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𝐋𝐢𝐬𝐭𝐬: - Lists are ordered collections of items. - They are mutable, meaning you can change their content after creation. - You can have duplicate values in a list. - Lists are defined using square brackets [ ]. Example: my_list = [1, 2, 3, 'apple', 'banana', 'cherry'] 𝐓𝐮𝐩𝐥𝐞𝐬: - Tuples are ordered collections of items, similar to lists. - However, they are immutable, meaning once created, their content cannot be changed. - Tuples are defined using parentheses ( ). - You can have duplicate values in a tuple. Example: my_tuple = (1, 2, 3, 'apple', 'banana', 'cherry') 𝐃𝐢𝐜𝐭𝐢𝐨𝐧𝐚𝐫𝐢𝐞𝐬: - Dictionaries are unordered collections of items that are stored as key-value pairs. - They are mutable. - Dictionaries are defined using curly braces { }. - Each key in a dictionary must be unique, but the values can be duplicated. Example: my_dict = {'name': 'John', 'age': 30, 'city': 'New York'} I have curated the best interview resources to crack Python Interviews 👇👇 https://topmate.io/coding/898340 Hope you'll like it Like this post if you need more resources like this 👍❤️

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Useful Cheatsheets for Programmers 👇👇 Data Science Cheatsheet https://github.com/aaronwangy/Data-Science-Cheatsheet SQL Cheatsheet https://learnsql.com/blog/sql-basics-cheat-sheet/ https://t.me/programming_guide/299 https://www.sqltutorial.org/wp-content/uploads/2016/04/SQL-cheat-sheet.pdf https://t.me/learndataanalysis/442?single Java Programming Cheatsheet https://introcs.cs.princeton.edu/java/11cheatsheet/ PHP and Ruby Cheatsheets https://t.me/programming_guide/300 https://t.me/programming_guide/301 Pandas in 5 minutes https://bit.ly/3EZgNgF Python Cheat sheet https://t.me/pythondevelopersindia/314 UML Cheat sheet https://www.guru99.com/uml-cheatsheet-reference-guide.html. GIT and Machine Learning Cheatsheet https://t.me/datasciencefun/714?single Javascript Cheat sheet https://t.me/programming_guide/623 HTML Cheatsheet https://web.stanford.edu/group/csp/cs21/htmlcheatsheet.pdf ENJOY LEARNING 👍👍

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30-days learning plan to master Data Structures and Algorithms (DSA) and prepare for coding interviews. ### Week 1: Foundations and Basic Data Structures Day 1-3: Arrays and Strings - Topics to Cover: - Array basics, operations (insertion, deletion, searching) - String manipulation - Two-pointer technique, sliding window technique - Practice Problems: - Two Sum - Maximum Subarray - Reverse a String - Longest Substring Without Repeating Characters Day 4-5: Linked Lists - Topics to Cover: - Singly linked list, doubly linked list, circular linked list - Common operations (insertion, deletion, reversal) - Practice Problems: - Reverse a Linked List - Merge Two Sorted Lists - Remove Nth Node From End of List Day 6-7: Stacks and Queues - Topics to Cover: - Stack operations (push, pop, top) - Queue operations (enqueue, dequeue) - Applications (expression evaluation, backtracking, breadth-first search) - Practice Problems: - Valid Parentheses - Implement Stack using Queues - Implement Queue using Stacks ### Week 2: Advanced Data Structures Day 8-10: Trees - Topics to Cover: - Binary Trees, Binary Search Trees (BST) - Tree traversal (preorder, inorder, postorder, level order) - Practice Problems: - Invert Binary Tree - Validate Binary Search Tree - Serialize and Deserialize Binary Tree Day 11-13: Heaps and Priority Queues - Topics to Cover: - Binary heap (min-heap, max-heap) - Heap operations (insert, delete, extract-min/max) - Applications (heap sort, priority queues) - Practice Problems: - Kth Largest Element in an Array - Top K Frequent Elements - Find Median from Data Stream Day 14: Hash Tables - Topics to Cover: - Hashing concept, hash functions, collision resolution (chaining, open addressing) - Applications (caching, counting frequencies) - Practice Problems: - Two Sum (using hash map) - Group Anagrams - Subarray Sum Equals K ### Week 3: Algorithms Day 15-17: Sorting and Searching Algorithms - Topics to Cover: - Sorting algorithms (quick sort, merge sort, bubble sort, insertion sort) - Searching algorithms (binary search, linear search) - Practice Problems: - Merge Intervals - Search in Rotated Sorted Array - Sort Colors - Find Peak Element Day 18-20: Recursion and Backtracking - Topics to Cover: - Basic recursion, tail recursion - Backtracking (N-Queens, Sudoku solver) - Practice Problems: - Permutations - Combination Sum - Subsets - Word Search Day 21: Divide and Conquer - Topics to Cover: - Basic concept, merge sort, quick sort, binary search - Practice Problems: - Median of Two Sorted Arrays - Pow(x, n) - Kth Largest Element in an Array (using divide and conquer) - Maximum Subarray (using divide and conquer) ### Week 4: Graphs and Dynamic Programming Day 22-24: Graphs - Topics to Cover: - Graph representations (adjacency list, adjacency matrix) - Traversal algorithms (DFS, BFS) - Shortest path algorithms (Dijkstra's, Bellman-Ford) - Practice Problems: - Number of Islands Day 25-27: Dynamic Programming - Topics to Cover: - Basic concept, memoization, tabulation - Common problems (knapsack, longest common subsequence) - Practice Problems: - Longest Increasing Subsequence - Maximum Product Subarray Day 28: Advanced Topics and Miscellaneous - Topics to Cover: - Bit manipulation - Greedy algorithms - Miscellaneous problems (trie, segment tree, disjoint set) - Practice Problems: - Single Number - Decode Ways - Minimum Spanning Tree ### Week 5: Review and Mock Interviews Day 29: Review and Weakness Analysis - Activities:   - Review topics you found difficult   - Revisit problems you struggled with Day 30: Mock Interviews and Practice - Activities:   - Conduct mock interviews with a friend or use online platforms   - Focus on communication and explaining your thought process Top DSA resources to crack coding interview 👉 GeekforGeeks 👉 Leetcode 👉 DSA Steps 👉 FreeCodeCamp 👉 Coding Interviews 👉 Best DSA Resources Join for more: https://t.me/free4unow_backup ENJOY LEARNING 👍👍

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Python Patters

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Python Cheatsheet

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