# numpy.zeros() in Python

Filed Under: NumPy Python numpy.zeros() function returns a new array of given shape and type, where the element’s value as 0.

## numpy.zeros() function arguments

The numpy.zeros() function syntax is:

``````
zeros(shape, dtype=None, order='C')
``````
• The shape is an int or tuple of ints to define the size of the array.
• The dtype is an optional parameter with default value as float. It’s used to specify the data type of the array, for example, int.
• The order defines the whether to store multi-dimensional array in row-major (C-style) or column-major (Fortran-style) order in memory.

## Python numpy.zeros() Examples

Let’s look at some examples of creating arrays using the numpy zeros() function.

### 1. Creating one-dimensional array with zeros

``````
import numpy as np

array_1d = np.zeros(3)
print(array_1d)
``````

Output:

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

Notice that the elements are having the default data type as the float. That’s why the zeros are 0.

### 2. Creating Multi-dimensional array

``````
import numpy as np

array_2d = np.zeros((2, 3))
print(array_2d)
``````

Output:

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

### 3. NumPy zeros array with int data type

``````
import numpy as np

array_2d_int = np.zeros((2, 3), dtype=int)
print(array_2d_int)
``````

Output:

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

### 4. NumPy Array with Tuple Data Type and Zeroes

We can specify the array elements as a tuple and specify their data types too.

``````
import numpy as np

array_mix_type = np.zeros((2, 2), dtype=[('x', 'int'), ('y', 'float')])
print(array_mix_type)
print(array_mix_type.dtype)
``````

Output:

``````
[[(0, 0.) (0, 0.)]
[(0, 0.) (0, 0.)]]
[('x', '<i8'), ('y', '<f8')]
`````` numpy.zeros() in Python

Reference: API Doc

1. het gala says: