The NumPy zeros() function is used to return a new array of specified shape and data type, filled with zeros.

### Syntax

```numpy.zeros(shape, dtype=float, order='C')
```

### Parameters

 `shape` `Required. `Specify shape of the returned array in form of int or tuple of ints. `dtype` `Optional. `Specify the desired data-type for the array. Default: float `order` `Optional. `Specify whether to store multi-dimensional data in row-major (C-style) or column-major (Fortran-style) order in memory. Two possible values are: C (C-style) and F (Fortran-style). Default: 'C'

### Return Value

Returns an array (ndarray) of zeros with the given shape, dtype, and order.

### Example: Create 2-D array of zeros

In the below example, zeros() function is used to create a 2 dimensional array of zeros of specified shape.

```import numpy as np
Arr = np.zeros((2,3))
print(Arr)
```

The output of the above code will be:

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

### Example: zeros() function with dtype parameter

The zeros() function can be used with dtype parameter to provide the data type of the elements of the array. In the below example, data type of the returned array is complex.

```import numpy as np
Arr = np.zeros((2,2), dtype=complex)
print(Arr)
```

The output of the above code will be:

```[[ 0.+0.j  0.+0.j]
[ 0.+0.j  0.+0.j]]
```