✅ Day 54 of 100 Days LeetCode Challenge Problem: 🔹 #728 – Self Dividing Numbers 🔗 https://lnkd.in/gxraQJ82 Learning Journey: 🔹 Today’s problem focused on identifying numbers that are divisible by each of their digits. 🔹 For every number in the given range, I extracted its digits and checked divisibility conditions. 🔹 Any number containing zero was immediately rejected since division by zero is invalid. 🔹 Valid numbers were collected into the final result list. Concepts Used: 🔹 Digit Extraction 🔹 Modulo Arithmetic 🔹 Iterative Checking 🔹 Conditional Filtering Key Insight: 🔹 Breaking numbers into digits simplifies many number-theory problems. 🔹 Early elimination (like handling zeros) improves efficiency. 🔹 Clear validation logic makes implementation straightforward and readable. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity
Self Dividing Numbers LeetCode Challenge
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✅ 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
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✅ Day 56 of 100 Days LeetCode Challenge Problem: 🔹 #24 – Swap Nodes in Pairs 🔗 https://lnkd.in/g6W2b3Fq Learning Journey: 🔹 Today’s problem focused on swapping every two adjacent nodes in a linked list. 🔹 I used an iterative pointer manipulation approach to swap nodes in pairs without modifying node values. 🔹 A prev pointer helped connect previously swapped pairs with the current pair. 🔹 Careful handling of edge cases (empty list or single node) ensured correctness. Concepts Used: 🔹 Linked List Manipulation 🔹 Pointer Rewiring 🔹 Iterative Traversal 🔹 In-place Modification Key Insight: 🔹 Linked list problems often rely entirely on precise pointer updates. 🔹 Keeping track of previous connections prevents breaking the list structure. 🔹 Drawing pointer transitions step-by-step makes implementation much easier. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity
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✅ 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
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✅ 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
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🚀 30 𝐃𝐚𝐲𝐬 𝐨𝐟 𝐏𝐲𝐭𝐡𝐨𝐧 — 𝐃𝐚𝐲 #13 | 𝐈𝐧𝐭𝐞𝐫𝐦𝐞𝐝𝐢𝐚𝐭𝐞 & 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐍𝐞𝐬𝐭𝐞𝐝 𝐋𝐨𝐨𝐩𝐬 Day 13 was focused on learning intermediate and advanced concepts of nested loops. Today, I explored how loops can be placed inside other loops to create more structured and complex program flows. Understanding this concept helped me see how programs handle multi-level iterations. 📌 𝐖𝐡𝐚𝐭 𝐈 𝐂𝐨𝐯𝐞𝐫𝐞𝐝: 🔹 Intermediate nested loop structures 🔹 Advanced nested loop logic 🔹 How loops interact with each other inside different levels 🔹 Using nested loops to generate different patterns 💡 𝐊𝐞𝐲 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲: - Nested loops are powerful when it comes to handling multi-level iteration and pattern-based logic. - Understanding how each loop controls rows and columns is key to mastering patterns. A 𝐡𝐮𝐠𝐞 𝐬𝐡𝐨𝐮𝐭𝐨𝐮𝐭 𝐭𝐨 𝐭𝐡𝐞 𝐂𝐨𝐝𝐞 & 𝐃𝐞𝐛𝐮𝐠 𝐘𝐨𝐮𝐓𝐮𝐛𝐞 𝐜𝐡𝐚𝐧𝐧𝐞𝐥 for explaining these concepts so clearly and making even complex topics easy to understand. The structured explanations really make learning smoother. 𝐃𝐚𝐲 13 𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞 ✅ Each concept is helping me think more logically about programming. 💻✨ #Python #30DayChallenge #Day13 #NestedLoops #PatternProgramming #PythonLearning #CodingJourney #LearnToCode #Programming #TechGrowth
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✅ 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
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They asked for the sum of 5 numbers. The loop ran forever. One line was missing: count += 1. Without incrementing the counter, the condition never became false. One line. Infinite loop. I wrote a beginner practice guide that walks through both classics: ✅ Sum of N numbers — counter loop, running sum, read inside the loop ✅ Sum of positive vs negative separately — two sums, if/else inside the loop ✅ Variables you need: num_of_numbers, sum, count (and why count < N, not <= N) ✅ Full program structure and trace examples ✅ Common mistakes: forget count += 1, wrong condition, forget to init sum to 0 ✅ Clear takeaways and next steps ~6 min read. No fluff. https://lnkd.in/gkhQBbuQ #Python #Programming #Coding #Beginners #LearnToCode #SumOfNumbers #WhileLoop #Practice #Tech #SoftwareDevelopment #CodingTips
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They wanted the maximum of 5 numbers. The program printed 0. Every number was negative. max = 0 fails when all inputs are negative. Read the first number into max, then loop for the rest. One idea, two bugs avoided. I wrote a beginner guide that covers two classics in one: ✅ Maximum of N numbers — read first into max, loop N−1 times, update if larger (and why not max = 0) ✅ Decimal to binary — divide by 2, collect remainders, reverse. In code: prepend to a string. ✅ Why the "build as number" method loses leading zeros (and why string method is correct) ✅ Full programs: max of N and decimal-to-binary with n=0 handled ✅ Summary, takeaways, and next steps (min, binary→decimal) ~6 min read. Straight to the point. https://lnkd.in/gqJWam9x #Python #Programming #Coding #Beginners #LearnToCode #Maximum #DecimalToBinary #Binary #WhileLoop #Practice #Tech #SoftwareDevelopment #CodingTips
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Day 3: Mastering Operators! 🚀 Today, I learned how to make my code "think" using Operators. These are the tools that let us do math and create logic in programming. What I practiced today: ✅ Math Operators: Using +, -, *, /, and % for calculations. ✅ Comparison: Using ==, >, and < to compare values. ✅ Logical Thinking: Using and, or, and not to build smart conditions. I have practiced these concepts with real examples and pushed all my code to Github💻 Small steps every day lead to big results. #Coding #Python #Learning #Codegnan
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Day 5: 90-Day Coding Challenge 🚀 Continuing the journey by strengthening my understanding of greedy algorithms and efficient array traversal techniques. Today’s problem focused on the Best Time to Buy and Sell Stock challenge. The goal was to determine the maximum profit that can be achieved by buying and selling a stock once, given the stock prices across different days. Instead of checking all possible buy–sell combinations, I applied a greedy one-pass approach by tracking the minimum price seen so far and calculating the potential profit at each step. This allowed me to efficiently determine the best possible transaction while scanning the array only once. Today’s learning highlights: ✅ Understanding how maintaining a running minimum helps identify the best buying point ✅ Calculating profit dynamically while traversing the array ✅ Achieving an optimized O(n) time complexity with O(1) space complexity This problem reinforced an important insight: keeping track of key values during a single traversal can eliminate the need for nested iterations and significantly improve performance. Day 5 completed. On to Day 6. 💻🔥 #90DayCodingChallenge #CodingJourney #DSA #Arrays #GreedyAlgorithm #ProblemSolving #Python #LearningJourney #Consistency #Growth
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