Count Binary Substrings with LeetCode Challenge

✅ Day 53 of 100 Days LeetCode Challenge Problem: 🔹 #191 – Number of 1 Bits 🔗 https://lnkd.in/gZPa-tQf Learning Journey: 🔹 Today’s problem focused on counting the number of set bits (1s) in the binary representation of an integer. 🔹 I converted the number to its binary form and iterated through the string representation. 🔹 By counting occurrences of '1', I determined the Hamming weight of the number. 🔹 This approach is simple and clear for understanding bit representation. Concepts Used: 🔹 Bit Manipulation 🔹 Binary Representation 🔹 String Conversion 🔹 Counting Technique Key Insight: 🔹 Every integer can be analyzed at the bit level for efficient computation. 🔹 Converting to binary provides an intuitive way to visualize set bits. 🔹 Bit manipulation problems often have multiple optimized approaches beyond basic counting. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 58 of 100 Days LeetCode Challenge Problem: 🔹 #1680 – Concatenation of Consecutive Binary Numbers 🔗 https://lnkd.in/gt22hnfF Learning Journey: 🔹 Today’s problem involved concatenating the binary representations of numbers from 1 to n. 🔹 I generated binary strings using bin(i)[2:] and appended them sequentially. 🔹 After forming the final binary string, I converted it back to an integer. 🔹 Since the result can be very large, I applied modulo 10**9+7. Concepts Used: 🔹 Binary Representation 🔹 String Manipulation 🔹 Modular Arithmetic 🔹 Simulation Key Insight: 🔹 Direct string concatenation works but is not optimal for large n. 🔹 Efficient solutions avoid large intermediate strings by using bit shifts and modular arithmetic at each step. 🔹 Understanding bit-length growth is crucial for optimization in binary construction problems. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 57 of 100 Days LeetCode Challenge Problem: 🔹 #1404 – Number of Steps to Reduce a Number in Binary Representation to One 🔗 https://lnkd.in/ggb5GXaW Learning Journey: 🔹 Today’s problem focused on reducing a binary number to 1 using specific rules. 🔹 If the number is even, divide it by 2. If it is odd, add 1. 🔹 I converted the binary string to an integer, applied the operation, and converted it back to binary after each step. 🔹 The process continued until the value became "1", counting the total operations. Concepts Used: 🔹 Binary Representation 🔹 Bit Manipulation Concepts 🔹 Simulation 🔹 Conditional Logic Key Insight: 🔹 Binary problems often map directly to parity checks (even vs odd). 🔹 Simulation is straightforward but understanding bit behavior can lead to optimized solutions. 🔹 Recognizing patterns in binary transitions improves problem-solving efficiency. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 61 of 100 Days LeetCode Challenge Problem: 🔹 #260 – Single Number III 🔗 https://lnkd.in/gKWtdDrb Learning Journey: 🔹 Today’s problem focused on finding the two elements that appear only once in an array where all others appear twice. 🔹 I used a frequency counting approach with Counter to track occurrences. 🔹 Then, I iterated through the dictionary and collected elements with frequency equal to 1. 🔹 This straightforward method ensures correctness with clear logic. Concepts Used: 🔹 Hash Map / Dictionary 🔹 Frequency Counting 🔹 Array Traversal 🔹 Filtering Logic Key Insight: 🔹 Hash-based counting simplifies duplicate detection problems. 🔹 When constraints allow extra space, clarity can be prioritized over bit-level optimization. 🔹 This problem also has an advanced XOR-based O(1) space solution, but counting keeps the implementation simple and readable. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 63 of 100 Days LeetCode Challenge Problem: 🔹 #1758 – Minimum Changes To Make Alternating Binary String 🔗 https://lnkd.in/gSY9BDhw Learning Journey: 🔹 Today’s problem focused on converting a binary string into an alternating pattern with minimum changes. 🔹 There are only two valid alternating patterns: starting with '0' (0101...) or starting with '1' (1010...). 🔹 I counted mismatches for both patterns while iterating through the string. 🔹 The answer is the minimum number of flips required between the two possibilities. Concepts Used: 🔹 String Traversal 🔹 Pattern Matching 🔹 Greedy Counting 🔹 Parity Indexing Key Insight: 🔹 When only two structural patterns are possible, evaluate both and choose the minimum cost. 🔹 Index parity (i % 2) is a clean way to enforce alternating constraints. 🔹 Comparing against expected patterns avoids unnecessary string reconstruction. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 68 of 100 Days LeetCode Challenge Problem: 🔹 #1207 – Unique Number of Occurrences 🔗 https://lnkd.in/g2vjwwft Learning Journey: 🔹 Today’s problem required checking whether the frequency of each element in an array is unique. 🔹 I first used Counter to count how many times each number appears in the array. 🔹 Then I extracted the occurrence counts using .values(). 🔹 To verify uniqueness, I compared the length of the occurrences list with the length of a set created from those values. 🔹 If both lengths match, it means all occurrence counts are unique. Concepts Used: 🔹 Hash Map / Frequency Counting 🔹 Python Counter from collections 🔹 Sets for Uniqueness Check Key Insight: 🔹 Converting values to a set removes duplicates automatically. 🔹 If the size of the set equals the number of frequency values, then all occurrence counts are distinct. Complexity: 🔹 Time: O(n) 🔹 Space: O(n) #LeetCode #Algorithms #DataStructures #CodingInterview #100DaysOfCode #SoftwareEngineering #Python #ProblemSolving #LearningInPublic #TechCareers

🚀 #Day41 of #100DaysOfCode 📌 Problem: 80. Remove Duplicates from Sorted Array II Today’s challenge was about handling duplicates in a sorted array while keeping the array in-place. 💡 Key Idea: The array is already sorted, so duplicates appear next to each other. We need to ensure that each number appears at most twice. Extra duplicates beyond two should be removed while maintaining the original order. 🧠 Approach: 1️⃣ Traverse the array from left to right. 2️⃣ Keep track of how many times the current number appears consecutively. 3️⃣ Allow insertion only if the occurrence count is ≤ 2. 4️⃣ Maintain an index pointer to place valid elements in the correct position. ⚡ Complexity: Time Complexity: O(n) Space Complexity: O(1) (in-place modification) #leetcode #Python #programming #coding #softwaredevelopment #100daysofcode

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🚀 30 𝐃𝐚𝐲𝐬 𝐨𝐟 𝐏𝐲𝐭𝐡𝐨𝐧 — 𝐃𝐚𝐲 #20 | 𝐃𝐞𝐞𝐩 𝐃𝐢𝐯𝐞 𝐢𝐧𝐭𝐨 𝐒𝐭𝐫𝐢𝐧𝐠𝐬 & 𝐌𝐞𝐭𝐡𝐨𝐝𝐬 Day 20 was all about going deeper into strings and string methods to build a stronger conceptual understanding. Instead of practicing questions, I focused on understanding how strings work internally and how different methods can be used to manipulate text efficiently. 📌 𝐖𝐡𝐚𝐭 𝐈 𝐂𝐨𝐯𝐞𝐫𝐞𝐝: 🔹 Strengthened my understanding of strings 🔹 𝐬𝐩𝐥𝐢𝐭() — breaking strings into parts 🔹 𝐣𝐨𝐢𝐧() — combining elements into a string 🔹 𝐟𝐢𝐧𝐝() — locating substrings 🔹 𝐫𝐞𝐩𝐥𝐚𝐜𝐞() — modifying text 🔹 Explored multiple other useful 𝐬𝐭𝐫𝐢𝐧𝐠 𝐦𝐞𝐭𝐡𝐨𝐝𝐬 This deeper dive helped me understand how Python handles text data and how these methods are used in real-world scenarios. 💡 𝑲𝒆𝒚 𝑻𝒂𝒌𝒆𝒂𝒘𝒂𝒚 Going deep into concepts builds clarity. When the foundation is strong, applying it becomes much easier and more effective. 𝐃𝐚𝐲 20 𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞 ✅ Understanding is getting stronger with every step. 💻✨ #Python #30DayChallenge #Day20 #PythonStrings #StringMethods #LearningJourney #LearnToCode #Programming #TechGrowth #Consistency

𝐃𝐚𝐲 𝟗 𝐨𝐟 𝐦𝐲 𝐃𝐒𝐀 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧 𝐣𝐨𝐮𝐫𝐧𝐞𝐲 — 𝐭𝐨𝐝𝐚𝐲 𝐰𝐚𝐬 𝐥𝐞𝐬𝐬 𝐜𝐨𝐝𝐢𝐧𝐠, 𝐦𝐨𝐫𝐞 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 🧩 Not every day is about solving problems. Today was about building clarity. I focused on Python arrays and understanding them properly before jumping into heavy problem solving. Here’s what I covered: • How arrays are implemented in Python • Basic operations — add, remove, update elements • Key properties of arrays and how they behave Then I moved to the fundamentals of: • Searching algorithms • Sorting algorithms Today was mostly theory + understanding the “why” behind things — and honestly, this step feels underrated. Because better understanding today = faster problem solving tomorrow. 📌 Plan for Day 10: Applying all of this through problem solving on arrays Slowly shifting from learning → applying. #DSA #Python #DataStructures #Algorithms #CodingJourney #LearnInPublic #Programming #SoftwareDevelopment #ComputerScience #TechLearning #CodeNewbie #100DaysOfCode #Developers #CodingLife