Binary Search Tree Node Structure in Python

🚀 Day 43 of My Coding Journey: Exploring Set Mutations in Python! Today, I worked on an interesting problem involving set mutation operations in Python — and it reminded me how powerful and flexible sets can be when handling data efficiently. 💡 Instead of just performing basic operations like union or intersection, mutation methods such as: 🔹 update() 🔹 intersection_update() 🔹 difference_update() 🔹 symmetric_difference_update() allow us to modify the original set directly, making our code more efficient and clean. ✨ One key takeaway: Understanding when to mutate vs when to create a new set can make a huge difference in performance and readability. 📌 Practicing problems like these strengthens logical thinking and prepares us for real-world data manipulation tasks. #Day43 #Python #Coding #ProblemSolving #DataStructures #LearningJourney #100DaysOfCode

🚀 Day 2/30 – Stack & Queue Implementation using Python 🐍📚 Continuing my 30 Days Python Challenge with one of the most important Data Structures fundamentals! Today, I built a Stack & Queue implementation in Python to strengthen my understanding of LIFO and FIFO concepts, along with how data flows in real-world applications 💻 What I focused on today: ✨ Implementing Stack operations: push, pop, peek ✨ Implementing Queue operations: enqueue, dequeue ✨ Strengthening DSA logic and problem-solving skills This challenge is all about consistency, learning in public, and becoming better every single day 🚀 👉 Would love your feedback! Day 3 coming tomorrow… stay tuned 👀 #Python #30DaysChallenge #PythonProjects #DataStructures #Stack #Queue #CodingJourney #LearnPython #BuildInPublic #ProblemSolving

Python Series — Day 1 Answer + Day 2 Question 🚀 🧠 Day 2 Question What will be the output of this code? a = [1, 2, 3] b = a b.append(4) print(a) Options: A. [1, 2, 3] B. [1, 2, 3, 4] C. Error D. Depends on Python version Drop your answer 👇 (And don’t Google 😄) Answer tomorrow 🚀 #Python #CodingChallenge #DataEngineering #LearningInPublic #Tech

🚀 Day 3 — Python Journey Today’s focus was on float operations in Python (working with decimal numbers). 📌 What I learned: Float declaration Addition, subtraction, multiplication, division Rounding values using round() Scientific notation Precision handling in floats 💡 What I found interesting: Float values are not always 100% accurate due to precision limitations. Even simple calculations can sometimes give unexpected results. Understanding this early is important, especially for real-world applications like finance or data science. Step by step, trying to build a strong foundation. #Day3 #Python #CodingJourney #LearnInPublic #Consistency

Today, I learned how to take user input in Python using the input() function. This allows programs to interact with users and collect data such as name, age, and city. I also learned how to convert input into numbers using int() and float(), which is very important for calculations and data processing. #Day2 #Python #LearningJourney #DataScience #MachineLearning #Consistency

🚀 Day 85 – Python + DSA Journey Today I focused on strengthening my fundamentals in Arrays and problem-solving using Python. 🔹 Topics Covered: • Array Traversal, Insertion, Deletion • Time Complexity (O(n), O(1)) • Problem-Solving Patterns 🔹 Problems Solved: ✅ Find Second Largest Element (Optimized O(n) approach) ✅ Reverse an Array (Two-pointer technique) ✅ Move Zeros to End (Efficient swapping logic) ✅ Two Sum Problem (Hashing concept) 💡 Key Learnings: • Importance of thinking in terms of patterns • Optimizing solutions without using sorting • Writing clean and efficient code for interviews Every day I’m getting better at breaking down problems and building logical solutions. 📌 Consistency is the key — one step closer to my goal every day! #Day85 #Python #DSA #CodingJourney #ProblemSolving#Learning #SoftwareDevelopment

🚀 Day 14 of My Python + DSA Journey Tried a different approach today and optimized my solution 👇 ✅ Majority Element II (#229) 💡 Majority Element II Find elements appearing more than n/3 times 🔍 Approach: Used Boyer-Moore Voting Algorithm → tracked candidates and validated counts ⏱ O(n) time | O(1) space 🔥 What I learned today: • Same problem can have multiple approaches • Optimization reduces space from O(n) → O(1) • Smart algorithms > brute-force thinking Learning to not just solve… but solve better ⚡ #Day14 #LeetCode #Python #DSA #CodingJourney #100DaysOfCode

This one NumPy concept saved me hours of coding 👇 👉 Vectorization Earlier, I used loops for almost everything in Python. It worked… but it was slow and messy. Then I discovered this: Instead of processing data element by element, NumPy lets you operate on the entire array at once. Example: Adding 10 to every number Before (Python list): → loop through each element Now (NumPy): → one single line That’s it. This small shift leads to: - faster execution - cleaner code - better performance on large datasets The real change is in thinking: ❌ Think in loops ✅ Think in operations on data That’s when NumPy actually starts making sense. If you’re learning NumPy, focus on this concept early. #NumPy #Python #DataScience #DataEngineering #MachineLearning #CodingJourney #TechLearning

𝗙𝗿𝗼𝗺 𝗱𝗮𝘁𝗮 𝘁𝗼 𝗶𝗻𝘀𝗶𝗴𝗵𝘁. 𝗦𝘁𝗮𝗿𝘁 𝗵𝗲𝗿𝗲. You don’t need to be a programmer to start using Python in your work. You just need to know where to begin. If you work with air quality data, Python helps you analyse it, visualise it, and turn it into insight you can use. We start simple and build from there. Join 𝗝𝗼𝗵𝗻 𝗜𝗻𝗻𝗶𝘀 for this introductory course focused on practical application using real air quality examples. You will work with data, build plots, and create simple tools you can use in your own work. No theory for the sake of it. Just capability you can use. 📅 𝟭𝟯, 𝟭𝟱, 𝟮𝟬 & 𝟮𝟮 𝗠𝗮𝘆 𝟮𝟬𝟮𝟲 🕛 𝟭𝟮.𝟬𝟬 – 𝟮.𝟬𝟬 𝗽𝗺 𝗔𝗘𝗦𝗧 💻 𝗢𝗻𝗹𝗶𝗻𝗲 👉 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗻𝗼𝘄 for 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝘁𝗼 𝗣𝘆𝘁𝗵𝗼𝗻: https://lnkd.in/gqW9piKb #AirQuality #Python #DataAnalysis #EnvironmentalScience #CASANZ

Day 32 / #120DaysOfCode – LeetCode Challenge Today’s focus: Arrays & Majority Voting Algorithm ✅ Problem Solved: • Majority Element II 💻 Language: Python 📚 Key Learnings: • Applied Boyer-Moore Voting Algorithm (extended version) • Learned how to track two candidates for n/3 majority • Understood the importance of validation step after candidate selection • Improved ability to handle edge cases in frequency problems Consistency builds confidence 🚀 Every day = 1% better 💪 🔗 LeetCode Profile: https://lnkd.in/gbeMKcv5 #LeetCode #Python #DSA #Arrays #Algorithms #Consistency #CodingJourney #120DaysOfCode