subset

This question already has an answer here: Subset data frame based on number of rows per group 2 answers I have a data frame df, and I am trying to subset all rows that have a value in column B occur more than once in the dataset. I tried using table to do it, but am having trouble subsetting from the table: t<-table(df$B) Then I try subsetting it using: subset(df, table(df$B)>1) And I get the error "Error in x[subset & !is.na(subset)] : object of type 'closure' is not subsettable" How can I subset my data frame using table counts? Here is a dplyr solution (using mrFlick's data.frame) library

This question already has an answer here: duplicates in multiple columns 2 answers I would like to delete duplicate rows based in two collumns, instead just one. My input df : RAW.PVAL GR allrl Bak 0.05 fr EN1 B12 0.05 fg EN1 B11 0.45 fr EN2 B10 0.35 fg EN2 B066 My output: RAW.PVAL GR allrl Bak 0.05 fr EN1 B12 0.45 fg EN2 B10 0.35 fg EN2 B066 I had tried df<- subset(df, !duplicated(allrl, RAW.PVAL)) , but I do not work to delete rows with this two columns simultaneously duplicated. Thank you! If you want to use subset , you could try: subset(df, !duplicated(subset(df, select=c(allrl, RAW.PVAL)

I have a data frame with an ID column and a few columns for values. I would like to only keep certain rows of the data frame based on whether or not the value of ID at that row matches another set of values (for instance, called "keep"). For simplicity, here is an example: df <- data.frame(ID = sample(rep(letters, each=3)), value = rnorm(n=26*3)) keep <- c("a", "d", "r", "x") How can I create a new data frame consisting of rows that only have IDs that match those of keep? I can do this for just one letter by using the which() function, but with multiple letters I get warning messages and

I have a data.frame with start and end time: ranges<- data.frame(start = c(65.72000,65.72187, 65.94312,73.75625,89.61625),stop = c(79.72187,79.72375,79.94312,87.75625,104.94062)) > ranges start stop 1 65.72000 79.72187 2 65.72187 79.72375 3 65.94312 79.94312 4 73.75625 87.75625 5 89.61625 104.94062 In this example, the ranges in row 2 and 3 are entirely within the range between 'start' on row 1 and stop on row 4. Thus, the overlapping ranges 1-4 should be collapsed to one range: > ranges start stop 1 65.72000 87.75625 5 89.61625 104.94062 I tried this: mdat <- outer(ranges$start, ranges$stop,

I'm looking for an efficient way to select rows from a data table such that I have one representative row for each unique value in a particular column. Let me propose a simple example: require(data.table) y = c('a','b','c','d','e','f','g','h') x = sample(2:10,8,replace = TRUE) z = rep(y,x) dt = as.data.table( z ) my objective is to subset data table dt by sampling one row for each letter a-h in column z. OP provided only a single column in the example. Assuming that there are multiple columns in the original dataset, we group by 'z', sample 1 row from the sequence of rows per group, get the

I have a set of values and would like to create list of all subsets containing 2 elements. For example, a source set ([1,2,3]) has the following 2-element subsets: set([1,2]), set([1,3]), set([2,3]) Is there a way to do this in python? Seems like you want itertools.combinations : >>> list(itertools.combinations((1, 2, 3), 2)) [(1, 2), (1, 3), (2, 3)] If you want sets you'll have to convert them explicitly. If you don't mind an iterable instead of a list, and you're using Python 3, you can use map : >>> s = set((1, 2, 3)) >>> map(set, itertools.combinations(s, 2)) <map object at 0x10cdc26d8> To

I was hoping to be able to construct a do.call formula for subsetting without having to identify the actual range of every dimension in the input array. The problem I'm running into is that I can't figure out how to mimic the direct function x[,,1:n,] , where no entry in the other dimensions means "grab all elements." Here's some sample code, which fails. So far as I can tell, either [ or do.call replaces my NULL list values with 1 for the index. x<-array(1:6,c(2,3)) dimlist<-vector('list', length(dim(x))) shortdim<-2 dimlist[[shortdim]] <- 1: (dim(x)[shortdim] -1) flipped <- do.call(`[`,c