search for: franciscororolaio

Hello, I have a dataset with 40 variables, some of them are always 0 (each row). I would like to make a subset containing only the columns which values are not all 0, but I don't know how to do it. I tried: for(cut_column in 1:40) { if(sum(dataset[,cut_column])!=0) { columns_useful<-c(columns_useful,dataset[cut_column]) } } sorted_dataset<-subset(dataset,

Hello, I have to write a big sentence with cat() and I would like that R automatically adds a new line when it is needed (when the text arrives at the end of the window), the same as Windows Notepad does (Word Wrap). How could I do? Thank you F.

Hello, I have a csv file with many variables, both characters and integers. I would like to load it on R and do some operations on integer variables, the problem is that R loads the entire dataset considering all variables as characters, instead I would like that R makes the distinction between the two types, because there are too many variables to do: x1<-as.integer(x1)

Hello, I need to analyse some data coming from a questionnaire which have for each item a likert scale 1-5. I need to find the lowest scores in the distribution, and for this purpose I thought to use the quantile() function to identify the participants belonging to the 5% with lowest scores (who have a score < than quantile, am I right?). The problem is: which type of quantile should I

Hello, I would like to make a function which extracts a subset, from a dataset, with only the columns that I want (specifying their names). For example, having this matrix: > mydata<-matrix(c(22,1,3,2001,24,5,7,2002,26,7,8,2002,28,5,7,2003), byrow=TRUE, ncol=4, dimnames=list(c(1,2,3,4), c("age","day","month","year"))) > mydata age day