# np.zeros() – Create Numpy Arrays of zeros (0s)

In this article, we will discuss how to create 1D or 2D numpy arrays filled with zeros (0s).

## numpy.zeros()

Python’s Numpy module provides a function to create a numpy array of given shape & type and filled with 0’s i.e,

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

Arguments:

• shape: Shape of the numpy array. Single integer or sequence of integers.
• dtype: (Optional) Data type of elements. Default is float64.
• order: (Optional) Order in which data is stored in multi-dimension array i.e. in row major(‘F’) or column major (‘C’). Default is ‘C’.

Returns:

• It returns a numpy array of given shape but filled with zeros.

Let’s understand with some examples but first we need to import the numpy module,

`import numpy as np`

## Create 1D Numpy Array of given length and filled with zeros

Suppose we want to create a numpy array of five zeros (0s). For that we need to call the numpy.zeros() function with argument 5 i.e.

`np.zeros(5)`

It returns a 1D numpy array with five 0s,

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

We can assign the array returned by zeros() to a variable and print its type to confirm if it is a numpy array or not,

```arr = np.zeros(5)
print(arr)
print(type(arr))```

Output:

```[0. 0. 0. 0. 0.]
<class 'numpy.ndarray'>```

## Create Numpy array of zeros of integer data type

By default numpy.zeros() returns a numpy array of float zeros. But if we want to create a numpy array of zeros as integers, then we can pass the data type too in the zeros() function. For example,

```arr = np.zeros(5, dtype=np.int64)
print(arr)```

Output:

`[0 0 0 0 0]`

It returned a numpy array of zeros as integers because we pass the datatype as np.int64.

## Create two dimensional (2D) Numpy Array of zeros

To create a multidimensional numpy array filled with zeros, we can pass a sequence of integers as the argument in zeros() function. For example, to create a 2D numpy array or matrix of 4 rows and 5 columns filled with zeros, pass (4, 5) as argument in the zeros function.

```arr_2d = np.zeros( (4, 5) , dtype=np.int64)
print(arr_2d)```

Output:

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

It returned a matrix or 2D Numpy Array of 4 rows and 5 columns filled with 0s.

## Create 3D Numpy Array filled with zeros

To create a 3D Numpy array filled with zeros, pass the dimensions as the argument in zeros() function. For example,

```arr_3d = np.zeros( (2, 4, 5) , dtype=np.int64)
print(arr_3d)```

Output:

```[[[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]]]```

It created a 3D Numpy array of shape (2, 4, 5).

Summary:

In this article we learned how to create 1D or 2D numpy array of given shape and filled with zeros.

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