 # Create Numpy Array Filled With All Zeros | python

We can use the Numpy.zeros () method to accomplish this task. This method takes three parameters, which are 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. `

Example # 1:

 ` # Python program to create an array with all zeros ` ` import ` ` numpy as geek `   ` a ` ` = ` ` geek.zeros (` ` 3 ` `, dtype ` ` = ` ` int ` `) ` ` print ` ` (` ` "Matrix a:" ` `, a) `   ` b ` ` = ` ` geek.zeros ([ ` ` 3 ` `, ` ` 3 ], dtype = int ) ```` print ( "Matrix b : " , b)  ```

Exit:

``` Matrix a: [0 0 0] Matrix b: [[0 0 0] [0 0 0] [0 0 0]]    Example # 2:            ` # Python program to create an array with all zeros `   ` import ` ` numpy as geek `     ` c ` ` = ` ` geek.zeros ([` ` 5 ` `, ` ` 3 ` ` ]) `   print  ` (` ` "Matrix c:" ` ` , c) `     ` d ` ` = ` ` geek.zeros ([` ` 5 ` `, ` ` 2 ` `], dtype ` ` = ` ` float ` `) `  ` print ` ` (` ` "Matrix d:" ` `, d) `         Exit:  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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