The numpy.zeros() function returns a new array of given shape and type, with zeros.
numpy.zeros(shape, dtype = None, order = 'C')
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.
ndarray of zeros having given shape, order and datatype.
Code 1 :
Matrix b : [0 0] Matrix a : [[0 0] [0 0]] Matrix c : [[ 0. 0. 0.] [ 0. 0. 0.] [ 0. 0. 0.]]
Code 2 : Manipulating data types
[(0.0, 0) (0.0, 0)]
Note : zeros, unlike zeros and empty, does not set the array values to zero or random values respectively.Also, these codes won’t run on online-ID. Please run them on your systems to explore the working.
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