subset

I want to select rows by name in a data frame that is a subset of a larger one. The subsetted data frame appears to have retained the names of the original data frame, such that: > DFsubset[1:3,] x1 x2 x3 271 3 5 2 553 2 4 1 563 2 5 3 while using the printed row name returns the following: > DFsubset[271,] Error in xj[i, , drop = FALSE] : subscript out of bounds How can I select these rows based on the row names from the original DF, ie. 271, 553, 563? You need to reference the rownames of your data.frame: dfsub[rownames(dfsub) == 271,] #where dfsub is your subsetted data.frame EDIT: as

I have a dataset of 2500 rows which are all bank loans. Each bank loan has an outstanding amount and collateral type. (Real estate, Machine tools.. etc) I need to draw a random selection out of this dataset where for example the sum of outstanding amount = 2.5Million +-5% and maximum 25% loans with the same asset class. I found the function optim, but this asks for a function and looks to be constructed for optimization a portfolio of stocks, which is much more complex. I would say that there is an easy way of achieving this? I created a sample data set which could illustrate my question

I wrote a wrapper around ftable because I need to compute flat tables with frequency and percentage for many variables: mytable <- function(...) { tab <- ftable(..., exclude = NULL) prop <- prop.table(x = tab, margin = 2) * 100 bind <- cbind(as.matrix(x = tab), as.matrix(x = prop)) margin <- addmargins(A = bind, margin = 1) round(x = margin, digits = 1) } mytable(formula = wool + tension ~ breaks, data = warpbreaks) A_L A_M A_H B_L B_M B_H A_L A_M A_H B_L B_M B_H 10 0 0 1 0 0 0 0.0 0.0 11.1 0.0 0.0 0.0 12 0 1 0 0 0 0 0.0 11.1 0.0 0.0 0.0 0.0 13 0 0 0 0 0 1 0.0 0.0 0.0 0.0 0.0 11.1 14 0 0 0 1 0

I have an array of n integers (not necessarily distinct!) and I would like to iterate over all subsets of size k. However I'd like to exclude all duplicate subsets. e.g. array = {1,2,2,3,3,3,3}, n = 7, k = 2 then the subsets I want to iterate over (each once) are: {1,2},{1,3},{2,2},{2,3},{3,3} What is an efficient algorithm for doing this? Is a recursive approach the most efficient/elegant? In case you have a language-specific answer, I'm using C++. The same (or almost the same) algorithm which is used to generated combinations of a set of unique values in lexicographical order can be used to

I would like to know if there is a simple way to achieve what I describe below using ddply . My data frame describes an experiment with two conditions. Participants had to select between options A and B , and we recorded how long they took to decide, and whether their responses were accurate or not. I use ddply to create averages by condition. The column nAccurate summarizes the number of accurate responses in each condition. I also want to know how much time they took to decide and express it in the column RT . However, I want to calculate average response times only when participants got the

I saw the code below from java tutorial oracle. In order to count the number of words between doorbell (inclusive) and pickle (inclusive), the author added \0 after the word pickle . I understand that the effect of adding \0 after pickle , is that the word pickle is now included as part of the subset. But my question is, why use \0 ? Could someone please help me out? Thanks in advance for any help! SortedSet<String> dictionary = new TreeSet<>(entire collection of words from a dictionary); int count = dictionary.subSet("doorbell", "pickle\0").size(); System.out.println(count); Edit: Also, what

I want to subtract y from x, which means remove one "A", three "B" and one "E" from x, so xNew will be c("A", "C", "A","B","D") . It also means length(xNew)=length(x) - length(y) x <- c("A","A","C","A","B","B","B","B","D","E") y <- c("A","B","B","B","E") setdiff doesn't work because xNew <- setdiff(x,y) xNew [1] "C" "D" match also doesn't work xNew <- x[-match(y,x)] xNew [1] "A" "C" "A" "B" "B" "B" "D" It removes "B" on the fifth position 3 times, so there are still three "B" left. Is anyone know how to do this, is there a function available in R or we should write a private function? Thanks a

Normally I wonder where mysterious errors come from but now my question is where a mysterious lack of error comes from. Let numbers <- c(1, 2, 3) frame <- as.data.frame(numbers) If I type subset(numbers, ) (so I want to take some subset but forget to specify the subset-argument of the subset function) then R reminds me (as it should): Error in subset.default(numbers, ) : argument "subset" is missing, with no default However when I type subset(frame,) (so the same thing with a data.frame instead of a vector), it doesn't give an error but instead just returns the (full) dataframe. What is going