Profile
Settings
Refer your friends
Sign out
Introduction
Python provides many functions and features through its extensive data structures, including dictionaries, tuples, sets, and Lists. Lists are the most efficient and easiest-to-use data structure for Python. Both the List and Array are used in Python to store data and can be used for indexing and iteration. Python, on the other hand, doesn’t have built-in support for Array.
To use the Array module, we need to either import it from the NumPy package or import it manually. This is the primary difference between Array and List. Let’s first briefly introduce both data structures before we get into the details.
What is Array in Python?
An Array can also be a linear data structure which can store data. It can also be ordered, enclosed, and mutable in square brackets. It can also store uncommon items. However, there are limitations to the storage of various types of data. We need to import a NumPy or an Array module to use the Array in Python.
What is a List?
The List is the most important data type within the Python language. The List in Python language is the list of separated values within a square bracket. The best thing about the List is that its elements don’t need to be the same data type as the negative indexing. All string operations are applied to the List data type, such as concatenation, slicing, etc. We can also create nested Lists, i.e. Lists that contain another list.
What is the Difference Between List and Array?
| Point of Difference | Array | Lists |
| Mathematical Operations | If you want to do numerical operations, Arrays are great: Arrays can be helpful for mathematical operations | Lists cannot handle numerical operations. You’ll get an error if you attempt numeric operations with a List. |
| Data Type Storage | Arrays can only store elements of one data type. Arrays can store homogeneous values. | List can also store elements from different data types. List can store heterogeneous values. |
| Replaceability | Only a few cases can replace a Python List with the Array data structure. | Only a few cases can replace a Python List with the Array data structure. |
| Importing Module | The Array, however, is not part of the Python data structure. Before creating or using Arrays, you will need to import the “Array” module. | The in-built data structure of Python language is List. Therefore, no module or package should be imported before it can be used. |
| Modification Capabilities | Array cannot resize or modify memory locations very well | It’s possible to modify and resize the Lists very quickly and efficiently |
| Numerical Operation | Array gives you an advantage when performing mathematical operations in Python. The NumPy module allows us to store data values in an Array structure and allow us to manipulate them easily. | Although the List can perform the mathematical operations, they are not as efficient as the Array. |
- For frequent deletion and insertion, the List is more efficient than arrays. However, Arrays are better and suitable for regular access to elements.
- Arrays can compactly store large amounts of data and are, therefore, more efficient. Arrays are excellent for numerical operations, but the List can’t directly handle maths operations.
- The objects in the Python table are mutable. This allows us to add or remove items from the List at any time without specifying their size.
This blog explained the differences between Python Lists and Python Arrays. You learnt how they differ and which one to opt for an item’s sequence. Now, you can put your understanding into practice.
