# Python Array Declaration Hey, readers. Hope you all are doing well. In this article, we would be primarily focusing on Variants of Python Array Declaration.

## What is a Python Array?

As we all know, Python offers various data structures to manipulate and deal with the data values.

When it comes to ARRAY as a data structure, Python does not offer a direct way to create or work with arrays. Rather, it provides us with the below variants of Array:

• Python Array Module: The Array module contains various methods to create and work with the values.
• Python List: List can be considered as a dynamic array. Moreover, heterogeneous elements can be stored in Lists, unlike Arrays.
• Python NumPy Array: NumPy arrays are best suitable for mathematical operations to be performed on a huge amount of data.

Having understood about Python Array, let us now understand the ways through which we can declare an array in Python.

## Python Array Declaration – Variants of the Python Array

In the below section, we will understand the techniques through which we can declare an array using the variants of Python array.

### Type 1: Python Array module

`Python Array module `contains` array() function`, using which we can create an array in the python environment.

Syntax:

```array.array('format code',[data])
```
• `format_code`: It represents the type of elements to be accepted by an array. The code ‘i’ represents numeric values.

Example:

```import array
arr = array.array('i', [10,20,30,40,50])
print(arr)
```

Output:

```array('i', [10, 20, 30, 40, 50])
```

### Type 2: Python List as an Array

`Python list` can be used to dynamically create and store the elements like an array.

Syntax:

```list = [data]
```

Example:

```lst = [10,20,30,40, 'Python']
print(lst)
```

Output:

```[10, 20, 30, 40, 'Python']
```

As mentioned above, elements of various data types can be stored together in List.

### Type 3: Python NumPy array

`NumPy module` contains various functions to create and work with array as a data structure.

The `numpy.array() function` can be used to create single as well as multi-dimensional array in Python. It creates an array object as ‘ndarray’.

```np.array([data])
```

Example: Array creation using numpy.array() function

```import numpy
arr = numpy.array([10,20])
print(arr)
```

Output:

```[10 20]
```

Further, we can use `numpy.arange() function` to create an array within the specific range of data values.

```numpy.arange(start,stop,step)
```
• `start`: The starting element of the array.
• `end`: The last element of the array.
• `step`: The number of interval or steps between array elements.

Example:

```import numpy
arr = numpy.arange(1,10,2)
print(arr)
```

Output:

```[1 3 5 7 9]
```

## Conclusion

By this, we have come to the end of this topic. Feel free to comment below, in case you come across any question.