# numpy.zeros() in Python | np.zeros() in Python

Numpy `zeros()` is also known as np.zeros or numpy.zeros. It is used to create a Numpy array whose each element has a value of zero. Using `array()` function, you can also create Numpy array whose each element is having a value of zero. Then why do we need to use `zeros()` function? Let's understand it with the help of a simple example:

Suppose, you want to create a Numpy array having 3 rows and 15 columns, and each element's value is zero. With `array()` function, you can do it like this:

```import numpy as np

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

As you can see this way of creating an array is a messy task and at the same time, it is error-prone. With zeros() function, this task can be achieved very easily. Let's look at it how:

`np.zeros(shape=(3, 15), dtype=int)`

As you can see how simple it is to create array with zeros() function.

Finally, lets take a look at the syntax of numpy `zeros()` function

```np.zeros(shape, dtype=None)
OR
numpy.zeros(shape, dtype=None)```

`shape` parameter is used to specify the dimensions of the Numpy array. Here, you specify the value in the form of tuple or list.

`dtype` is used to specify the data type of array and this parameter is optional.

## How to use Numpy zeros function?

Let's create a one-dimensional array with zeros() function.

```import numpy as np

a = np.zeros(6)
print(a)```

Output of the above program

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

Python program to create numpy zeros array with the specified data type

```import numpy as np

a = np.zeros(6, dtype=int)
print(a)```

Output of the above program

`[0 0 0 0 0 0]`

Python program to create numpy zeros array with the specific dimension or shape

```import numpy as np

a = np.zeros(shape=(2, 6), dtype=int)
print(a)
b = np.zeros((2, 6), dtype=int)
print(b)
c = np.zeros([2, 6], dtype=int)
print(c)```

Output of the above program

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

As you can see there are three different ways of specifying shape to Numpy zeros() function.