Solving #100DaysOfDSA Day 99: Intersection of Two Arrays in Python

⚡ Day 91 of #100DaysOfDSA – Contains Duplicate II 🔄 📌 Problem. no 219: Determine whether there exist two identical elements in an array such that their indices are within distance k. If such elements exist — return True; otherwise, return False. 🚀 Runtime: 23 ms – Beats ⚡97.32% of Python submissions 💾 Memory: 23.88 MB – Beats 87.29% 💻 Language: Python ✅ Result: Accepted – 65 out of 65 test cases passed successfully This challenge deepened my understanding of hash map optimization and index-based checks for nearby duplicates — a perfect blend of logic and efficiency. 🔑 Key Learnings ✔️ Used a dictionary to store indices for O(n) efficiency ✔️ Applied index difference checks with constant-time lookups ✔️ Strengthened reasoning on spatial constraints in arrays 🎯 Day 91 — Smart hashing, clean logic, and another step forward in mastering efficient Python solutions. 🚀 #100DaysOfCode #100DaysOfDSA #LeetCode #PythonProgramming #DataStructures #AlgorithmPractice #CodeNewbie #DailyCoding #ProblemSolving #TechJourney #WomenWhoCode #CodeLife #CodingChallenge #DSAChallenge #DeveloperLife #PythonDeveloper #LearnToCode #CodingCommunity #CodeEveryday #SoftwareEngineering #KathirCollegeOfEngineering #KathirCollege #BTechLife #AIDS #FutureEngineer #CodingMotivation #ProgrammingSkills

⚡ Day 90 of #100DaysOfDSA – Contains Duplicate 🔁 📌 Problem. no 217: Check if any value appears at least twice in a list of integers. If a duplicate exists — return True; otherwise, return False. 🚀 Runtime: 6 ms – Beats ⚡97.87% of Python submissions 💾 Memory: 25.97 MB – Beats 47.47% 💻 Language: Python ✅ Result: Accepted – 77 out of 77 test cases passed successfully This problem helped reinforce set operations and efficient data lookup concepts. A simple but powerful reminder that clean logic can yield the fastest results. 🔑 Key Takeaways ✔️ Utilized set conversion for O(n) time complexity ✔️ Simplified logic with direct comparison of lengths ✔️ Strengthened understanding of duplicate detection in arrays 🎯 Day 90 — Simplicity wins! Mastering efficiency through minimal, elegant Python code. 🚀 #100DaysOfCode #100DaysOfDSA #LeetCode #PythonProgramming #DataStructures #AlgorithmPractice #CodeNewbie #DailyCoding #ProblemSolving #TechJourney #WomenWhoCode #CodeLife #CodingChallenge #DSAChallenge #DeveloperLife #PythonDeveloper #LearnToCode #CodingCommunity #CodeEveryday #SoftwareEngineering #KathirCollegeOfEngineering #KathirCollege #BTechLife #AIDS #FutureEngineer #CodingMotivation #ProgrammingSkills

🔥 Day 97 of #100DaysOfDSA – Counting Bits 💡 📌 Problem. no 338: For every number from 0 to n, count the number of 1s in its binary representation and return the list of counts. An elegant way to connect bit manipulation with loop optimization! ⚙️ 🚀 Runtime: 15 ms – Beats ⚡46.30% of Python submissions 💾 Memory: 17.81 MB – Beats 48.48% 💻 Language: Python ✅ Result: Accepted – 15 / 15 test cases passed 🎯 🔑 Key Learnings ✔️ Binary representation is a powerful yet simple way to analyze integer patterns ✔️ Python’s built-in functions like bin() and .count() simplify complex operations ✔️ Clean loops and logic always make debugging easier 💡 Day 97 — Simplicity in Bits, Power in Logic! 🔢 #100DaysOfCode #100DaysOfDSA #LeetCode #PythonProgramming #DataStructures #AlgorithmPractice #CodeNewbie #DailyCoding #ProblemSolving #TechJourney #WomenWhoCode #CodeLife #CodingChallenge #DSAChallenge #DeveloperLife #PythonDeveloper #LearnToCode #CodingCommunity #CodeEveryday #SoftwareEngineering #KathirCollegeOfEngineering #KathirCollege #BTechLife #AIDS #FutureEngineer #CodingMotivation #ProgrammingSkills

🚀 Day 8 of my #180DaysOfDataScience journey! Today, I learned about the core principles of Object-Oriented Programming (OOPs) in Python — the foundation of clean, reusable, and scalable code. 💻 Here are the 4 key pillars of OOPs I explored: 1️⃣ Encapsulation – Protecting data by keeping it private and controlled. 2️⃣ Inheritance – Reusing and extending existing code. 3️⃣ Polymorphism – Same function behaving differently for different objects. 4️⃣ Abstraction – Hiding unnecessary details and showing only what’s needed. These principles help in building efficient, modular, and easy-to-maintain programs. Excited to apply these in real-world projects soon! 🔥 #Day8 #Python #OOPsConcepts #DataScienceJourney #LearningEveryday #CodeNewbie #ObjectOrientedProgramming #TechLearning #PythonDeveloper #DataScienceWithPython #CodingCommunity #180DaysOfDataScience

🌟 Functions – The Building Blocks of Clean Code 🌟 Master functions to write reusable, modular, and maintainable Python! ✨ Function Flavours: 1️⃣ Built-in: print(), len(), type() 2️⃣ User-defined: def my_func() 3️⃣ Parameterized + Default args 4️⃣ Nested functions 5️⃣ Lambda (anonymous inline functions) 💡 Why It Matters: 1️⃣ Eliminate code duplication 2️⃣ Improve readability & debugging 3️⃣ Enable functional programming patterns 4️⃣ Scale from scripts to ML pipelines Pro move: Use lambdas with map(), filter(), sorted()! 📚 Huge shoutout to my mentor Yash Wadpalliwar at Fireblaze AI School - Training and Placement Cell for showing how small, smart functions power real-world systems! 🙌 #Python #Functions #Lambda #PythonTips #CleanCode #CodingTips #LearnPython #Programming #TechSkills #PythonProgramming #CodeOrganization #Developer #SoftwareEngineering #100DaysOfCode #CodeNewbie #PythonDeveloper #DataScience #MachineLearning #FireblazeAISchool

⚡ Day 92 of #100DaysOfDSA – Single Number III 🔍 📌 Problem. no 260: Given an array where every element appears twice except for two unique numbers, find both unique elements that appear only once. 🚀 Runtime: 0 ms – Beats ⚡100.00% of Python submissions 💾 Memory: 13.23 MB – Beats 65.94% 💻 Language: Python ✅ Result: Accepted – 35 / 35 test cases passed flawlessly This problem pushed me to dive deeper into bit manipulation and understand how XOR can efficiently isolate unique numbers without using extra space. 🔑 Key Learnings ✔️ XOR helps cancel out repeating elements effectively ✔️ Smart bit-level logic simplifies complex comparisons ✔️ Achieved O(n) time and O(1) space – clean and optimal 🎯 Day 92 — Every bit counts when it comes to optimization! ⚙️🔥 #100DaysOfCode #100DaysOfDSA #LeetCode #PythonProgramming #DataStructures #AlgorithmPractice #CodeNewbie #DailyCoding #ProblemSolving #TechJourney #WomenWhoCode #CodeLife #CodingChallenge #DSAChallenge #DeveloperLife #PythonDeveloper #LearnToCode #CodingCommunity #CodeEveryday #SoftwareEngineering #KathirCollegeOfEngineering #KathirCollege #BTechLife #AIDS #FutureEngineer #CodingMotivation #ProgrammingSkills

🚀 Day 46 of #100DaysOfDSA Solved LeetCode Problem #257 – Binary Tree Paths 🌿➡️🌿 📌 Problem Insight: Given the root of a binary tree, the task is to return all root-to-leaf paths as strings. Each path should follow the format: root -> child -> ... -> leaf This is a classic DFS + recursion problem that builds strong tree traversal skills. 💡 Key Learnings: Practiced Depth-First Search (DFS) to explore root-to-leaf paths. Understood how to accumulate path strings during recursive calls. Learned to identify leaf nodes and finalize completed paths. Time Complexity: O(n) — visit each node once. Space Complexity: O(h) — recursion stack height (h = tree height). 👉 Tree problems teach us to explore step by step — each decision builds the full path 🌳💡 #LeetCode #DSA #ProblemSolving #100DaysChallenge #Day46 #CodingJourney #Python #BinaryTree #DFS

🚀 Day 29/100 – Third Maximum Number (LeetCode #414) Today’s problem focused on finding the third distinct maximum number in a list — a task that tests both logic and precision. It was a great exercise in sorting, distinct values, and edge cases. This problem reminded me that simplicity in approach often leads to clearer, faster solutions. 🔍 Key Learnings: Handling duplicates using Python sets Sorting efficiently to extract specific elements Always account for edge cases in logic-based questions 🔗 Problem link:https://lnkd.in/gGHddwQB 🧠 Language: Python Every challenge strengthens the coding mindset — one function at a time. On to Day 30 💪 #100DaysOfCode #LeetCode #Python #CodingChallenge #ProblemSolving #Algorithms #PythonProgramming #DataStructures #DailyCoding #CodeJourney #TechCommunity #ProgrammerLife #LearnCoding #CodingConsistency

🔥 Day 96 of #100DaysOfDSA – Power of Three 💡 📌 Problem. no 326: Check if a given number is a power of 3. If it is, return True; otherwise, return False. Simple yet elegant number theory logic at play. 🚀 Runtime: 11 ms – Beats ⚡61.54% of Python submissions 💾 Memory: 12.45 MB – Beats 51.93% 💻 Language: Python ✅ Result: Accepted – 21,040 / 21,040 test cases passed! 🔑 Key Learnings ✔️ Efficient looping and modular arithmetic can reveal hidden mathematical patterns ✔️ Edge cases (like n <= 0) must always be handled carefully ✔️ Clean, readable code performs just as powerfully as optimized code 🎯 Day 96 — Mathematics + Logic = Pure Programming Magic ✨ #100DaysOfCode #100DaysOfDSA #LeetCode #PythonProgramming #DataStructures #AlgorithmPractice #CodeNewbie #DailyCoding #ProblemSolving #TechJourney #WomenWhoCode #CodeLife #CodingChallenge #DSAChallenge #DeveloperLife #PythonDeveloper #LearnToCode #CodingCommunity #CodeEveryday #SoftwareEngineering #KathirCollegeOfEngineering #KathirCollege #BTechLife #AIDS #FutureEngineer #CodingMotivation #ProgrammingSkills

🔁 Day 45 of #100DaysOfDSA — Reverse Linked List Problem: Reverse Linked List (LeetCode #206) Given the head of a singly linked list, reverse it and return the reversed list. Concepts Used: 🧠 Stack-based approach Traverse the linked list and push each node’s value into a stack. Then reassign values by popping from the stack to reverse the list. 🧩 Learning Reflection: This problem helped me understand how stacks can simplify linked list manipulations. Though not the most space-efficient solution, it reinforces the concept of LIFO (Last In, First Out) operations beautifully. ⏱️ Complexity: Time: O(N) Space: O(N) 💬 Closing Thought: Sometimes, using an extra data structure makes logic clearer — and that’s okay while learning. #LeetCode #DSA #LinkedList #Python #100DaysOfCode #CodingJourney