Analyzing TDS distribution in Hensell Sand formation with Python

LeetCode #98 – Validate Binary Search Tree | Python Implementation I implemented a recursive DFS approach with boundary tracking to validate BST properties. Core Insight: BST validation requires tracking allowable ranges, not just comparing immediate children. Each recursive call narrows the valid interval, ensuring global ordering throughout the entire subtree. Time: O(n) | Space: O(h) where h = tree height (recursion stack) #LeetCode #DataStructures #Python #BinarySearchTree #Recursion #DFS #CodingInterview #SoftwareEngineering

Raw data is rarely ready for analysis. After ingestion comes wrangling: filtering the rows you need, selecting the right columns, standardising formats, and verifying the result before moving on. Episode 4 of the Practical Learning Series covers a simple four-step workflow in Python, with working code and the mistakes to avoid. Because the quality of your analysis depends on the quality of your preparation. Swipe through → #DataScience #Python #PracticalLearning #DataWrangling #DataManagement #DSI

Over the past week I've been learning Computer Vision in Python. As a capstone, I developed a program using mediapipe and pycaw to create a volume control tool using the distance between hand landmarks. The code is available at: https://lnkd.in/egcbjxav #ComputerVision #OpenCV #Python #Innovation #AIProjects #Mediapipe

🤜 Python Challenge #2 – Answer Revealed! b = a does not create a new list. It simply makes b reference the same list object in memory as a. When we do: a += [4] Python modifies the list in-place instead of creating a new one. Since both a and b point to the same list, the change appears in both variables. #Python #PythonLearning #CodingChallenge #100DaysOfCode #LearnPython

Day 12/100 – #100DaysOfCode 🚀 Solved LeetCode #217 – Contains Duplicate (Python). Today I worked on an array problem to determine whether any value appears at least twice in the array. Approach: 1) Sort the array first. 2) Traverse through the array from index 0 to n-2. 3) Compare each element with the next element. 4) If two adjacent elements are equal, a duplicate exists. 5) If no duplicates are found after traversal, return False. Time Complexity: O(n log n) due to sorting Space Complexity: O(1) Understanding how sorting can simplify duplicate detection in arrays 💪 #LeetCode #Python #DSA #Arrays #ProblemSolving #100DaysOfCode

LeetCode #104 – Maximum Depth of Binary Tree | Python Implementation I implemented a recursive DFS approach that calculates tree depth by taking the maximum of left and right subtree depths plus one for the current node. Core Insight: Depth calculation decomposes naturally into subproblems. Each node's depth is determined by its deepest child, making recursion the cleanest solution with minimal code. Time: O(n) | Space: O(h) where h = tree height (recursion stack) #LeetCode #DataStructures #Python #BinaryTree #Recursion #DFS #CodingInterview #SoftwareEngineering

🚀 Day 25 — DSA + Python Today I practiced Array Rotation problems. ✅ Learned: Left rotation Right rotation Rotation by K positions 💡 Understood the logic of shifting elements and how to think about better approaches instead of brute force. Practicing arrays is helping me build stronger problem-solving skills in DSA. #DSA #Python #CodingJourney #100DaysOfCode

Python to Python in seconds Learn how tuples work with order and indexing to create powerful data elements. Discover the role of tuples in data storage and transfer, and how they differ from lists and sets in Python. Read the full article 👉 https://lnkd.in/dsvjjhch #PythonTuples #LearnPython #ITFreshers #DataStructures #PythonFundamentals #TechLab Code. Learn. Build. — TechLab by Neeraj

Searching through large datasets doesn’t have to be slow. This guide explains how binary search works in Python, how to implement it, and where it’s most useful. https://lnkd.in/gFT4BuYp

Day 10/100 – #100DaysOfCode 🚀 Solved LeetCode #66 – Plus One (Python). Today I worked on an array manipulation problem that simulates adding one to a large integer represented as a list of digits. Approach: 1) Traverse the array from the last digit to the first. 2) If the current digit + 1 is not equal to 10, simply increment it and return the array. 3) If the digit becomes 10, set it to 0 and carry over to the next digit. 4) If the carry reaches the first digit, add 1 at the beginning of the array. Time Complexity: O(n) Space Complexity: O(1) Understanding how carry propagation works in arrays 💪 #LeetCode #Python #DSA #Arrays #ProblemSolving #100DaysOfCode