This article aims to provide an overview of Python's data structures and algorithms. A data scientist must be familiar with this subject to construct and solve machine-learning models more successfully.
The built-in data structures and user-defined data structures will be demonstrated using real-world applications and last. But, not least, I'll expose you to specific algorithms, including traversal, sorting, and searching algorithms.
Built-in Data Structures:
As their name suggests, data structures enable us to organize, store efficiently and manage data for access and modification.
We will examine built-in data structures in this section. Python's four categories of built-in data structures are list,tuple, set, and dictionary.
A list contains data separated by commas and is defined using square brackets. The list is both ordered and changeable. It might include a variety of various data types.
An additional container is a tuple. It is a data type for elements in ordered, immutable sequences. Tuples are immutable because you cannot sort them or add or delete elements from them.
A set is a group of distinct, mutable elements that are not ordered. It can help us swiftly eliminate duplicates from a list.
For a detailed overview, check out the DSA online course by Learnbay.
User-Defined Data Structures:
Ques, Stack, and Tree are three user-defined data structures I will now introduce to you. I'm assuming you are familiar with the fundamentals of classes and functions.
A linear data structure called a stack has elements ordered in consecutive order. It operates on the last in, first out, or L.I.F.O principle. As a result, the piece added last will be deleted first. The activities are:
1. Pushing a component into the stack.
2. Remove a stack element using a pop command.
The conditions to check:
1. When we try to add one more element to a stack with its maximum number of items, the overflow condition results.
2. When we attempt to remove an element from an empty stack, the underflow condition results.
The queue is a linear data structure with sequentially arranged items. It adheres to the first in, first out (F.I.F.O.) principle. Consider going to the movies with your pals. As you can probably guess, the first person to receive the ticket is also the first to exit the queue. The queue's mechanism is the same.
Here are some characteristics of a queue.
1. Front indicates the first element.
2. Rear denotes the final component.
There are two procedures:
Enqueue means to add something to a queue. It will be completed in the back.
Dequeue means to remove anything from the queue. At the front, it will be completed.
There are two prerequisites:
Insertion into a full queue overflow, Deletion from an empty queue underflow.
Tree (general tree):
Hierarchy is defined using trees. The final nodes, which are referred to as child nodes, come after the root node.
Hope this article was informative enough. Feel free to check out theDSA course, to master other data structures and algorithms concepts.