Python range() Function Tips for Efficient Coding

Today I learned about Lambda Functions in Python 🐍 A lambda function is a small, anonymous function written in a single line using the lambda keyword. It’s mainly used for: ✅ Short and simple operations ✅ Writing compact code ✅ Using inside functions like map(), filter(), and sorted() Example idea: Instead of writing a full function to square a number, we can do it in one line with a lambda function. Less code. Same logic. Cleaner style. Understanding these small tools really helps in writing more Pythonic and efficient code. Learning one concept every day 🚀 #Python #DataScience #LearningInPublic #Programming #100DaysOfCode #CareerSwitch

Picking up from yesterday's article by Yohann Mansiaux on R to Python package habits, this continuation is a practical toolkit for parity. The takeaway isn’t that ecosystems are identical, it’s that you can standardise dev ergonomics so R and Python packages feel consistent across teams. Curious how others are handling cross-language in practice, let me know how your teams are adapting. https://hubs.li/Q0411Dm20 #RStats #Python #OpenSourceTools #ReproducibleResearch #ClinicalDataScience

Most of the students have come across this doubt, so I thought it was worth sharing. Why do some Python or pandas methods work inside print() directly, while others don’t? The key difference is simple: Some methods return results, while others create objects that need an extra step. For example, groupby() doesn’t give final data, it prepares the data. Only after applying something like .mean() or .sum() do we get an output. I’ve noticed that once students understand what a function returns, Python suddenly feels much less confusing. Have you faced a similar “aha” moment while learning Python or pandas? #Python #Pandas #DataScience #LearningToCode #ProgrammingConcepts #TeachingPython #ComputerScience

Day 5 — #30DaysOfPythonWithKapil 🚀 Today I solved a Python problem: Armstrong Number The task was to: Read a number N and check whether it is an Armstrong Number or not. 👉 An Armstrong Number is a number where the sum of each digit raised to the power of total digits equals the number itself. Example: 1634 → --- What I practiced & understood today: ✅ ✔ Converting number to string for digit access ✔ Using len() to get total digits ✔ Applying power operation on each digit ✔ Looping through digits using for loop ✔ Strengthening logical thinking step-by-step Sharing my solution below 👇 (Attached code screenshot) This daily practice is really helping me understand logic + fundamentals more clearly. Small steps every day, but staying consistent 💪 Let’s keep learning and growing 🚀💻 #Python #CodingJourney #ArmstrongNumber #ProblemSolving #Consistency #LearnInPublic #LogicBuilding #FutureDataScientist

Here’s a clean, engaging Instagram description that perfectly matches this image and your 60 Days Python Series – Day 4 👌🐍 🔥 Day 4/60 – Python Series Today’s challenge: Remove vowels from a given string using Python 💻 This task helps you understand: ✔️ String traversal ✔️ Conditional logic ✔️ Clean function-based thinking Small programs like this build strong fundamentals that matter in interviews and real projects 🚀 📌 Save this post for revision 📌 Share with Python beginners 📌 Follow for the complete 60 Days Python Series 💬 Comment “day4” if you’re learning along 👇 #python #60dayspython #day4 #pythonprogramming #stringmanipulation #codinglogic #learnpython #beginnerscoding #programmingreels #techlearning

Python taught me something early on that applies far beyond code. The real power isn’t in writing clever lines — it’s in reducing complexity. Breaking a problem down, naming things clearly, and letting the structure do the work makes everything easier to reason about. I’ve learned that the best scripts are the ones future-you (or someone else) can understand instantly. That mindset has quietly improved how I approach problem solving overall. #Python #LearningInPublic #WorkflowAutomation

Had a great session on Introduction to Lists in Python 🐍 We discussed why lists are so important, how to create them, how indexing (including negative indexing) works, and explored some useful list methods. We also practice iterating over lists and solved a few questions together. The session had active participation and engaging discussions among the 3 of us 😅 (count doesn't matter, participation does), I am glad I could help clear doubts and make the concepts easier to understand 💡🙌 🔗 Here's the Colab link for you to practice the questions discussed during the session: https://lnkd.in/gu_G4VHV 📽️ Sharing the session recording here for anyone who wants to learn or revise: https://lnkd.in/gcUh_eys 🔗 GitHub Link for the assignments: https://lnkd.in/grGDz464 If you have any questions or suggestions, feel free to drop the in the comments - happy to connect and help! #Python #Learning #Teaching #PythonLists #ProgrammingBasics

Nested Loops = Power + Responsibility Today I learned how loops inside loops actually work, and when not to use them. • Domino tiles → generating unique combinations • Team pairings → home vs away (no team vs itself) • One extra loop can turn seconds into hours 💡 Lesson: Nested loops are powerful, but only when the problem truly needs them. Learning Python beyond syntax, thinking in logic #Python #LearningInPublic #Coding #DeveloperJourney #Coursera

Day 3/100 – #100DaysOfPython 🐍 Today was focused on revising and practicing some important Python concepts. What I revised & practiced today: • Functions (parameters, return values) • Recursion • Logic-based practice questions Working on recursion again reminded me how important it is to think in terms of base cases and smaller subproblems. Key takeaway: Progress comes from showing up daily. Even 1% better practice each day builds strong problem-solving skills over time. Consistency > Motivation 🚀 #Python #100DaysOfCode #LearningInPublic #BTech #ProblemSolving #CodingJourney

Python Lists: When Single Values Aren’t Enough int, float, and string felt powerful, until I realized real programs work with collections. That’s where lists shine 👇 🔹 Store multiple values in one variable 🔹 Access items with indexing (starts at 0) 🔹 Use len() to count elements 🔹 Check existence with in 🔹 Slice lists just like strings (list[1:3]) 💡 Best part? If you understand strings, you already understand lists. Same rules. Same logic. More power. One concept learned → many doors unlocked #Python #LearningInPublic #ProgrammingBasics #VSCode #DeveloperJourney