Apurv Prajapati’s Post

🚀 Python Practice – Function Examples Taking my Python learning a step further by practicing real-world function-based problems 🐍 In this session, I worked on: ✔️ Temperature Conversion (Celsius ↔ Fahrenheit) ✔️ Password Strength Checker ✔️ Shopping Cart Total Cost Calculator ✔️ Palindrome Checker ✔️ Factorial using Recursion These examples helped me understand how functions can be used to solve practical problems and write reusable, structured code. A big thanks to Krish Naik Sir for his amazing teaching and clear explanations 🙌 Documented all my practice in a Jupyter Notebook and shared it as a PDF to track my progress. Learning by building real logic step by step 📊 #Python #Functions #Practice #LearningJourney #DataAnalytics #Coding

Dataclasses - stop writing boring classes. A complete guide · from basics to production patterns You have been writing __init__, __repr__, and __eq__ by hand. Python has had a better way since 3.7. If you haven't switched to dataclasses yet — this post is for you. 👇 #Python #PythonTips #CleanCode #Programming #LearnPython #SoftwareDevelopment #OOP #CodeQuality #PythonicProgrammer

🚀 Day 2/100 – Python & DSA Journey Today I focused on applying basics to a real problem. 🔹 Problem: Find the area of a triangle Instead of just memorizing the formula, I implemented it using Python by taking user input and performing calculations. Formula used: Area = (1/2) × base × height What I learned today: ✔ How to take multiple inputs from the user ✔ Converting input into the correct data type (float) ✔ Performing mathematical operations in Python ✔ Writing cleaner output using f-strings This may look simple, but it’s helping me build the foundation for problem solving.

Learn predictive modeling with Python and Scikit-Learn. Build accurate models and drive business success with our comprehensive guide. #PredictiveModeling Read the full article

🔁 Python Fundamentals Revision Continuing my Python revision to strengthen core concepts 🐍 In this session, I focused on: ✔️ Syntax & Semantics ✔️ Variables ✔️ Data Types ✔️ Operators Revisiting these fundamentals is helping me improve code clarity and avoid common mistakes. I’ve documented my practice in a Jupyter Notebook and shared it as a PDF to keep track of my learning journey. Strong basics = Better problem solving 💡 Next step: diving deeper into control flow and real-world problem solving 🚀 #Python #Revision #Programming #DataAnalytics #LearningJourney #Coding

At this point, Python is starting to feel less like a language… and more like a toolkit. Today’s Python MahaRevision 🧠 Chapter 13: Advanced Python (Part 2) This chapter introduced some really powerful and practical concepts: → Virtual environments → pip freeze (managing dependencies) → Lambda functions → bin() method → format() function → map, filter, reduce It’s interesting how these tools make code shorter, cleaner, and more efficient—once you understand how to use them properly. Practice set done: Worked on applying lambda functions, transforming data using map/filter, experimenting with reduce, and managing environments and dependencies. Some concepts felt a bit abstract at first (especially map/filter/reduce)… but with practice, they started making more sense. Biggest takeaway: Better tools don’t just make coding easier—they change how you think about solving problems. Still exploring, still improving. #Python #LearningInPublic #CodingJourney #Programming #AdvancedPython

This year I'm writing a new #Python series, and my first article is now live on roadmap.sh! "Python Division: Operators, Floor Division, and Examples" explores some of the most commonly used (and sometimes misunderstood) parts of Python division, including: ✨ The difference between / and // ✨ Practical, real-world examples like rate calculations and pagination ✨ Common pitfalls such as the dreaded ZeroDivisionError 😱 I'm looking forward to sharing more insights through this series and diving into some of the stranger things that can happen in Python. 👀 If you're learning Python or looking to sharpen your fundamentals, stay tuned! 🔗 https://lnkd.in/eMgm6W6C #Programming #Coding #SoftwareDevelopment #LearnToCode

Day 1 of learning NumPy. I thought it was just a faster Python list. Nope. NumPy arrays store only one data type — that's why they're blazing fast. And this blew my mind: my_list + 5 → Error my_array + 5 → Adds 5 to everything instantly No loops. No extra code. Just math. Day 1 and I'm already Cooked. #NumPy #Python

In this tutorial, we will show how to use Python in Excel and when and how it’s useful. Instead of switching to other tools like Jupyter or VS Code, you can use Python directly in Excel. https://lnkd.in/e_QdRFzk

Python String Methods: file names, user input, APIs, data cleaning, logs. If you work with Python, these 10 string methods aren’t optional — they’re daily tools. You’ll use them for: - cleaning extra spaces. - checking file extensions. - splitting and joining data. - finding and counting characters. These methods help you write cleaner, shorter, and more readable code. If you ever forget the syntax, this one image is enough to refresh your memory. Save it — future you will thank you. #Python #LearnPython #PythonTips #Programming #Coding #SoftwareEngineering #PythonDeveloper