I want to create different methods for a class called Multiset. I have all the required methods, but I’m unsure of how to write intersection, union, and subset methods. For intersection and union, my code starts like this: def intersect(var) x = Multiset.new end Here is an example: X = [1, 1, 2, 4] Y … Read more
A categorical variable V1 in a data frame D1 can have values represented by the letters from A to Z. I want to create a subset D2, which excludes some values, say, B, N and T. Basically, I want a command which is the opposite of %in% D2 = subset(D1, V1 %in% c(“B”, “N”, “T”)) … Read more
I have a large data set and I would like to read specific columns or drop all the others. data <- read.dta(“file.dta”) I select the columns that I’m not interested in: var.out <- names(data)[!names(data) %in% c(“iden”, “name”, “x_serv”, “m_serv”)] and than I’d like to do something like: for(i in 1:length(var.out)) { paste(“data$”, var.out[i], sep=””) <- … Read more
When I need to filter a data.frame, i.e., extract rows that meet certain conditions, I prefer to use the subset function: subset(airquality, Month == 8 & Temp > 90) Rather than the [ function: airquality[airquality$Month == 8 & airquality$Temp > 90, ] There are two main reasons for my preference: I find the code reads … Read more
