🧠 LeetCode Insight — Minimum Size Subarray Sum (Sliding Window) I’ve been spending time strengthening my understanding of common problem-solving patterns, and today I revisited a great example of the sliding window technique. Problem: Find the minimal length of a contiguous subarray whose sum is at least a given target. 💡 Key Idea Instead of checking all possible subarrays, we: Expand the window by moving the right pointer Shrink the window from the left as soon as the sum meets the condition Keep track of the smallest valid window length This ensures we never do unnecessary work. Python CODE: https://lnkd.in/gErMBvjV ⏱ Complexity Time: O(n) Space: O(1) 🎯 Takeaway What clicked for me here is that sliding window problems are really about finding the right moment to shrink the window. Once the condition is satisfied, shrinking early helps discover the optimal answer. 👉 Which sliding window problem helped you understand this pattern better? #Python #DataStructures #ProblemSolving #SlidingWindow #LeetCode #SoftwareEngineering #LearningInPublic
Sliding Window Technique for Minimum Subarray Sum
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🚀 Day 4/30 | LeetCode Problem: Running Sum of 1D Array (1480) Problem: Given an array nums, return the running sum, where each element at index i is the sum of elements from index 0 to i. Approach: Initialize a variable to store the cumulative sum Traverse the array one by one Add each element to the cumulative sum Store the result in a new list This is a simple single-pass solution. Time Complexity: O(n) Space Complexity: O(n) Python Code: class Solution: def runningSum(self, nums): a = 0 b = [] for i in nums: a = a + i b.append(a) return b Example: Input: [1, 2, 3, 4] Output: [1, 3, 6, 10] Takeaway: Running sum is a basic form of prefix sum, which is very useful in many array problems. 📌 Accepted ✅ | All test cases passed 🔖 Hashtags #LeetCode #30DaysOfLeetCode #Day4 #Python #DSA #Algorithms #ProblemSolving #CodingJourney #SoftwareEngineering #TechCommunity
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ContextPlot is a small Python tool that places a real world image (design, site diagram, schematic, CAD export) directly into a data plot. The goal is simple: turn a standard time series figure into a context driven visual where the meaning of the signal is immediately clear. Code: https://lnkd.in/eFAcdCYu Video: https://lnkd.in/efByD8Um Follow Bernard Akaawase for more content. I got the inspiration for this project from #MVCO #ASIT at Woods Hole Oceanographic Institution. #python #visualization, #plotting
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📅 Winter Arc | Task 6/30 🎯 Challenge: Python Today’s focus: **Day 6: Loops Basics** ✅ What I worked on today: (You can personalize these points) - {{Practiced star and number patterns using for + while loops together in Python.}} - {{Learned to combine for and while loops in a single program: for loop to control rows while loop to print stars or numbers in each row}} - {{Wrote patterns like right-angled triangle, inverted triangle, and pyramids using this combined approach.}} 📚 Key takeaways from today: - {{for loops control rows, while loops control printing inside rows.}} - {{Combining loops helps make complex patterns and improves logic skills.}} This journey with Matrix – Winter Arc is helping me stay consistent, sharpen my skills, and take ownership of my daily progress. Small efforts every day are compounding into real growth. Staying locked in. On to the next task ❄️🔥 @MATRIX JEC #MatrixWinterArc #BuildWithMatrix #WinterArc #30DayChallenge #DailyProgress #MatrixJEC
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Day 41 – Counting Uppercase Letters in a String: Today’s task focused on identifying and counting uppercase letters in a user-provided string. By iterating through each character and applying conditional checks, the solution accurately detects uppercase characters. This exercise strengthened understanding of string traversal, built-in string methods, and logical conditions—key fundamentals for text analysis and data preprocessing. GitHub Code: https://lnkd.in/g5HQM5je #Day41 #100DaysOfCode #Python #StringManipulation #LogicBuilding #DailyCoding #Consistency
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This solution solves LeetCode 3013: Divide an Array Into Subarrays With Minimum Cost II by applying a sliding window technique with balanced data structures to efficiently track the smallest possible starting elements. Since the first subarray always begins at index 0, its cost is fixed, and the problem reduces to selecting the remaining k−1 starting indices within the given distance constraint such that their values sum to the minimum. By continuously maintaining the smallest k−1 elements as the window moves, the approach achieves optimal performance and avoids time-limit issues common with brute-force methods. #LeetCode #HardProblem #Python #SlidingWindow #DataStructures #Algorithms #CompetitiveProgramming #CodingInterview #Optimization
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Day 45 – Splitting and Joining a String: Today’s task focused on splitting a string using a user-defined delimiter and then joining the parts back into a clean, readable format. This exercise strengthened understanding of string methods, input handling, and text restructuring, which are essential skills for data preprocessing and text manipulation in real-world applications. GitHub Code: https://lnkd.in/gznh5VpR #Day45 #100DaysOfCode #Python #StringManipulation #LogicBuilding #TextProcessing #DailyCoding #Consistency
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🧠 LeetCode Insight — Permutation in String (Sliding Window + Frequency Map) I’ve been spending time improving my understanding of string-based sliding window problems, and this one ties the pattern together very well. Problem: Check whether one string’s permutation exists as a substring of another. 💡 Core Logic The key idea is simple but powerful: If a permutation of s1 exists in s2, then some substring of length len(s1) must have the same character frequencies as s1. So the solution becomes: Count character frequencies of s1 Maintain a sliding window of size len(s1) in s2 Compare frequency maps as the window moves Python code: https://lnkd.in/gKvqJkVU 🧩 Why This Works The window size is fixed, so frequency comparison is meaningful Each character is added once and removed once Removing zero-count entries keeps the maps comparable No unnecessary recomputation ⏱ Complexity Time: O(n) Space: O(1) (bounded by alphabet size) 🎯 Takeaway Sliding window problems become much easier when you stop thinking about substrings and start thinking about state. Here, the state is the character frequency map — once it’s correct, the solution follows naturally. 👉 Which string problem helped you really understand sliding window logic? #Python #DataStructures #SlidingWindow #ProblemSolving #LeetCode #SoftwareEngineering #LearningInPublic
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🚀 LeetCode Day 23 – Question 1572 🧮 Matrix Diagonal Sum Today’s problem focuses on understanding matrix traversal and diagonal logic. 📌 Key Concepts 🔹 Primary Diagonal From top-left to bottom-right Condition: row index = column index 🔹 Secondary Diagonal From top-right to bottom-left Condition: row index + column index = n − 1 🧠 Core Insight For each row: Add the primary diagonal element Add the secondary diagonal element ⚠️ If the matrix size is odd, the center element lies on both diagonals — count it only once. ⏱ Complexity Time Complexity: O(n) Space Complexity: O(1) Clean logic. Simple traversal. Strong fundamentals. 💪 #LeetCode #CodingJourney #ProblemSolving #100DaysOfCode #Python
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🚀 Day 5/50 – LeetCode Challenge Revisiting a core stack-based problem to strengthen logic and edge-case handling. 📌 Problem: Valid Parentheses (Easy) 🧠 Approach: Use a stack to track opening brackets and validate correct closing order ✨ Key Learning: Simple data structures can solve complex-looking problems cleanly Consistency over perfection. #LeetCode #Python #DSA #Consistency #LearningInPublic
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Day 11 of #100DaysOfLeetCode 🚀 Problem: LeetCode 43 – Multiply Strings Today’s challenge was interesting because direct integer multiplication is not allowed. We have to multiply two numbers given as strings and return the result as a string. 🧠 Key Learnings: You can’t convert strings to int (that’s the trap) Manual multiplication (just like school math) is the right approach Use an array to store intermediate results Handle carry properly Watch out for leading zeros 💡 Why this problem matters: Tests understanding of string manipulation Strengthens logic for large number handling ⏱️ Complexity: Time: O(n × m) Space: O(n + m) Slowly getting more comfortable with thinking beyond built-in shortcuts 💪 Consistency > Motivation. #LeetCode #Python #MultiplyStrings #DSA #CodingJourney #100DaysOfCode
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