wrap on top of the scripts, so that end-users can select their input files, adjust some parameters for processing, and select output folder or filenames. Please advice me if there is any tools or project suitable for

*Hola!!! resulta que tengo unos datos de divisas ordenados por fechas (días) los que he convertido a formato tipo YYYY-MM-DD donde DD siempre es 01:* * * * EUR.resto$date<-as.Date(EUR.resto$date) EUR.resto$mo <- substr(EUR.resto$date,6,7) EUR.resto$yr <- substr(EUR.resto$date, 1,4)

Hi, I am using aggregate() to add up groups of data according to year and month. It seems that the function aggregate() automatically sorts the levels of factors of the grouping elements, even if the order of the levels of factors is supplied. I am wondering if this is a bug, or if I missed something important. Below is an example that shows what I mean. Does anyone know if this is just the way

Hi, I am trying to aggregate the sum of my test data.frame as follow: testDF <- data.frame(v1 = c("a", "a", "a", "a", "a", "b", "b", "b", "b", "b", "c", "c", "c", "c", "c", "d", "d", "d", "d",

Given a dataframe m > m X Y V3 V4 1 1 A 0.5 1.2 2 1 B 0.2 1.4 3 2 A 0.1 0.9 How do I convert m to this with V4 as the cell values ? A B 1 1.2 1.4 2 0.9 NA