Data structures and algorithms in python

What are the Important Data Structures and Algorithms in Python?

Last updated on 04th Nov 2022, Artciles, Blog

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Nirvi (Python developer )

Nirvi is a Python developer with 7+ years of experience in the Hadoop ecosystem, Sqoop, Hive, Spark, Scala, HBase, MapReduce, and NoSQL databases, such as HBase, Cassandra, and MongoDB. She spends most of her time researching technology and startups.

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    • In this article you will learn:
    • 1.Important Data Structures in Python.
    • 2.Algorithm.
    • 3.Conclusion.

Important Data Structures in Python:

Lists:

Python Lists are the ordered collections of a data just like arrays in the other programming languages. It allows a various types of elements in the list. The implementation of a Python List is similar to Vectors in C++ or ArrayList in JAVA. The costly operation is an inserting or deleting the element from a beginning of the List as all elements are needed to be shifted. An Insertion and deletion at end of the list can also become costly in case where a preallocated memory becomes full.

Example: Creating Python List

Python3

  • List = [1, 2, 3, “GFG”, 2.3]
  • print(List)

List elements can be accessed by a assigned index. In a python starting index of the list, a sequence is 0 and an ending index is (if N elements are there) N-1.

Tuple:

  • Python tuples are similar to the lists but Tuples are immutable in nature i.e. once created it cannot be a modified. Just like List, a Tuple can also contain elements of different types.
  • In a Python, tuples are created by a placing a sequence of values separated by ‘comma’ with or without use of a parentheses for grouping of the data sequence.
  • To create tuple of one element there must be trailing comma. For example, (8,) will create tuple containing 8 as a element.
Data Structures in Python

Set:

  • Python set is the mutable collection of data that does not allow the any duplication. Sets are basically used to include the membership testing and eliminating a duplicate entries. The data structure used in this Hashing, a famous technique to perform insertion, deletion, and traversal in O(1) on a average.
  • If a Multiple values are present at a same index position, then value is appended to that index position, to form Linked List. In, CPython Sets are implemented using dictionary with a dummy variables, where key beings members set with greater optimizations to time complexity.

Frozen Sets:

Frozen sets in a Python are immutable objects that are only support methods and operators that produce result without affecting a frozen set or sets to which they are be applied. While elements of set can be modified at a any time, elements of the frozen set remain a same after creation.

String:

  • Python Strings is an immutable array of a bytes representing Unicode characters. Python does not have character data type, a single character is simply a string with the length of 1.
  • As strings are be immutable, modifying a string will result in a creating new copy.

Dictionary:

Python dictionary is the unordered collection of data that saves data in a format of key:value pair. It is like hash tables in the any other language with a time complexity of O(1). Indexing of a Python Dictionary is done with help of keys. These are of any hashable type i.e. an object whose can never change like a strings, numbers, tuples, etc. Can create a dictionary by using a curly braces ({}) or dictionary comprehension.

Matrix:

A matrix is the 2D array where each element is of a strictly the same size. To create matrix will be using a NumPy package.

Bytearray:

Python Bytearray gives the mutable sequence of an integers in range 0 <= x < 256.

Linked List:

A linked list is the linear data structure in which an elements are not stored at a contiguous memory locations. The elements in a linked list are linked using a pointers A linked list is be represented by a pointer to first node of the linked list. The first node is called head. If linked list is empty, then value of the head is a NULL. Every node in the list consists of at least two parts:

  • Data.
  • Pointer (Or Reference) to the next node.
Data Structures and Algorithms in Python

Linked List Traversal:

In a previous program, have created a simple linked list with the three nodes. Let us traverse a created list and print the data of every node. For traversal, let us write general-purpose function of printList() that prints any given list.

Stack:

A stack is the linear data structure that stores items in the Last-In/First-Out (LIFO) or First-In/Last-Out (FILO) manner. In a stack, a new element is added at a one end and an element is removed from that end only. The insert and delete operations are be often called a push and pop.

Queue:

As a stack, a queue is a linear data structure that saves an items in a First In First Out (FIFO) manner. With queue, the least recently added item is a removed first. A good example of a queue is any queue of the consumers for a resource where a consumer that came first is served first.

Binary Tree:

The topmost node of a tree is called the root whereas bottommost nodes or the nodes with the no children are called the leaf nodes. The nodes that are be directly under a node are called its a children and the nodes that are directly above something are called its be a parent.A binary tree is the tree whose elements can have almost a two children. Since every element in a binary tree can have only a 2 children, typically name them a left and right children. A Binary Tree node contains a following parts.

  • Data.
  • Pointer to left child.
  • Pointer to the right child.

Algorithm:

Algorithm Inorder(tree):

  • Traverse a left subtree i.e. call Inorder(left-subtree).
  • Visit a root.
  • Traverse a right subtree i.e. call Inorder(right-subtree).

Algorithm Preorder(tree):

  • Visit a root.
  • Traversea left subtree i.e. call Preorder(left-subtree).
  • Traverse a right subtree i.e. call Preorder(right-subtree).

Algorithm Postorder(tree):

  • Traverse a left subtree i.e. call Postorder(left-subtree).
  • Traverse a right subtree i.e. call Postorder(right-subtree).
  • Visit a root.

Conclusion:

Data structures deal with how a data is organised and held in memory, when a program processes it. It is an important to note that, the data that is saved in a disk as part of persistent storages (like relational tables) are not referred as a data structure here.An Algorithm is step by step set of an instruction to process the data for a particular purpose. So, an algorithm utilises a different data structures in a logical way to solve the specific computing problem.

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