similar to: summarizing a complex dataframe

Hi all, I'm handling massive data.frames and matrices in R (30000 x 400). In the 1st column, say, I have 0s and 1s indicating rows that matter; other columns have probability values. One simple task I would like to do would be to get the column mean values for signaled rows (the ones with 1) As a very fresh "programmer" I have build a simple function in R which should not be very

Due to missing data with some of my predictor variables I first do multiple imputation as follows: library(foreign) library(Amelia) library(norm) set.seed(666) M=10 impdat <-

Hi, I was checking the source code to the function combn that "generates all combinations of the elements of 'x' taken 'm' at a time.", because I wished to modify it. I have a doubt about a statement. This is the main loop. ._1 <- 1:1 nmmp1 <- n - m + ._1 while (a[1] != nmmp1) { if (e < n - h) { h <- ._1 e <-

I have data on ~340000 cases where it is desired to predict binary outcome, Withdrawn, using up to 8, A:H, predictors in a 3 x 2^7 design, but where the frequencies in these 168 cells vary enormously (1--108000). As well, there are two additional variables, Agency and Office, and it is desired, among other things, to determine if the rates vary with Agency and Office controlling for A - H. I fit

I have a very simple query with regard to summarizing the number of factors present in a certain snippet of a data frame. Given the following data frame: foo <- data.frame(yr = c(rep(1998,4), rep(1999,4), rep(2000,2)), div = factor(c(rep(NA,4),"A","B","C","D","A","C")), org = factor(c(1:4,1:4,1,2))) I want to get

Hi all, I have some data as follows. Cat1 Cat2 Cat3 COG Counts A B C COG1 10 B D COG2 20 C COG3 30 D COG4 40 I would like to sum all the counts for each category: A B C D 10 30 40 60 >CAT2COG<-

Hello, I have a question about working with dates in R. I would like to summarize a response variable based on a designated and irregular time period. The purpose of this is to compare the summarized values (which were sampled daily) to another variable that was sampled less frequently. Below is a trivial example where I would like to summarize the response variable dat$x such that I have average

Greetings, I am working in the sem package on a model with 3 exogenous variables (2 are nominal-categorical), and 4 endogenous, continuous variables. To use sem with the nominal variables, I created dummy variables. Now, in my sem output I have estimates for path coefficients for the relationship between each level of the nominal variables and the endogenous variables they are associated

Hi everyone, I looked around the list for a while but couldn't find a solution to my problem. I am storing some results to a simulation in a list and for each element i have two separate vectors(is that what they are called, correct my vocab if necessary). See below Version1_<-list() for(i in 1:5){ Version1_[[i]]<-list(First=rnorm(1),Second=rnorm(1)) } What I want is to put all

Hi Listers, Surely, I just have a mental block and there is a more elegant way of creating a summary count (other than extracing it from ftable). I''d like to create a new data.frame containing counts of spell by loc ie have three columns showing spell,loc,count. Below the data.frame... Any help appreciated Thanks Herry spell loc 101 Parts 1 102 Overall 2 105 Parts 1 106

I am trying to aggregate data in column 2 to identifiers in col 1 eg.. take this> identifier quantity 1 10 1 20 2 30 1 15 2 10 3 20 and make this> identifier quantity 1 45 2 40 3 20 Thanks in

Hi, I summary() a variable with 409908 numeric observations. The variable is part of a data.frame. The problem is that the min and max returned by summary() do not equal the ones returned by min() and max(). Does anybody know why that is? > min(data$vc) [1] 15452 > max(data$vc) [1] 316148 > summary(data$vc) Min. 1st Qu. Median Mean 3rd Qu. Max. 15450 21670 40980

I have a matrix containing -1, 0, 1, however certain rows will not have all 3 numbers. I have written some codes to compute the frequency table of how many -1s, 0s, 1s per row, but it is very ugly and not efficient if there are more than 3 numbers. Please suggest. m <- rbind(sample(0:1, replace=T, 10), sample(-1:1, replace=T, 10)) m.table <- t(apply(m, 1, function(x) c(sum(x==-1, na.rm=T),

I have a dataframe with several different treatment variables, and would like to calculate the mean and standard deviation of the replicates for each day and treatment variable. It seems like it should be easy, but I've only managed to do it for one treatment at a time using subset and tapply. Here is an example dataset: > `exampledata` <- structure(list(day = c(1L, 1L, 1L, 1L, 1L,

All, Is there an efficient way to apply say "mean" or "median" to a dataframe according to say all combinations of two variables in the dataframe? Below is a simple example and the outline of a "manual" solution that will work but is not very efficient (could also generalize this to a function). Searched the archives and docs but didn't see anything close to

Hi everyone, I'm sure this is simple, but I can't seem to figure this out. Situation. 3 different groups of subjects each submit n X n matrices of scores. What I want to do is aggregate each group of scores into a summary n X n matrix. I need the result to be a matrix so that I can calculate a dissimilarity structure on it. So I thought I would create a multi-dimensional array and

Hi, An example data set is: group level color A 1 "blue" A 1 "Red" B 1 "blue" B 2 "Red" A 2 "Red" B 2 "Red" B 2 "blue" B 2 "blue" A 2 "blue" A 2 "Red"

Dear R users, Let?s say I have 10 models, each named m1,m2,m3..., and I would like to summarize them automatically and simultaneously - e.g., to extract parameter estimates later on from all models; how can I do that? I have tried: x=1:10 #this creates some example data y=rnorm(10) m1=lm(x~y) m2=lm(x~1) sum.lms=function(x)summary(paste("m",x,sep="")) sum.lms(1:2) but

Hi, I want to check the status of a blind transfer (only sip endpoint) between various phones. Transfer is working perfectly, using ## from features.conf or using transfer key from phone, here SNOM320. My problem is that if party to transfer to is busy, the transfer fail and the call is ended. What I want to do is to return the call to the party who originate the transfer. I checked

in my view: <% if @main_singer_1 == @your_singer %> <% if @main_drummer_1 == @your_drummer %> i want to have this in a loop so i can change _1 How would I do this. I have some idea but I am not sure. [1..20].each do ..... and then replace _1 with each of the numbers or if someone can show the code to do this. number = "1" <% if