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numpy.zeros() in Python
  • Difficulty Level : Medium
  • Last Updated : 23 Oct, 2020

The numpy.zeros() function returns a new array of given shape and type, with zeros.

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-types
b = geek.zeros((2,), dtype=[('x', 'float'), ('y', 'int')])

Output :

[(0.0, 0) (0.0, 0)]

Reference :
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.

This article is contributed by Mohit Gupta_OMG πŸ˜€. If you like GeeksforGeeks and would like to contribute, you can also write an article using or mail your article to See your article appearing on the GeeksforGeeks main page and help other Geeks.

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