Implementing Insertion Sort in Python

🚀 Day-103 of Python Problem-Solving! Problem: Given a list of numbers, we wanted to: 1️⃣ Find the smallest prime in the list. 2️⃣ Multiply only the even numbers by that prime. 3️⃣ Keep the odd numbers unchanged. This exercise is a simple yet powerful way to combine mathematical logic with Python list operations. It helps strengthen problem-solving skills that are often asked in interviews and coding challenges. #Day103 #100DaysOfCode #PythonProgramming #PythonTips #CodingChallenge #ProblemSolving #LearnPython #TechLearning #PythonDevelopment #DataStructures #PythonPractice #CodeEveryDay

📌Python Sets – Intersection What is Intersection? It returns a new set containing only the elements that are common in both sets. ✅ Using intersection() method ✅ Using & operator (shortcut method) ✅ Result always contains unique common elements 🧩 Example: set3 = set1.intersection(set2) # or set3 = set1 & set2 🔎 Important Note: Sets can contain different data types. True and 1, False and 0 are considered the same values in sets. Understanding set operations helps in comparing and analyzing data efficiently #Python #PythonSets #DataAnalytics #LearningJourney #CodingPractice #Upskilling

🚀 Python Learning Journey – Revision Day Today, I revised Day 7, Day 8, and Day 9 topics to strengthen my fundamentals. Here’s what I revised: ✅ Functions (def, arguments, return values) ✅ Built-in string functions ✅ List built-in methods and functions Revision helped me understand concepts more clearly and confidently. Practicing consistently and building a strong foundation 💪 Small steps every day lead to big results. #Python #LearningJourney #Revision #Functions #Strings #Lists #KeepLearning

“Better features = better predictions. Here’s how I realized it.” I spent hours transforming and selecting features in my dataset. The impact was huge: • Improved model accuracy • Reduced overfitting • Revealed hidden patterns in data This taught me that algorithms matter less than meaningful features. 💬 What’s your go-to feature engineering trick? #DataScience #MachineLearning #FeatureEngineering #Python #Projects

Start strong: XGBoost 3.2.0 (Feb 2026) delivers major categorical re-coder updates and hardware compatibility, scaling predictive modeling effectively. Release: https://lnkd.in/gWiAbMEc In ML tasks, these broaden efficient training options. Following XGBoost 3.2.0? What stands out? #XGBoost #MachineLearning #Python #DataScience #AIProgress

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

One common Python interview question: ▫️What’s the difference between List and Tuple? 🔹 List → Mutable (can be modified) 🔹 Tuple → Immutable (cannot be modified) my_list = [1, 2, 3] my_tuple = (1, 2, 3) ▪️If your data will change → use List. ▪️If your data should stay constant → use Tuple. Simple concept. Big impact on performance, memory, and clean code decisions 👌. #Python #Programming #SoftwareDevelopment #DataScience #AI #LearningJourney

📌Python Sets – Symmetric Difference I learned about the Symmetric Difference operation in Python sets. 🧩What is Symmetric Difference? It returns a new set containing elements that are present in either of the sets, but NOT in both. ✅ Using symmetric_difference() method ✅ Using ^ operator (shortcut method) ✅ Common elements are automatically removed 🧩 Example: set3 = set1.symmetric_difference(set2) # or set3 = set1 ^ set2 🔎 Key Concept: 🔹It removes the common elements (intersection). 🔹It keeps only unique, non-overlapping values. Set operations are very useful for comparing and analyzing datasets efficiently #Python #PythonSets #DataAnalytics #LearningJourney #CodingPractice #Upskilling

👉 Question for you: How would you optimize this solution to avoid nested loops? 💡 Python Logic Problem – Find Two Numbers Whose Sum = 9 Today I practiced solving a small array problem in Python. Given a list of numbers: [2, 7, 11, 15, 6, 3] The task was to find two numbers whose sum equals 9. 🔹 Approach I Used: ✔️ Iterated through the list using nested loops ✔️ Compared each pair of numbers ✔️ Checked if their sum equals the target value (9) ✔️ Printed the matching pair 📚 Concepts Practiced: List indexing Nested loops Conditional logic Basic problem-solving approach Problems like this are common in coding interviews and data structure practice, so solving them helps strengthen logical thinking. Small improvements every day → Better programming skills 🚀 Let’s connect if you're also learning Python! #Python #PythonProgramming #CodingPractice #DataStructures #CodingInterview #LearnToCode #DeveloperJourney #100DaysOfCode #ProblemSolving

🚀 Python Learning Journey – Revision Day Today, I revised Day 10 and Day 11 topics to strengthen my understanding. Here’s what I revised: ✅ Tuples (immutability, count(), index(), built-in functions) ✅ Dictionaries (key–value pairs, adding, updating, removing elements) ✅ Dictionary methods like keys(), values(), items(), get(), update(), pop() Revision helped me clearly understand the differences between tuples and dictionaries. Strengthening fundamentals step by step 💪 Consistency continues! #Python #LearningJourney #Revision #Tuples #Dictionaries #Coding #KeepLearning