Day 96 of #100DaysOfDSA: Checking if a number is a power of 3 in Python

🗓 Day 12 / 100 – #100DaysOfLeetCode 📌Problem 3234: Count the Number of Substrings With Dominant Ones A substring is considered to have dominant ones if: Number of 1s ≥ (Number of 0s)² The challenge was to count how many substrings in the binary string satisfy this condition. 🧠 My Approach: Iterated through substrings while tracking zero count and one count. Used the condition ones ≥ zeros² to determine validity. Applied early stopping when zeros became large, since the condition becomes much harder to meet as zeros grow. This pruning helped avoid unnecessary checks and made the approach more efficient. 💡 Key Learning: This problem highlights how mathematical constraints can simplify substring evaluation. Understanding how zeros grow quadratically in the condition helped shape a smarter, more optimized checking approach rather than brute-force enumeration. A great exercise in reasoning about substring properties and designing early-exit logic. Consistent effort… consistent progress 🚀 #100DaysOfLeetCode #LeetCodeChallenge #Python #ProblemSolving #BinaryStrings #StringAlgorithms #Optimization #LogicBuilding #DataStructures #Algorithms #DSA #CompetitiveProgramming #CodingJourney #SoftwareEngineering #LearningInPublic #TechStudent #DeveloperJourney #CareerGrowth #CodeEveryday #CodingCommunity #KeepLearning #Programmer

⚡ 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 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 94 of #100DaysOfDSA – First Bad Version 🧩 📌 Problem. no 278: Find the first bad version in a sequence of software versions using minimal API calls. 🚀 Runtime: 11 ms – Beats ⚡86.79% of Python submissions 💾 Memory: 12.47 MB – Beats 49.90% 💻 Language: Python ✅ Result: Accepted – 24 / 24 test cases passed successfully This challenge was a neat application of binary search to minimize API queries and optimize decision-making over large datasets. 🔑 Key Learnings ✔️ Efficient mid-point calculation prevents overflow in large searches ✔️ Binary search is a timeless and versatile tool ✔️ Understanding search space optimization enhances overall coding logic 🎯 Day 94 — Debug less, think binary, and aim for precision! ⚙️📈 #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 71 of #100DaysOfCode Today's challenge was LeetCode Problem #3228 - Maximum Number of Operations to Move Ones to the End. This problem focused on binary string manipulation and calculating the maximum possible operations under specific conditions. It tested the ability to analyze how '1's can be shifted past '0's efficiently while maintaining optimal time complexity. Key Learnings: Applied an efficient linear approach to avoid unnecessary simulations. Learned to track and update the count of '1's dynamically during iteration. Strengthened problem-solving strategies for string-based algorithmic questions. Language Used: Python Runtime: 55 ms (Beats 74.85%) Memory: 18.12 MB (Beats 54.49%) Day 70 represents continuous progress in improving logical reasoning and coding efficiency. Each solved problem builds a stronger foundation for advanced algorithmic thinking and real-world software development. #LeetCode #Python #ProblemSolving #CodingChallenge #100DaysOfCode #Algorithm #DataStructures #Mythyly

🚀#3217: Delete Nodes from Linked List present in an Array Recently, I explored an interesting problem involving the removal of specific nodes from a linked list based on a given list of values. 💡 Problem Overview: Given a linked list and a list of numbers nums, the task is to delete all nodes whose values are present in nums. 🔍 Approach Summary: 1️⃣ Convert nums into a set for constant time lookups. 2️⃣ Traverse the linked list using two pointers, curr (current node) and prev (previous node). 3️⃣ If the current node’s value is in the set: - If it’s the head, move the head forward. - Otherwise, link the previous node to the next node, effectively removing the current one. 4️⃣ Continue traversing until all matching nodes are removed. ✨ Key Learnings: - Utilizing a set improves efficiency for value lookups. - Careful handling of the head node prevents pointer issues. - Clean traversal logic leads to better readability and fewer edge case errors. #Python #DataStructures #LinkedList #Coding #ProblemSolving #LeetCode #DSA #LearningJourney

📌 Problem. no 179: Given a list of non-negative integers, arrange them such that they form the largest possible number. Solved using a custom comparator to sort numbers based on concatenation order and achieve the optimal result. ⚡ Runtime: 3 ms – Beats 78.56% of submissions 💾 Memory: 12.69 MB – Beats 24.66% of solutions 💻 Language Used: Python ✅ Status: Accepted – All 235 test cases passed successfully! This problem enhanced my understanding of string-based comparison, custom sorting, and optimization through logic-based ordering. It’s an elegant challenge that blends sorting and string manipulation seamlessly. 🔑 Key Learnings: ✔️ Learned how to design and implement custom comparators ✔️ Understood how concatenation order affects numeric outcomes ✔️ Strengthened my grasp on sorting logic and greedy approaches 🎯 Day 84 — A creative challenge that refined my problem-solving through custom sorting and logical structuring! 🚀🔥 #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 83 of #100DaysOfDSA – Majority Element 💡 📌 Problem. no 169: Given an array nums, find the element that appears more than ⌊n / 2⌋ times. Implemented an efficient hash map-based counting approach to track element frequency and determine the majority element quickly. ⚡ Runtime: 13 ms – Beats 37.81% of submissions 💾 Memory: 13.60 MB – Beats 64.79% of solutions 💻 Language Used: Python ✅ Status: Accepted – All 53 test cases passed successfully! This challenge helped me better understand frequency counting, dictionary operations, and threshold-based decision making. It’s a great problem for mastering counting logic and handling arrays efficiently. 🔑 Key Learnings: ✔️ Strengthened my understanding of hash maps and element frequency counting ✔️ Learned how to use early termination for optimization ✔️ Improved confidence in solving majority and occurrence-based problems 🎯 Day 83 — A solid step forward in mastering counting logic and data structure efficiency! 🚀🔥 #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 38 / 100 – Recursion: Factorial of a Number (LeetCode-#509) Today’s challenge was all about recursion — one of the most elegant concepts in programming. I revisited the Factorial problem, which beautifully demonstrates how a big problem can be broken into smaller subproblems. The idea is simple: 👉 The factorial of n is n * factorial(n-1) until n becomes 1. But the real challenge lies in understanding the flow of recursive calls and how the call stack unwinds to give the final result. This problem reminded me that recursion isn’t just about repeating a function — it’s about trusting the process and thinking in terms of smaller steps to solve complex problems. 🔍 Key Learnings Every recursive function must have a base case to prevent infinite loops. The call stack stores each recursive call until it’s resolved. Recursion is a natural fit for problems that can be divided into smaller, similar subproblems. 💭 Thought of the Day Recursion teaches patience and structure. Sometimes, you need to trust that solving the smaller version of a problem will help you conquer the big one — both in code and in life 💫. 🔗 Reference Problem:https://lnkd.in/g3yNGDbJ #100DaysOfCode #Day38 #LeetCode #Python #Recursion #Factorial #ProblemSolving #CodingChallenge #Algorithms #ProgrammingMindset #DataStructures #CleanCode #LearnByDoing #TechGrowth #PythonProgramming

It’s time to think like an engineer. The Build Your Own Algorithm Challenge is here, your chance to apply everything you’ve learned and create something uniquely yours. Your goal: Pick one data structure. Design a simple algorithm around it. Show how it solves a real-world problem, sorting data, finding patterns, or optimizing performance. It’s not about complexity, it’s about clarity of thought and logical problem-solving. Because real programmers don’t just write code, they design systems that work. Share your approach in the comments or tag us with #LearnProgrammingChallenge for a chance to get featured on our page! 💻 Course: Python Data Structures and Algorithms – Complete Guide 🎓 Instructors: Tim Buchalka & Jean-Paul Roberts #PythonProgramming #CodingChallenge #AlgorithmDesign #LearnProgrammingAcademy #TimBuchalka #ProblemSolving #PythonDevelopers #DataStructures