Two Sum Problem Solution in Python

🚀 Day 2 – DSA Series Remove Duplicates from Sorted Array Solved LeetCode 26 – Remove Duplicates from Sorted Array using Python. 🧠 Problem Summary Given a sorted array nums, remove duplicates in-place such that each unique element appears only once. Return the number of unique elements k, where: • The first k elements of nums contain the unique values • The remaining elements beyond k don’t matter • No extra array allowed (O(1) space) Example: Input: [1, 1, 2] Output: k = 2 → Modified array: [1, 2, _] 💡 Approach Used (Two Pointer Technique) Since the array is sorted, duplicates are adjacent. ✔️ Initialized k = 1 (first element always unique) ✔️ Iterated from index 1 ✔️ Compared current element with previous element ✔️ When a new unique element is found: • Placed it at index k • Incremented k This ensures in-place modification without extra space. ⏱ Complexity Analysis Time Complexity: O(n) – single pass Space Complexity: O(1) – no additional data structures 🔎 Key Takeaway This problem strengthens: • Two Pointer pattern • In-place array manipulation • Understanding problem constraints carefully Continuing the DSA series — one problem at a time. 🚀 #DSA #LeetCode #Python #Algorithms #TwoPointers #ProblemSolving #CodingJourney

🚀 Day 4 – DSA Daily Series Move Zeroes (LeetCode 283) using Python. 🧠 Problem Given an integer array nums, move all 0’s to the end of the array while maintaining the relative order of the non-zero elements. Important constraints: • The operation must be done in-place • No extra array should be created Example: Input: nums = [0,1,0,3,12] Output: [1,3,12,0,0] 💡 Approach Used the Two Pointer technique. • Maintain a pointer k to track the position for the next non-zero element • Traverse the array using index i • Whenever a non-zero element is found, swap it with the element at position k • Increment k This ensures: • Non-zero elements move to the front • Zeros automatically shift toward the end ⏱ Complexity Time Complexity: O(n) – single pass through the array Space Complexity: O(1) – in-place modification 🔎 Key Learning This problem helps strengthen: • Two Pointer pattern • In-place array manipulation • Maintaining relative order while rearranging elements Consistency is key when practicing DSA — solving one problem at a time. 🚀 #DSA #LeetCode #Python #Algorithms #ProblemSolving #CodingJourney

🔢 Exploring the change of numbering base 🧪 🤔 Thinking about binary numbers, I went back to the question of change of numbering base. In fact, I recently found out that the python function ìnt()`admits an optional argument that is interpreted as the basis in the representation we are introducing, and the function returns the decimal representation. For example: int('a', base=16) # returns 10 int('f', base=16)  # returns 15 I wanted to write a function that allows us to transform the numerical basis not just to decimal, but from binary to octal... or whatever you want. Interestingly, the algorithm that it occurs to me has to transform to decimal base as a middle step. 🤯 I wrote a whole post about it in my blog, the code is there with some explanations. Find the link 🔗 in the first comment. #mathematics #numbers #fun #python #binary #ternary #decimal #hexadecimal #octal ... and more!!!

Built an interactive #machine #learning Lab for my CE4/6/8910 course — runs entirely in the browser (zero installs). Students pick a dataset, choose an #algorithm, tune hyperparameters, and train live. There's also a full #Python Lab powered by Pyodide (WebAssembly) where they can write numpy, pandas, and sklearn code against the same data. The 30-second #demo below shows the full workflow. Download (html, works in browser): https://lnkd.in/eZFzPXAX #MachineLearning #EngineeringEducation #AI #Python #WebAssembly

INSTEAD OF WASTING TIME AND TRYING TO GET FIGURES. WHY NOT USING CODE?? Sometimes, lecturers or organizations need to generate different sets of questions for multiple candidates, especially when working with matrices. However, this often requires a lot of manual effort and can be time-consuming. Why not simplify the process using NumPy in Python? With just a few lines of code, you can easily generate multiple variations of matrix-based questions efficiently and save valuable time. #randint is an inbuilt function of the random module of numpy #Syntax: np.random.randint(start, stop (rows, columns)) a=np.random.randint(2,30, (3,3)) b=np.random.randint(2,30, (3,3)) c=np.random.randint(2,30, (3,3)) d=np.random.randint(2,30, (3,3)) e=np.random.randint(2,30, (3,3)) #DataScience #Python #NumPy #Education #Automation

Most Python workflows rely on heuristics. They’re quick, intuitive, but usually not optimal. A simple greedy approach might get you a solution, but it often leaves efficiency, performance, and cost savings on the table. GAMSPy brings algebraic modeling into Python, so you can express constraints and objectives directly and solve for a true optimum. At PyConDE & PyData 2026, Justine Broihan and Muhammet Soyturk will walk through this using a classic operations example, and then extend it into machine learning. They'll cover: 🔸 How optimization compares to rule-based heuristics and 🔸 How it can be used to test ML models (e.g. minimal changes needed to trigger misclassification) 🔸 The Art of the Optimal: A Pythonic Approach to Complex Decision-Making 📍 April 14 · 16:30 📍 Platinum (2nd Floor) If you're building decision-making systems in Python, this is worth a look. More details 👉 https://lnkd.in/dyifGdVi #PyConDE #PyData #Optimization #GAMSPy #GAMS #Python

Day 25 – divmod() print(divmod(10, 3)) Use: Quotient & remainder Content: Used divmod() to get quotient and remainder. Useful in math logic. #Python generate like a cartoon style image Image created Generated image Generated image Generated image Share Gulive description to post in. Linked in Here’s a clean LinkedIn-ready description for your post: 🚀 Day 25 of #30DaysOfCode – Learning divmod() in Python Today I explored the divmod() function in Python. print(divmod(10, 3)) 🔹 divmod() returns both the quotient and remainder in a single step. 🔹 Output: (3, 1) 🔹 It combines the functionality of // (floor division) and % (modulus). This function is especially useful in mathematical logic, time calculations, and problem-solving scenarios where both values are needed together. Small functions, big impact! 💡 #Python #PythonBasics #CodingJourney #LearnToCode #Programming #30DaysOfCode

🚀 Day 54 of #100DaysOfCode 🧩 Problem: Minimum Number of Flips to Make the Binary String Alternating Today I solved an interesting problem involving string manipulation, rotations, and sliding window techniques. 💡 Key Idea: An alternating binary string can only follow two patterns: • "010101..." • "101010..." Since the problem allows rotating the string (moving the first character to the end), the trick is to consider all rotations efficiently. 🔑 Optimization Trick: Instead of rotating the string repeatedly, we can concatenate the string with itself ("s + s") and use a sliding window of size "n" to simulate all rotations. Then we compare each window with both alternating patterns and count the minimum flips required. ⚡ Concepts Used • Sliding Window • Greedy Thinking • String Pattern Matching • Optimization Trick ("s + s" rotation) 💻 Language: Python This problem was a great exercise in thinking about string rotations and pattern mismatches efficiently in O(n) time. 📈 Consistency is the key to improving problem-solving skills! #LeetCode #CodingChallenge #Python #DataStructures #Algorithms #ProblemSolving #100DaysOfCode

DSA Tip: Bubble Sort If you’re comparing every pair of items in a list manually to sort them… there’s a better way. Use Bubble Sort. It repeatedly swaps adjacent elements to “bubble” the largest (or smallest) values to the end of the list. No complicated indexing. No extra storage. Just step-by-step, reliable sorting. Insight: Even simple algorithms like Bubble Sort teach us how repeated small steps lead to order and efficiency. FOLLOW FOR MORE DSA TIPS & INSIGHTS #DSA #Python #BubbleSort #CodingTips #LearnToCode

LeetCode Problem 1758: "Minimum changes to make alternating binary string": You are given a string s consisting only of the characters '0' and '1'. In one operation, you can change any '0' to '1' or vice versa. The string is called alternating if no two adjacent characters are equal. For example, the string "010" is alternating, while the string "0100" is not. Return the minimum number of operations needed to make s alternating. Approach: Here are two possibilities, first do not make change in the 1st character and apply rules following it, second consider step of changing the very first character and apply rules following it. The below implementation in Python works on this principle only, simple and straightforward. #Python #LeetCode #Strings #OptimalSolution #CompetitiveProgramming #DataStructures #Algorithms #ProblemSolving