Trapping Rain Water | Leetcode | Explained with Python in Hindi

🌧️ Welcome to our coding tutorial on solving the intriguing "Trapped Rainwater" problem! 🌊 Imagine a mesmerizing landscape represented by a series of non-negative integers, each indicating the height of a bar. Picture the bars forming an elevation map, where the width of each bar is precisely 1 unit. Now, envision a heavy downpour of rain gracing this landscape. As the rainwater cascades down, valleys are formed between these bars, creating opportunities to store water. In this exciting coding session, we embark on a journey to unravel the secrets of computing how much water can be trapped within these valleys after the rain has ceased. Together, we'll explore a clever algorithm to efficiently calculate the trapped rainwater, making use of smart data structures and problem-solving techniques. Whether you're a beginner or a seasoned coder, fear not! Our friendly instructors will guide you through every step of the process, explaining the core concepts and logic behind the algorithm. We believe that understanding the "why" behind each solution is just as important as getting the "how" right! Throughout this tutorial, we'll use Python to implement the algorithm, allowing for clear and concise code demonstrations. By the end of the video, you'll be equipped with the skills to solve this fascinating problem on your own, and you'll gain valuable insights into tackling similar challenges in your coding journey. So, if you're ready to take on the "Trapped Rainwater" puzzle, hit that play button and let's dive into the world of elevation maps and water-trapping strategies. Don't forget to like, subscribe, and ring the notification bell to be the first to know about our upcoming coding adventures! Get ready for an exciting ride filled with knowledge, curiosity, and the joy of coding. See you in the video! 🌧️💡💻 Timecodes: 0:00 Understanding Problem Statement 3:33 Why two pointer is not the best approach 4:56 Running Maximum and Minimum Approach 7:00 Implementing Running Max and Min Approach