numpy.zeros_like() in Python

Numpy.zeros_like() in Python The zeros_like() method of Python numpy class returna an array of zeros with the same shape and type as that of specified array. Syntax

numpy.zeros_like(a, dtype=None, order='K', subok=True)

Parameter The numpy.zeros_like() method consists of four parameters, which are as follows: arrray : This parameter represents an array_like input subok  :It true is invoked then it represents  newly created array will be sub-class of array else it represents  a base-class array order  :The order parameter can be either C_contiguous or F_contiguous. C order means that operating row-rise on the array will be slightly quicker FORTRAN-contiguous order in memory (the first index varies the fastest). F order means that column-wise operations will be faster. dtype :It is an optional parameter. It depicts the data type of returned array, and by default, it is a float. Return This method returns an array of zeros having given shape, order and datatype. Example 1

# Python Programming giving an example for
# numpy.zeros_like method
importnumpy as numpy
array = numpy.arange(8).reshape(4, 2)
print("Original array : \n", array)
obj1 = numpy.zeros_like(array, float)
print("\nMatrix : \n", obj1)
array = numpy.arange(7)
obj2 = numpy.zeros_like(array)
print("\nMatrix : \n", obj1)

Output Original array :

[[0 1]
 [2 3]
 [4 5]
[6 7]]

Matrix :

 [[ 0.  0.]
[ 0.  0.]
[ 0.  0.]
[ 0.  0.]]

Matrix :

[[ 0.  0.]
[ 0.  0.]
[ 0.  0.]
[ 0.  0.]]