# Convert a list and tuple into NumPy arrays: Python Numpy tutorials 2

**Convert a list and tuple into NumPy arrays**: NumPy is a widely used Python library that provides efficient and convenient tools for working with arrays and matrices. One of its key features is the ability to convert lists and tuples into arrays, which makes it easier to work with these data structures. In this article, we’ll show you how to use NumPy to convert a list and a tuple into arrays and explain the process in detail.

**Converting a List to a NumPy Array**

To convert a list to a NumPy array, we first need to import the NumPy library:

import numpy as np

Next, we can create a list of numbers:

my_list = [1, 2, 3, 4, 5]

To convert this list into a NumPy array, we can use the **np.array()** function:

my_array = np.array(my_list)

This will create a NumPy array from the list. We can print the array to verify that it has been created correctly:

print(my_array)

This will output the following:

[1 2 3 4 5]

**Converting a Tuple to a NumPy Array**

To convert a tuple to a NumPy array, we can follow a similar process. First, we need to import the NumPy library:

import numpy as np

Next, we can create a tuple of numbers:

my_tuple = (1, 2, 3, 4, 5)

To convert this tuple into a NumPy array, we can use the **np.array()** function:

my_array = np.array(my_tuple)

This will create a NumPy array from the tuple. We can print the array to verify that it has been created correctly:

print(my_array)

This will output the following:

[1 2 3 4 5]

**Explanation**

In both cases, we used the** np.array()** function to convert a list or a tuple into a NumPy array. This function takes a single argument, which can be any iterable object (such as a list or a tuple). The function then creates a NumPy array from the input data.

When we printed the NumPy arrays, we noticed that they were printed without any commas or other separators between the numbers. This is because NumPy arrays are treated as a single object, rather than a collection of individual elements. This is one of the key advantages of NumPy arrays – they are much more efficient to work with than standard Python lists or tuples.

**Conclusion**

In this article, we showed you how to use NumPy to convert a list and a tuple into arrays. We also explained the process in detail, and highlighted some of the key features of NumPy arrays. We hope this article has been helpful in getting you started with NumPy!