Divide Array into Subarrays with Min Cost: LeetCode 3010 Solution

Python Clarity Series – Episode 9 Topic: Dictionary get() vs Direct Access 📌 Why does this code crash sometimes? d = {"a": 10} print(d["b"]) Error ❌ KeyError Better way: print(d.get("b")) Output: None 👉 d["key"] → Throws error if key missing 👉 d.get("key") → Returns None (safe access) 💡 Smart Tip: Use .get() when key might not exist. In real-world coding, this prevents crashes. This is beyond exam — this is practical Python. Have you used .get() before? #PythonTips #CodingClarity #FutureProgrammers

Day 14 of my #100DaysOfCode challenge 🚀 Today I worked on a Python program to find the common elements between two lists using sets. The goal was to solve the problem efficiently without using nested loops. What the program does: • Takes two lists as input • Converts both lists into sets • Uses set intersection to find common elements • Converts the result back into a list • Prints the common elements How the logic works: Two lists are defined with numeric values Both lists are converted into sets using set() The intersection operator & is used to find common elements The resulting set is converted back into a list The final list of common elements is displayed Example: List 1:[1, 2, 3, 4, 5] List 2:[4, 5, 6, 7, 8] Output: Common elements:[4, 5] Key learnings from Day 14: – Understanding set operations in Python – Using intersection (&) efficiently – Avoiding nested loops for better performance – Writing clean and optimized code #100DaysOfCode #Day14 #Python #PythonProgramming #SetOperations #DataStructures #ProblemSolving #CodingPractice #LearnByDoing #ComputerScience #BTech #CSE #AIandML #VITBhopal #TechJourney

🚀 pandas 3.0 is here! The long-awaited major release brings game-changing improvements: ✨ Dedicated string dtype by default, better type safety & performance ✨ Copy-on-Write (CoW), consistent copy/view behaviour, no more SettingWithCopyWarning ✨ Improved date time handling, microsecond resolution, avoiding out-of-bounds errors Read on for more: https://lnkd.in/eUzg9mEH #Pandas #Python #DataScience #Pandas3

📘 Day 15 of my #90DaysPythonChallenge Topic: Recursion Today, I explored recursion in Python and learned how functions can call themselves to solve problems step by step. 🔹 Practiced recursive functions 🔹 Worked on factorial, sum of numbers, and Fibonacci 🔹 Understood the importance of base cases Recursion helped me think differently about problem-solving and breaking problems into smaller parts. 📂 Practice code available on GitHub: https://lnkd.in/dnNfeh_f #Python #90DaysPythonChallenge #LearningInPublic #CodingJourney #Recursion

🚀 DSA 150 – Day 1 🧩 Leet code 217: Contains Duplicate Today I solved Contains Duplicate using Python. 🔎 Problem Summary: Given an integer array of nums, return True if any value appears at least twice, otherwise return False. 📚 Topics Covered: Arrays HashSet (using Python set) 💡 Key Learning: Instead of using nested loops (O(n²)), I used a HashSet to track seen elements while iterating once through the array. This reduced the time complexity to O(n) with O(n) space. Every small step builds stronger fundamentals. On to Day 1 💪🔥 #DSA #Python #Leet code #Problem solving #Coding journey

Weekly Challenge 4: Binary Search (Iterative). Why search harder when you can search smarter? Use Binary Search. Imagine looking for a word in a dictionary. Do you read every page from the beginning? No. You open it in the middle and decide: "Left or Right?". That is the essence of Binary Search, and it's the focus of my coding challenge for Week 4. The Implementation: I wrote a Python script (using NumPy) that generates a random environment to test the algorithm. Key Takeaway: While a simple loop (Linear Search) checks elements one by one ($O(n)$), Binary Search cuts the problem in half with every step ($O(\log n)$). Check out the trace in the console output below to see how few attempts it takes to find the target! 👇 📂 Full code on GitHub: https://lnkd.in/ezPaaiDM #Python #BinarySearch #Algorithms #CodingChallenge #DataStructures #Engineering

Headline: Stop writing loops to clean your data. 🛑 One of the most common tasks in Python is handling duplicate entries. While you could write a for-loop with a conditional check, there’s a much faster, more "Pythonic" way to do it: Sets. Sets are unordered collections of unique elements. By casting your list to a set, Python handles the heavy lifting of deduplication instantly. Why use this? ✅ Cleaner, more readable code. ✅ Better performance for large datasets. ✅ Built-in membership testing (O(1) complexity). How are you using Sets in your current workflow? Let’s discuss below! 👇 #PythonProgramming #Pyspiders #CodingTips #SoftwareDevelopment

🧩 Problem: Remove Element (LeetCode #27) 💡 Concept Learned: This problem is a classic application of the Two Pointers technique. Instead of removing elements (which causes index shifting and bugs), we modify the array in-place by overwriting valid elements. 🔍 Key Insight: Maintain a pointer k to track the position of the next valid element. While traversing the array, whenever an element is not equal to val, place it at index k and move k forward. At the end, k represents the count of elements not equal to val. 🎯 Key Takeaway: In-place array problems often don’t require deletion. Overwriting elements is more efficient and avoids unnecessary shifts. Understanding how pointers move is crucial for solving such problems. 📈 Slowly building confidence by solving one problem at a time and learning from mistakes. #DSA #LeetCode #100DaysOfCode #TwoPointers #ProblemSolving #Python #CodingJourney #LearningInPublic #CodeNewbie

Day 4 of my Python Journey: Making data types play nice! 🐍 Today was all about Type Casting. In Python, data doesn't always arrive in the format we need. I spent today learning how to manually convert data types to keep my code running smoothly. What I covered: Implicit vs. Explicit Conversion: Letting Python do the work vs. taking control myself. The Big Three: Using int(), float(), and str() to bridge the gap between user input and mathematical operations. Common Pitfalls: Why you can't just turn "Hello" into an integer (and how to handle those errors). It’s a simple concept, but it’s the "glue" that holds more complex logic together. Onward to Day 5! #Python #CodingNewbie #100DaysOfCode #DataScience #TechLearning

🚀 Day 11/30 – Defining & Calling Functions in Python Today, I learned how to write cleaner and smarter code using functions. Instead of repeating the same logic multiple times, we can define it once and reuse it whenever needed. That’s powerful. 📌 What I practiced: • Defining a function using def • Calling the function • Passing values (arguments) • Returning results Here’s a simple example I built today: . 💡 Key Takeaway: Functions make programs organized, efficient, and professional. Small concept. Big impact. Day 11 complete ✅ #Python #30DaysChallenge #LearningInPublic #ProgrammingJourney #Consistency Aditya ChaturvediJECRC UniversityYash Raj ChoudharyRaj Gehlot