Writing a Python program to check loan eligibility using if-else statements

✅Day 83 of #100DaysOfLeetCode 1.📌Problem: Find the Pivot Integer Given a positive integer n, find the pivot integer 𝑥 such that the sum of all elements between 1 and 𝑥 inclusively equals the sum of all elements between 𝑥 and n inclusively. Return the pivot integer 𝑥. If no such integer exists, return -1. 2.🟢 Difficulty: Easy 3.📍Topic: Arithmetic & Basic Reasoning 4.🎯 Goal: Identify the integer x where the sum of numbers before and after (including) 𝑥z are equal for a given range.image.jpg 5.🧠Key idea: Approach 1: Find the total sum of numbers from 1 to n using 𝑛(𝑛+1). Incrementally compute the prefix sum from 1 up to 𝑖 and compare it with the suffix sum from 𝑖 to n. If prefix sum equals suffix sum for any i, that 𝑖 is the pivot integer; otherwise, return -1. #LeetCode #100DaysOfCode #CodingChallenge #Programming #DataStructures #Algorithms #CodingJourney #LearningJourney #GrowthMindset #ProblemSolving #DeveloperCommunity #Python #Java #SoftwareEngineering #TechCareersbest

🗓 Day 10 / 100 – #100DaysOfLeetCode 📌 Problem 3228: Maximum Number of Operations to Move Ones to the End The task was to determine the maximum number of operations needed to move all '1's in a binary string to the end, given specific operation rules. 🧠 My Approach: Traversed the string while keeping track of the total count of '1's seen so far. Whenever a '10' pattern appeared, added the current count of '1's to the total operations. This ensured that each move was counted optimally without unnecessary shifts or recomputation. ⏱ Time Complexity: O(n) 💾 Space Complexity: O(1) 💡 Key Learning: This problem reinforced the value of pattern-based logic and prefix counting — powerful techniques for problems involving strings or sequences. It also highlighted how thinking in terms of transitions (1→0) can simplify seemingly tricky problems. Ten days down, ninety to go 🚀 #100DaysOfLeetCode #LeetCodeChallenge #Python #ProblemSolving #Strings #LogicBuilding #DataStructures #Algorithms #DSA #CodingJourney #CompetitiveProgramming #SoftwareEngineering #LearningInPublic #DeveloperJourney #TechStudent #CodingCommunity #CareerGrowth #CodeEveryday #Optimization #KeepLearning #Programming

🔥 Day 24 String Patterns & Prefix Power 💪 Today’s DSA session was all about smart scanning and pattern precision decoding strings from both ends like a pro 🧠 🔹 LeetCode 1903 Largest Odd Number in a String We learned to scan from right to left to grab the largest possible odd substring mastering substring slicing and number logic in one go. A simple yet powerful trick in string + math hybrid problems ⚡ 🔹 LeetCode 14 Longest Common Prefix We revisited a classic finding the common thread across multiple strings! Perfect practice for pattern alignment and character-wise comparisons 🧩 💡 Strings may look simple but they hide some of the most elegant problem-solving patterns in all of coding. What’s your go-to trick when solving string questions slicing, pointers, or brute force? 👇 #Day24 #100DaysOfCode #LeetCode #StringProblems #CodingJourney #ProblemSolving #DSA #LearnToCode #TechCommunity #Python #Programming #CodingChallenge #DSA90WithSUUMIT #DSA90 #FullStack #Strings #DEV

The __del__( ) method is called a destructor. It perform clean up actions when the object is destroyed. ```python class A:   def __init__(self,s):       self.x=s   def __del__(self):          print("inside destructor")   def f2(self):     self.a=self.x+10     print("a=",self.a) obj=A(100) obj.f2( ) ``` #Output: inside destructor a= 110 #Python #OOPs #Programming #Learning #Coding

🗓 Day 14 / 100 – #100DaysOfLeetCode 📌 Problem 1437: Check If All 1’s Are at Least K Places Away The goal was to determine whether every pair of consecutive 1s in the array is separated by at least k zeros. 🧠 My Approach: Traversed the array while tracking the index of the previous 1. On encountering a new 1, checked the distance from the last one. If the gap was smaller than k, the condition failed instantly. This single-pass logic keeps the solution efficient and clean. 💡 Key Learning: This problem reinforced the importance of index tracking and using simple arithmetic comparisons to validate structural constraints. It’s a great reminder that not all problems require heavy algorithms — sometimes, clarity and careful traversal are enough for an optimal solution. Small steps forward build strong reasoning over time 🚀 #100DaysOfLeetCode #LeetCodeChallenge #Python #ProblemSolving #LogicBuilding #Arrays #Algorithms #DataStructures #DSA #CompetitiveProgramming #CodingJourney #SoftwareEngineering #LearningInPublic #DeveloperJourney #TechStudent #CareerGrowth #CodeEveryday #CodingCommunity #KeepLearning #Programming #TechCareer

🚀 LeetCode Daily Challenge 📘 Problem: Implement Stack using Queue (LeetCode #225) Today, I implemented a stack (LIFO) using a single queue (FIFO) — a classic problem that strengthens understanding of data structure manipulation. 💪 Key learning points: Efficiently rotating elements in a queue to simulate stack behavior Mastering core operations: push, pop, top, and empty Reinforcing how data structure constraints lead to creative solutions #LeetCode #DataStructures #Python #DSA #Learning #Programming #TechJourney #Queue #Stack

💡 Day 64 of #LeetCode365 Problem: 338. Counting Bits Category: Bit Manipulation | Dynamic Programming Today’s problem was all about counting 1s in binary numbers — basically, checking how “on” each number is 💡😅 💻 Approach: 👉 Use a DP array ans to store counts of 1s for each number. 👉 For each number: If it’s even ➡️ same count as i/2 If it’s odd ➡️ one more than (i−1) ans = [0, 1, 1] for i in range(3, n + 1): if i % 2 == 0: ans.append(ans[i // 2]) else: ans.append(ans[i - 1] + 1) return ans[:n + 1] ⚙️ Complexity: ⏱ O(n) | 💾 O(n) 💡 Lesson: Bits are like people — some are off, some are on, but together, they make the system work 😎💻 #LeetCode #Python #DynamicProgramming #BitManipulation #CodingHumor #100DaysOfCode #FunnyCode

🚀 Day 54 of #100DaysOfCode Solved LeetCode Problem 2011. Final Value of Variable After Performing Operations ✅ This problem tests simple yet essential programming logic — understanding how pre/post increment and decrement operations affect variable states. Given a list of operations like ["--X", "X++", "++X"], the goal is to compute the final value of X after applying all updates sequentially. 💡 Key Insight: Each operation (++X, X++) increases the value by 1, while (--X, X--) decreases it by 1. The implementation can be efficiently handled in O(n) time by iterating through the operations once. ⚙️ Result: Runtime: 0 ms ⚡ Beats 100% of Python submissions Memory Usage: 17.76 MB (Beats 60.70%) Another step forward in improving my algorithmic problem-solving and code optimization skills 💪 #LeetCode #Python #100DaysOfCode #CodingJourney #ProblemSolving #DailyPractice #TechLearning #MythylyCodes

🔺 Day 61 of #LeetCode365 Problem: 119. Pascal’s Triangle II Category: Array | Math | Dynamic Programming Today’s problem felt like déjà vu — same triangle 🟰 smaller goals 😅 Instead of building the whole triangle, we just needed that one special row. Efficiency and focus — that’s the Pascal way 💼 💻 Approach: 👉 Start with the first row [1] 👉 Build each subsequent row using the previous one 👉 Each new row = [0] + prev + [0], then sum adjacent pairs 👉 Return only the last row — no extra baggage ✨ result = [[1]] for i in range(rowIndex): temp = [0] + result[-1] + [0] row = [] for j in range(len(result[-1]) + 1): row.append(temp[j] + temp[j + 1]) result.append(row) return result[-1] ⚙️ Complexity: ⏱ O(n²) | 💾 O(n²) 💡 Lesson: Sometimes you don’t need the whole pyramid — just the one row that takes you closer to the top 🔼 #LeetCode #Python #DynamicProgramming #CodingJourney #100DaysOfCode #FunnyCode #DSA

🚀 Day 4 – LeetCode Problem Solving Journey 💻 Today’s challenge was “Merge Sorted Array” (LeetCode #88) — a classic array manipulation problem that helps improve understanding of two-pointer techniques and in-place merging. Problem: You are given two sorted arrays, nums1 and nums2, and the task is to merge them into a single sorted array, stored inside nums1. Example: Input: nums1 = [1,2,3,0,0,0], m = 3 nums2 = [2,5,6], n = 3 Output: [1,2,2,3,5,6] 🧠 Concept Used: Two-pointer approach starting from the end Comparison and in-place insertion Time Complexity: O(m + n) Space Complexity: O(1) Learning how to handle in-place data modification efficiently is a key step in mastering DSA! #LeetCode #Day4 #ProblemSolving #DSA #CodingJourney #100DaysOfCode #Python #Programming #DevelopersCommunity #SoftwareEngineering #LearningInPublic #CareerGrowth