In Python, both arrays and lists are used for storing the data. Furthermore, slicing, indexing, and iteration are all possible with both data structures. So what is the main difference between Python list vs array?
We’ll go through when to utilize a Python array or Python list in-depth in this blog. Python provides a wide range of data structures, each with its own set of features and operations.
Lists, sets, tuples, and dictionaries are among the built-in data structures. This is not, unfortunately, a complete list of the data structures accessible in Python. Additional data structures from various modules or packages can easily load.
The “must-import” category includes array data structures. In order to utilize an array in Python, you must first import it from the NumPy package or the array module. This is the first difference between Python list vs array.
Let’s examine the properties and functions of lists and arrays before going deeper into the distinctions between these two data structures.
Python list vs array: Definitions
What is a List?
In the Python programming language, the list is the most essential data type. The list is also written in Python programming as a list of comma-separated values in a square bracket. The most significant advantage of the list is that its elements do not have to be of the same data type, and it has negative indexing.
Additionally, all string operations, including slicing and concatenation, can also be applicable to the Python list data types. It is also possible to make a nested list, and it contains another list.
What is an Array?
An array is a data structure that stores a certain number of elements of the same data type. To execute their algorithm, the majority of the data structures utilize an array. The array has two key components:
one is a substance: Each item in the array refers to an element, and the second is referred to as an index: Every element in the array has a unique numerical value that uses to identify it. These components allow shared memory locations that make data changes simple. The array module used to declare an array in Python.
Python list vs array: Main difference
Here are the main Python List and Python Array difference:
| List | Array |
| Can’t directly manage arithmetic operations | Can instantly manage arithmetic operations |
| Can include elements that also belong to various data types | Only include elements that also belong to the same data type |
| Can nest to include various types of elements | Must include all nested elements of the similar sizes |
| In the list, there is no need to explicitly import a module for declaration | But in the case of an array, there is the requirement of explicitly importing a module for the declaration. |
| The complete list can be printed without any direct looping | A loop has to be made to access the array components |
| Mainly Chosen for the more concise sequence of data items | Mainly Chosen for the more extended sequence of data items |
| Take more extensive memory for simple addition of elements | More compact in-memory size |
| Excellent flexibility enables easy data modifications like addition and deletion. | More nominal flexibility since addition, deletion done element-wise |
Python List vs Array: When to use Array or List?
As we’ve seen, arrays and lists play important roles in the Python programming language. But the main question is whether to use an array or a list. So, if you wish to keep a short sequence of elements without doing any numerical computations, you should use the list data structure.
This is because it allows you to keep an ordered, changeable (easily modified), and indexed sequence of objects without loading any explicit modules. Because an array data structure also allows for more optimal data storage of elements, it recommends that we utilize one when dealing with a long series of data.
In addition, if you want to execute mathematical operations on a group of components, you should utilize an array. It’s because of an array data structure that primarily also depends on data science and data analytics.
A Python list is also quicker than a Python array. Because a Python array is built on a Python list because when you build a Python list, an array of pointers containing the references of elements in the list produce somewhere in storage.
Let’s wrap it up!
As a result of the above research, we can conclude that both list and array have their own set of benefits and drawbacks. You also learned the distinction between Python array vs list, as well as a table of differences between the two. We can utilize them depending on the data that needs to save and the operations that need to do on the pieces that need to store. Hope it will help you to learn more about Python.
