Solved LeetCode Problem 1716: Calculate Money in Leetcode Bank

🚀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

💻 2011: Final Value of Variable After Performing Operations Today’s challenge was a simple yet interesting warm up problem that tests how efficiently we can track changes in a variable through a series of operations. 🧠 Concept: We start with X = 0, and perform operations like ++X, X++, --X, and X--. Each increment or decrement modifies X by 1, the task is to return the final value after performing all operations. ⚙️ Approach: - A straightforward solution: - Iterate through all operations. - Increment count by 1 for ++ or X++. - Decrement count by 1 for -- or X--. - Return the final count. Even though it’s an easy problem, it’s a great reminder that clarity and precision matter, small details in logic can make a big difference. #LeetCode #Python #CodingPractice #ProblemSolving #100DaysOfCode

🚀 LeetCode #1526: Minimum Number of Increments on Subarrays to Form a Target Array Today I tackled an interesting Greedy Algorithm problem that really tests your ability to spot patterns and simplify complex logic. 🧩 Problem Brief: We start with an array of zeros and can increment any subarray by 1 in one operation. The goal is to form the target array using the minimum number of operations. 💡 Key Insight: Instead of simulating every operation, focus on how much each element increases compared to the previous one; each increase represents new operations needed. ⚙️ Formula: operations = target[0] + Σ(max(0, target[i] - target[i-1])) 🧠 Complexity: Time: O(n) Space: O(1) 🎯 Takeaway: Hard problems often become simple once you recognize the pattern behind the process. #LeetCode #Python #DSA #Coding #ProblemSolving #GreedyAlgorithm #LearningEveryday

🚀 Day 4/100 — Cracked LeetCode 1611: Minimum One Bit Operations to Make Integers Zero 🔥 Today’s challenge was a deep dive into bit manipulation and recursion. LeetCode 1611 looked deceptively simple—but beneath the surface, it’s a clever twist on Gray code transformations. 🔍 Problem Summary Transform an integer n into 0 using two constrained bit-flipping operations. The trick? You can only flip the rightmost bit, or flip the i-th bit if the (i-1)th is 1 and all lower bits are 0. 🧠 Key Insight This problem maps beautifully to recursive Gray code logic. For any number n, we recursively reduce it by flipping the highest set bit and subtracting the operations needed for the remainder. 📈 What I Learned Bitwise recursion can be elegant and powerful. Understanding binary patterns unlocks optimization. Python’s bit_length() is a hidden gem for bit-level logic. 🔧 Next Steps I’ll be documenting more of these insights as part of my 100-day challenge. If you’re into algorithmic puzzles or want to collaborate on clean, modular solutions—let’s connect! #100DaysOfCode #LeetCode #Python #BitManipulation #GrayCode #CodingChallenge #TechJourney #ScarBuilds

🚀 Day 69 of #100DaysOfCode Solved LeetCode Problem #3542: Minimum Operations to Convert All Elements to Zero (Medium) Concepts Used: Stack Data Structure Efficient traversal and state management Understanding subarray operations Approach Summary: Iterated through each element while maintaining a stack to track increasing sequences. Incremented operation count whenever a new minimum appeared. This approach ensures minimum operations to reduce all elements to zero efficiently. Result: Accepted (Beats 85.71% in Runtime & 90.06% in Memory) Each day, one problem closer to mastery! #Python #LeetCode #100DaysOfCode #ProblemSolving #DataStructures #Algorithms #CodingJourney #MCA

💡 Day 37 of 100 — Minimum Operations to Convert All Elements to Zero (#LeetCode 3542) Today’s problem was an interesting one short in code, but deeper in logic. It was one of those problems where the intuition slowly unfolds as you play with examples. 🧠 What I figured out This problem is all about monotonic stacks a pattern that helps you process elements in increasing or decreasing order efficiently. The key idea: Every time the current number is greater than what’s on top of the stack, it represents a new “operation” needed. By maintaining a non-decreasing stack, you avoid unnecessary repetitions and count exactly when new operations are required. 💻 My thought process At first, I tried to simulate each operation directly which got messy. Then I realized this could be solved cleanly using a stack that tracks when a new increase appears in the sequence. Every rise means one more operation, and when numbers fall, you just pop from the stack. 📊 Complexity: Time — O(n) Space — O(n) 💬 Reflection This one reminded me how often elegant ideas hide in short problems. It’s not about long code it’s about clarity of thought. Sometimes, a single stack can tell the whole story. #100DaysOfLeetCode #Day37 #LeetCodeJourney #Coding #ProblemSolving #Python #DSA

🗓 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

⏳ Leetcode #1611: Minimum One Bit Operations to Make Integers Zero 🔍 Today I picked up a problem that looked chaotic at first: transforming any integer into zero using very restricted bit-flip rules. Every bit could only flip if the bits below it satisfied certain conditions, making the process feel unpredictable 🧩. But once I dug deeper, something interesting appeared. The pattern wasn’t random at all; it was secretly following Gray Code. That realization turned a confusing sequence of operations into a clean, structured transformation ✨. ✅ Key Insight: The number of operations directly aligns with converting a Gray-Code-like representation of n into its binary form. ✅ Time Complexity: O(log n) ✅ Space Complexity: O(1) These are the moments that make problem solving rewarding: when the “why is this so messy?” suddenly becomes “this is actually lowkey clean” 🧠💡. #DataStructures #LeetCode #CodingChallenge #ProblemSolving #Python #DSA #ComputerScience #learningEveyDay

LeetCode 90-Day Challenge – Day 74 Problem: Evaluate Reverse Polish Notation Difficulty: Medium Problem: We’re given an array of strings tokens that represent an arithmetic expression in Reverse Polish Notation (RPN). Our goal is to evaluate this expression and return the result as an integer. In RPN, the operator appears after its operands, for example, instead of writing (2 + 1) * 3, we write 2 1 + 3 *. Solution approach: I solved this using a stack-based approach. Each time we encounter a number, we push it to the stack. When we encounter an operator, we pop the top two numbers, perform the operation, and push the result back. In the end, the stack will contain a single number, the final evaluated result. This approach runs in O(n) time and ensures integer division truncates toward zero, as required by the problem. #LeetCode #90DaysOfCode #Python #LinkedInChallenge #CodingJourney #ProblemSolving #LeetCodeChallenge

#96day of #100DaysOfCode 🌱 LeetCode 109: Convert Sorted List to Binary Search Tree Today’s challenge was about building balance — literally! Given a sorted linked list, we need to convert it into a height-balanced BST 🌳 🧠 Key Idea: The middle element of the list becomes the root. Left half forms the left subtree, right half forms the right subtree. Use slow–fast pointers to find the middle efficiently. 📈 Complexity: Time: O(n log n) Space: O(log n) (recursion stack) 💬 Learning: Balance matters — in trees, in code, and in life 🌿 Sometimes, the middle point creates the strongest foundation. #LeetCode #DSA #BinarySearchTree #LinkedList #CodingChallenge #Python #Algorithm #LeetCodeDaily #100DaysOfCode