In this article, we will learn how to create a Numpy array filled with all zeros, given the shape and type of array.
We can use Numpy.zeros() method to do this task. This method takes three parameters, discussed below –
shape : integer or sequence of integers order : C_contiguous or F_contiguous C-contiguous order in memory(last index varies the fastest) C order means that operating row-rise on the array will be slightly quicker FORTRAN-contiguous order in memory (first index varies the fastest). F order means that column-wise operations will be faster. dtype : [optional, float(byDeafult)] Data type of returned array.
Matrix a : [0 0 0] Matrix b : [[0 0 0] [0 0 0] [0 0 0]]
Matrix c : [[ 0. 0. 0.] [ 0. 0. 0.] [ 0. 0. 0.] [ 0. 0. 0.] [ 0. 0. 0.]] Matrix d : [[ 0. 0.] [ 0. 0.] [ 0. 0.] [ 0. 0.] [ 0. 0.]]
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