similar to: Reading parameters from dataframe and loading as objects

When data contains both factor and numeric variables, how to get quartiles for all numeric variables? n <- 100 x1 <- runif(n) x2 <- runif(n) x3 <- x1 + x2 + runif(n)/10 x4 <- x1 + x2 + x3 + runif(n)/10 x5 <- factor(sample(c('a','b','c'),n,replace=TRUE)) x6 <- factor(1*(x5=='a' | x5=='c')) data1 <- cbind(x1,x2,x3,x4,x5,x6) data

Hi everyone, I have dataset which I make a sample of it couple of times and each time I get the mean and standard deviation of each row for each sample. I have a function for that, which takes the name of the file and number of times to sample and then returns the mean and standard deviation for each row in each sample. Sample=function(name, n){

Hi, Is there anybody having experience with MSWLogo on Wine ? I want to use it in school, but I have some problems. Thanks in advance Olivier

I have a data with the sequence of events with millions records and more than 24 time stamped variables. sample data: 1 2 3 4 5 6 7 8 9 10 A A A C C C B B D D D D D D D C C C C C B B A C A C C C D D I want to predict sequence for next 3 period. How this can be achieved using R. Is there any package/function in R do this. I have gone through the document for package "TraMineR" but not

Hi Experts, I am new to R, using following sample code for capping outliers using percentile information. Working on large data (30000 observations and 150 variables), loop I am using in the below mentioned code for detecting outliers and capping to upper /lower percentile value is taking much time for the execution. Is there anything wrong with code, can anyone suggest improvement in the script