![]() ![]() To explicitly have 0 columns, you need to write. Each vector will represent a DataFrame column, and the length of. The default for matrix is to have 1 column. For sum of rows 1 you could try something like: numrows <- 5 numcols <- 5 randomuniformmatrix <- matrix (runif (numrows numcols), nrow numrows, ncol numcols) randomuniformmatrixnormalised <- randomuniformmatrix / rowSums (randomuniformmatrix) randomuniformmatrixnormalised ,1 ,2 ,3 ,4. Its most basic syntax is as follows: df <- ame (vector1, vector2) We can pass as many vectors as we want to this function. ![]() If you might have zero or NA value in the matrix, row(distances) (or col(distances)) will not: is.na(row(distances)) + 0LĪnd one can force the entire matrix to be NA values, as a way to produce a matrix of 1's, then subtract 1: is. 5 Answers Sorted by: 110 You have several options integer (3) numeric (3) rep (0, 3) rep (0L, 3) Share Follow answered at 7:43 Thierry 18k 5 47 66 10 I'd add also seq (0,0,length.out3) or as. To create a DataFrame in R from one or more vectors of the same length, we use the ame () function. The arguments to this matrix () are the set of elements in the vector. Or just (!distances) + 0L # if you don"t have zeroes in your matrix To create a matrix in R you need to use the function called matrix (). R initialize motrix matrixc selects all elements of the first row.I hope you find this helpful and not more confusing, but here's one way to get to your end goal of populating the checkerboard structs.matrixc selects all elements of the first column.matrixc results in a R slice matrix with the data on the rows 1, 2, 3 and columns 2, 3. You could convert your matrix to a logical matrix in a various ways and then add zeros, for example: is.na(distances) + 0L # if you don't have `NA` values in your matrix ![]() You could create a whole new matrix using the dimensions of your old matrix matrix(0L, nrow = dim(distances), ncol = dim(distances)) # similarly, to save a few keystrokes (because a matrix is a special case of two dimensional array) array(0L, dim(distances)) # you could preserve the structure of your old matrix using and fill it with zeroes distances <- 0L # you could simply multiply all the values by zero distances*0L # more general solution would be which will take in count NA cases too (because every number in power of zero is always equals to 1) distances^0L - 1L # some of my stuff: Obj] <- some_func( inp_vec reminds us that the default for 'mode' is logical and that R has a fairly rich set of automatic coercion methods, although I find his suggestion vector(,10) to be less clear than would be logical(10) which is its equivalent.I'll just put it here as there are bunch of nice answers in the comments After initializing the matrix, we can simply use as.ame to convert the matrix into a data frame and that’s it. Technically, lists are "vectors" in R, so this is a recommended (even necessary) practice for constructing lists with for-loops: obj <- list( length(inp_vec) ) There are many ways to initialize a data frame in R but initializing with matrix is the best among them because creating the data frame with matrix help us to avoid entering the wrong number of columns and the wrong number of rows. It's good that you ask because pre-allocating long vectors before for-loops that will be assigning results to long objects are made more efficient by not needing to successively lengthen vectors. matrix in R is a two-dimensional rectangular data set and thus it can be created using vector input to the matrix function.
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