numpy.zeros() in Python
The numpy.zeros() function returns a new array of given shape and type, with zeros.
Syntax:
numpy.zeros(shape, dtype = None, order = 'C')
Parameters :
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.
Returns :
ndarray of zeros having given shape, order and datatype.
Code 1 :
# Python Program illustrating# numpy.zeros method import numpy as geek b = geek.zeros(2, dtype = int)print("Matrix b : \n", b) a = geek.zeros([2, 2], dtype = int)print("\nMatrix a : \n", a) c = geek.zeros([3, 3])print("\nMatrix c : \n", c) |
Output :
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
# Python Program illustrating# numpy.zeros method import numpy as geek # manipulation with data-typesb = geek.zeros((2,), dtype=[('x', 'float'), ('y', 'int')])print(b) |
Output :
[(0.0, 0) (0.0, 0)]
Reference :
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.zeros.html#numpy.zeros
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.
Last Updated on October 29, 2021 by admin