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# NumPy | zeros method

NumPy
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schedule Jul 1, 2022
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Numpy's `zeros(~)` method creates a Numpy array with all zeros as its entries.

# Parameters

1. `shape` | `int` or `array-like`

The desired shape of the Numpy array. Providing an `int` would return a one-dimensional flattened array.

2. `dtype`link | `string` or `type` | `optional`

The desired data type for the Numpy array. By default, `dtype=numpy.float64`. If you're sure that the new Numpy array will only contain integers, you should want to specify `dtype=int`.

# Return value

A Numpy array of zeroes, with the shape and type specified by the parameters.

# Examples

## Creating an one-dimensional Numpy array

To create a flattened Numpy array with 3 zeros:

``` np.zeros(3) array([0., 0., 0.]) ```

## Creating a Numpy array of type int

To create a flattened Numpy array with 3 zeroes of type `int`:

``` np.zeros(3, int) array([0, 0, 0]) ```

## Creating a two-dimensional Numpy array

### Using a tuple

To create a 2 by 3 (i.e. 2 rows and 3 columns) matrix filled with zeros using a tuple:

``` np.zeros((2,3)) array([[0., 0., 0.],       [0., 0., 0.]]) ```

### Using an array

To create a 2 by 3 (i.e. 2 rows and 3 columns) matrix filled with zeros using an array:

``` np.zeros([2,3]) array([[0., 0., 0.],       [0., 0., 0.]]) ```

Note that you could also use Numpy arrays as well.