# 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

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

 `# Python Program illustrating``# numpy.zeros method` `import` `numpy as geek` `# manipulation with data-types``b ``=` `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 wonâ€™t run on online IDE’s. Please run them on your systems to explore the working.

Previous
Next