🚀 Day 18–24 of My Python Learning Journey Over the past few days, I’ve been diving deeper into Python and strengthening my core concepts 💻 Here’s what I explored 👇 🔹 Functions & Arguments 🔹 Types of Variables (Local, Global, Nonlocal) 🔹 Lambda Functions 🔹 Map & Reduce 🔹 Floor Function 🔹 Nested Functions 🔹 Function Aliasing 🔹 Generating Random Numbers 🔹 Method Overloading in Python ✨ This phase helped me understand how Python handles functions in a powerful and flexible way. 📌 One key takeaway: Functions are not just reusable blocks — they can be treated like objects, passed around, and optimized using tools like lambda, map & reduce. I’m building consistency and focusing on strong fundamentals every day 💪 #Python #LearningJourney #100DaysOfCode #Programming #Coding #PythonBasics #DeveloperJourney

𝗗𝗮𝘆 𝟵/𝟯𝟬 Instead of forcing my old coding habits into Python, I’m leaning into how the language handles data natively. Why write four lines of code when you can write one? 1. 𝗧𝗵𝗲 𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱 𝗪𝗮𝘆 (Looping & Appending): nums = [1, 2, 3, 4] squared = [] for n in nums: squared.append(n * n) 2. 𝗧𝗵𝗲 𝗠𝗼𝗱𝗲𝗿𝗻 Approach 🚀: squared = [n * n for n in nums] 👉🏻It’s cleaner, faster, and much more intuitive. These are the small details that make the Python journey so satisfying🤌🏻 At what point do you find List Comprehensions become too complex? Do you stick to them for simple one-liners, or use them for nested logic too? #Python #30daysofcode #CodingJourney #Day9 #SoftwareDevelopment

Day 64 of the #three90challenge 📊 Today I learned about Functions in Python — a key concept for writing clean and reusable code. Instead of repeating the same logic multiple times, functions allow us to define it once and reuse it whenever needed. What I practiced today: • Creating functions using def • Passing inputs (parameters) • Returning outputs using return • Writing reusable and organized code Example thinking: Instead of writing the same code again and again, functions help turn it into a single reusable block. Example: def calculate_total(a, b): return a + b print(calculate_total(5, 10)) This makes code more efficient, readable, and scalable. From writing code → to structuring it better 🚀 GeeksforGeeks #three90challenge #commitwithgfg #Python #DataAnalytics #LearningInPublic #Consistency #Upskilling #PythonBasics

Day 4/120 – I finally understood how Python actually “thinks” 🤯 For the past 3 days, I was learning concepts… But today, things started making sense. Because I learned this 👇 👉 Operators in Python Operators are what make your code “do something” Without them, Python is just… variables sitting idle 😅 Here’s what I explored today 👇 ➕ Arithmetic Operators → +, -, *, / Example: 10 + 5 = 15 📊 Comparison Operators → ==, !=, >, < Example: 10 > 5 → True 🧠 Logical Operators → and, or, not Example: (10 > 5) and (5 > 2) → True This is where logic begins 🔥 Now I can actually: ✔ Make decisions ✔ Compare values ✔ Build logic Feels like I unlocked a new level 🎮 Consistency > Perfection 💪 If you're learning, comment “LEVEL UP” 🚀 #Day4 #Python #DataAnalytics #LearningInPublic #CodingJourney #Consistency #Beginners

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

At first, I thought creating classes was enough… but then I realized—real power comes from building on top of them. Today’s Python MahaRevision 🧬 Chapter 11: Inheritance & More in OOP This chapter took things a step deeper: → Inheritance (reusing and extending existing classes) → Types of inheritance → Method overriding → Using super() → Exploring more OOP concepts It actually felt like connecting pieces together instead of starting from scratch every time. Practice set done: Worked on creating parent-child classes, modifying behaviors, and experimenting with inherited properties and methods. Biggest takeaway You don’t always need to build everything new—sometimes the smartest approach is to reuse and improve what already exists. Slowly understanding how real-world applications are structured. One step at a time. #Python #LearningInPublic #CodingJourney #Programming #OOP

🚀 Day 21 – Merge Two Sorted Lists (Python) 💻 Today’s task: Write a program to merge two sorted lists into a single sorted list. 🔍 The goal is to combine both lists while maintaining the sorted order. 📌 This exercise helped me understand: • Two-pointer technique 🔁 • Efficient list traversal ⚙️ • Writing optimized and clean logic ✨ ✨ A classic problem that builds a strong foundation for algorithms like merge sort. 📈 Learning step by step and improving consistency every day. #Python #100DaysOfCode #CodingJourney #Programming #ProblemSolving #Developer #LearnToCode #Tech #PythonTips #DataStructures

🚀 Day 18 – Flatten a Nested List (Python) 💻 Today’s task: Write a function to flatten a nested list. 🔍 A nested list contains elements that can be lists within lists. The goal is to convert it into a single, flat list. 📌 This exercise helped me understand: • Recursion concepts 🔁 • List traversal techniques 🧩 • Writing flexible and reusable functions ⚙️ ✨ A great problem to improve logical thinking and handle complex data structures. 📈 Learning step by step and staying consistent. #Python #100DaysOfCode #CodingJourney #Programming #ProblemSolving #Developer #LearnToCode #Tech #PythonTips #DataStructures

🚀 Just started diving into Learn Python the Hard Way by Zed A. Shaw—and it’s already reshaping how I approach coding. What I love is the structured, exercise-driven learning style—from basics like variables and loops to real-world concepts like APIs, data handling, and even SQL. It’s not just about reading, but doing consistently. Sometimes the “hard way” is actually the smartest way to build strong fundamentals. 💡 Are you learning Python the easy way… or the right way? #Python #Learning #DataScience #Programming #100DaysOfCode

Most people try to learn Python by memorizing everything. That rarely works. What actually helps is seeing how things connect. You need to understand how pieces fit together: • Variables → used in functions • Functions → used in loops • Loops → used to process data • Data → analyzed with libraries like Pandas That is how real code is written. The gap for most beginners is knowing when to use what. Once that clicks, Python becomes much easier. Which part of Python took you the longest to understand? 👉 Built an AI tool? Get it featured in our community of 13M+ AI Professionals: https://lnkd.in/gRjpdKYx Graphic credits to respective owner. #python #programming #coding #datascience #learning