LeetCode 3868: Minimum Cost to Equalize Arrays Using Swaps

✅ Day 89 of 100 Days LeetCode Challenge Problem: 🔹 #1480 – Running Sum of 1D Array 🔗 https://lnkd.in/gSTZrxF7 Learning Journey: 🔹 Today’s problem focused on computing the running (prefix) sum of an array. 🔹 Instead of using an extra array, I optimized the solution by modifying the input array in-place. 🔹 Starting from index 1, I updated each element as: • nums[i] += nums[i-1] 🔹 This way, each index stores the cumulative sum up to that point. 🔹 Finally, returned the modified array. Concepts Used: 🔹 Prefix Sum 🔹 In-place Computation 🔹 Array Traversal Key Insight: 🔹 The previous element already stores the prefix sum, so we can reuse it directly. 🔹 Eliminates the need for extra space while maintaining linear time. Complexity: 🔹 Time: O(n) 🔹 Space: O(1) #LeetCode #Algorithms #DataStructures #CodingInterview #100DaysOfCode #Python #ProblemSolving #LearningInPublic #TechCareers

✅ Day 87 of 100 Days LeetCode Challenge Problem: 🔹 #2840 – Check if Strings Can be Made Equal With Operations II 🔗 https://lnkd.in/gY73RBb5 Learning Journey: 🔹 Today’s problem extended the previous one, allowing swaps between indices where the difference is even. 🔹 I observed that this again partitions the string into two independent groups: • Even indices (0, 2, 4, …) • Odd indices (1, 3, 5, …) 🔹 I extracted characters from even and odd positions separately for both strings. 🔹 Then, I sorted these groups and compared them between s1 and s2. 🔹 If both even-index groups and odd-index groups match, the strings can be made equal. Concepts Used: 🔹 String Manipulation 🔹 Index Grouping (Parity-based) 🔹 Sorting 🔹 Greedy Observation Key Insight: 🔹 Since swaps are allowed only between indices with even distance, characters can only move within their parity group. 🔹 Therefore, the problem reduces to checking if both parity groups have identical character distributions. Complexity: 🔹 Time: O(n log n) 🔹 Space: O(n) #LeetCode #Algorithms #DataStructures #CodingInterview #100DaysOfCode #SoftwareEngineering #Python #ProblemSolving #LearningInPublic #TechCareers

✅ Day 81 of 100 Days LeetCode Challenge Problem: 🔹 #1897 – Redistribute Characters to Make All Strings Equal 🔗 https://lnkd.in/gZ7wZ7JE Learning Journey: 🔹 Today’s problem required checking if we can redistribute characters so that all strings become identical. 🔹 I combined all strings and used a frequency counter to count occurrences of each character. 🔹 Since we can freely move characters between strings, the only requirement is that each character count must be divisible by the number of strings. 🔹 If any character fails this condition, it’s impossible to evenly distribute it. Concepts Used: 🔹 Hash Map / Frequency Counting (Counter) 🔹 String Concatenation 🔹 Divisibility Check Key Insight: 🔹 The exact arrangement doesn’t matter—only the total frequency distribution matters. 🔹 If every character can be equally divided among all strings, a valid configuration always exists. Complexity: 🔹 Time: O(n * k) (n = number of strings, k = average length) 🔹 Space: O(1) (bounded by alphabet size) #LeetCode #Algorithms #DataStructures #CodingInterview #100DaysOfCode #SoftwareEngineering #Python #ProblemSolving #LearningInPublic #TechCareers

✅ Day 95 of 100 Days LeetCode Challenge Problem: 🔹 #869 – Reordered Power of 2 🔗 https://lnkd.in/gkNXaSFM Learning Journey: 🔹 Today’s problem focused on checking whether the digits of a number can be rearranged to form a power of 2. 🔹 I created a helper function to extract and store the digits of a number. 🔹 Then I sorted the digits of the input number for comparison. 🔹 Next, I generated powers of 2 iteratively and compared their sorted digit lists with the input. 🔹 If any match was found, I returned True. Otherwise, continued until the digit length exceeded the input. Concepts Used: 🔹 Digit Extraction 🔹 Sorting 🔹 Simulation of Powers of 2 🔹 Brute Force Optimization Key Insight: 🔹 Instead of generating permutations (which is expensive), sorting digits allows quick comparison. 🔹 Any valid rearrangement must have the same digit frequency as some power of 2. Complexity: 🔹 Time: O(log n * d log d) 🔹 Space: O(d) #LeetCode #Algorithms #DataStructures #CodingInterview #100DaysOfCode #Python #ProblemSolving #LearningInPublic #TechCareers

✅ Day 74 of 100 Days LeetCode Challenge Problem: 🔹 #653 – Two Sum IV: Input is a BST 🔗 https://lnkd.in/g9vDFKMA Learning Journey: 🔹 Today’s problem required checking whether there exist two nodes in a Binary Search Tree whose values sum to k. 🔹 I performed a Depth-First Search (DFS) traversal using a stack to visit all nodes of the tree. 🔹 While traversing, I stored each node’s value in a list. 🔹 Then I used a hash set to track visited values and checked whether the complement (k - value) already exists. 🔹 If the complement is found, it means two numbers sum to k, so the function returns True. Concepts Used: 🔹 Depth-First Search (DFS) 🔹 Stack-based Tree Traversal 🔹 Hash Set for Fast Lookup 🔹 Two Sum Pattern Key Insight: 🔹 The classic Two Sum approach works well after collecting values from the BST. 🔹 Using a set allows O(1) lookup, making it efficient to check complements during iteration. Complexity: 🔹 Time: O(n) 🔹 Space: O(n) #LeetCode #Algorithms #DataStructures #CodingInterview #100DaysOfCode #SoftwareEngineering #Python #ProblemSolving #LearningInPublic #TechCareers

Topic 4/100 🚀 🧠 Topic 4 — Generators Processing large data and running out of memory? 😵 This concept solves that problem. 👉 What is it? Generators are functions that return values one at a time using yield instead of returning everything at once. 👉 Use Case: Used in real-world applications for: Reading large files Data streaming Handling APIs with pagination 👉 Why it’s Helpful: Saves memory Improves performance Enables lazy evaluation (data generated only when needed) 💻 Example: def count_up_to(n): for i in range(n): yield i for num in count_up_to(5): print(num) 🧠 What’s happening here? Instead of storing all values in memory, the function generates them one by one when needed. ⚡ Pro Tip: If you're working with large datasets, always think “generator” before using lists. 💬 Follow this series for more Topics #Python #BackendDevelopment #100TopicOfCode #SoftwareEngineering #LearnInPublic

✅ Day 98 of 100 Days LeetCode Challenge Problem: 🔹 #338 – Counting Bits 🔗 https://lnkd.in/gXdNxX66 Learning Journey: 🔹 Today’s problem focused on counting the number of 1s in the binary representation of numbers from 0 to n. 🔹 I initialized an array ans of size n+1. 🔹 For each number i, I converted it to binary using bin(i)[2:]. 🔹 Counted the number of '1' bits by iterating through the binary string. 🔹 Stored the count in ans[i] and returned the final array. Concepts Used: 🔹 Bit Manipulation (Binary Representation) 🔹 Array Traversal 🔹 String Processing 🔹 Brute Force Approach Key Insight: 🔹 Each number’s bit count can be computed independently. 🔹 Converting to binary and counting '1' works, but can be optimized further using DP or bit tricks. Complexity: 🔹 Time: O(n log n) (binary conversion for each number) 🔹 Space: O(n) #LeetCode #Algorithms #DataStructures #100DaysOfCode #Python #CodingJourney #ProblemSolving #LearningInPublic

✅ Day 80 of 100 Days LeetCode Challenge Problem: 🔹 #3876 – Construct Uniform Parity Array II 🔗 https://lnkd.in/gENuCXJc Learning Journey: 🔹 Today’s problem focused on determining whether we can construct an array where all elements are either all even or all odd using allowed operations. 🔹 The key observation was around parity (odd/even nature) of numbers. 🔹 Since we can subtract elements, the parity depends on whether differences can produce consistent odd or even values. 🔹 I simplified the logic by checking: • If the minimum element is odd → we can make all elements odd • Otherwise, verify if all elements are already even Concepts Used: 🔹 Parity (Odd/Even Analysis) 🔹 Mathematical Observation 🔹 Greedy Logic Key Insight: 🔹 Subtracting numbers preserves or changes parity in predictable ways. 🔹 The smallest element plays a crucial role in determining whether all elements can be transformed into the same parity. Complexity: 🔹 Time: O(n) 🔹 Space: O(1) #LeetCode #Algorithms #DataStructures #CodingInterview #100DaysOfCode #SoftwareEngineering #Python #ProblemSolving #LearningInPublic #TechCareers

✅ Day 88 of 100 Days LeetCode Challenge Problem: 🔹 #1252 – Cells with Odd Values in a Matrix 🔗 https://lnkd.in/g5eE9A-e Learning Journey: 🔹 Today’s problem focused on simulating row and column increment operations on a matrix. 🔹 I initialized an m × n matrix with all zeros. 🔹 For each index [ri, ci], I incremented: • All elements in row ri • All elements in column ci 🔹 After applying all operations, I traversed the matrix to count how many cells contain odd values. Concepts Used: 🔹 Matrix Simulation 🔹 Nested Loops 🔹 Conditional Counting 🔹 Basic Array Manipulation Key Insight: 🔹 Direct simulation works efficiently due to small constraints. 🔹 Each operation affects an entire row and column, so tracking increments carefully is key. Complexity: 🔹 Time: O(m × n + k × (m + n)) 🔹 Space: O(m × n) #LeetCode #Algorithms #DataStructures #CodingInterview #100DaysOfCode #Python #ProblemSolving #LearningInPublic #TechCareers

✅ Day 75 of 100 Days LeetCode Challenge Problem: 🔹 #415 – Add Strings 🔗 https://lnkd.in/gHVN5VfP Learning Journey: 🔹 Today’s problem required adding two numbers represented as strings without directly using built-in conversion functions. 🔹 I implemented a helper function to convert a string into its numeric value by iterating through digits and multiplying them with the correct powers of 10. 🔹 After converting both strings to integers, I performed the addition. 🔹 Then, I converted the result back into a string by extracting digits using modulo (%) and reversing the constructed list. Concepts Used: 🔹 String to Number Conversion 🔹 Mathematical Digit Handling 🔹 Modulo & Division 🔹 String Construction Key Insight: 🔹 Manually converting between string and integer helps understand how numbers are built and processed internally. 🔹 Constructing the result in reverse and then reversing it ensures correct digit order. Complexity: 🔹 Time: O(n + m) 🔹 Space: O(n + m) #LeetCode #Algorithms #DataStructures #CodingInterview #100DaysOfCode #SoftwareEngineering #Python #ProblemSolving #LearningInPublic #TechCareers