The **numpy.zeros()** function in Python’s NumPy library creates an array filled with zeros. This function is particularly useful when we need to initialize an array with zeros before populating it with actual data. It’s commonly used in various numerical and scientific computing tasks. In this article, we will understand Python **numpy.zeros()** function, its syntax, and learn how to use it with the help of five unique examples. Let’s get started.

**Also Read: numpy.cbrt() in Python – Calculating Cube Roots in NumPy**

## Syntax of numpy.zeros() Function

Below is the syntax for using **numpy.zeros()** function in Python.

**Syntax:**

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

**Parameters:**

**shape:**A tuple specifying the dimensions (shape) of the output array. For example, for a 2D array, we would specify the shape as (rows, or columns).**dtype (optional):**The data type of the elements in the array. It’s typically floating, but we can specify other data types as well.**order (optional):**Specifies the memory layout of the array, either ‘C’ (row-major) or ‘F’ (column-major). The default is ‘C’.

**Return**: An array of zeros with the given shape, data type, and order.

## Examples of numpy.zeros() Function

Let us now look at some examples to demonstrate the use of **numpy.zeros()** function in Python. In each example, we have passed different parameter combinations to understand how this function works in different scenarios.

### Example 1: Creating a 1D array by specifying the shape

Here we will only provide rows in the** numpy.zeros()** function.

```
import numpy as np
np.zeros(5)
```

In the code above to use the **zeros()** function we first imported the **Numpy** library as **np** then we provided parameter **shape** as 5 in the **np.zeros()** function means we provided only row as the dimension of the output array.

**Output:**

In the output above, we got a 1D array filled with five zeros of data type float as the default data type is float.

### Example 2: Creating a 2D array by specifying the shape

Here we will provide both rows and columns in the** numpy.zeros()** function.

```
np.zeros((2,3))
```

In the code above we provided parameter **shape** as (2,3) in the **np.zeros()** function, which means we provided a tuple of integers that helps to create a 2D array of 2 rows and 3 columns.

**Output:**

In the output above, we got a 2D array filled with zeros of data type float as the default data type is float.

### Example 3: Creating a 1D array by specifying shape & dtype

Here we will provide **shape** and **dtype** in the** numpy.zeros()** function.

```
np.zeros(3,dtype="int")
```

In the code above within the** np.zeros()** function we have provided parameter **shape** as 3 and we have also provided **dtype** as **int** which means we have changed the data type of the element from float to** int**.

**Output:**

In the output above, we got a 1D array filled with zeros of data type Integer.

### Example 4: Creating a 2D array by specifying shape & dtype

Here we will do the same thing that we did in the last example but the only difference is we will specify tuple as a parameter for creating a 2D array.

```
np.zeros((4,5), dtype="int")
```

In the code above we provided parameter **shape** as (4,5) in the **np.zeros()** function to create a 2D array of 4 rows and 5 columns and we also have provided **dtype** as **int**.

**Output:**

In the output above, we got a 2D array filled with zeros of data type Integer.

### Example 5: Creating a 2D array by specifying shape & order

Here in the **numpy.zeros()** function we will provide **shape** which is the dimension of the output array and **order** which specifies the memory layout of the array.

```
np.zeros((3,4),order="F")
```

In the code above we provided **shape** as a tuple which is (3,4) which creates a 2D array filled with zeros of 3 rows and 4 columns and we also provided **order** as **F** to store data in column-major order in the memory which is by default **C** means row-major.

**Output:**

## Summary

In this tutorial, we have discussed** numpy.zeros()** function provided by Python’s NumPy library and also explored five examples to create an array filled with zeros using **numpy.zeros()** function with examples. After reading this tutorial, we hope you can easily create an array filled with zeros in Python.

## Reference

https://stackoverflow.com/questions/69847064/python-for-structure-based-array