B.5 Size information, reshaping/replicating & cleaning
The following statements are used to provide information on the dimensions of matrices or the number of observations or variables in a dataset, to reshape or replicate matrices, and to drop rows or columns with missing data from a matrix or dataset.
Syntax  Arguments and performed function 
S = size(X);  S is a $2\phantom{\rule{0.3em}{0ex}}\times \phantom{\rule{0.3em}{0ex}}1$ matrix of integers. The ﬁrst entry of S is the number of rows of X and the second entry is the number of columns of X.

p = rows(X);  p is a $1\phantom{\rule{0.3em}{0ex}}\times \phantom{\rule{0.3em}{0ex}}1$ matrix equal to the number of rows of X.

p = cols(X);  p is a $1\phantom{\rule{0.3em}{0ex}}\times \phantom{\rule{0.3em}{0ex}}1$ matrix equal to the number of columns of X.

W = kron(X, Y);  W is a matrix obtained as the Kronecker product of X, and Y.

W = repmat(X, M, N);  W is a matrix obtained by replicating X, M times along the row dimension and N times along the column dimension.

W = reshape(X, M, N);  W isan M$\times $N matrix constructed by reading the entries of X, in a columnmajor order.

W = dropmissing(X);  W is a matrix constructed by reading the entries of X, row by row, but skipping any rows in X that contain at least one missing value. An error is produced if an empty matrix results from dropping the rows of X with missing values.
When the argument provided to dropmissing() is a dataset, then the function returns a dataset. Therefore, this function is also documented in Section B.13. see also dropif and keepif 