Python Functions Returning Multiple Values

Stop using for loops to process data in Python. Do this instead. Day 6/47: Calculating Batting Strike Rates! 🏏 Processing millions of rows with a standard Python loop will freeze your system. The fix? Vectorization. Instead of looping row-by-row, NumPy aligns arrays in memory, executing math (runs / balls) * 100 instantly in parallel. Standard Lists = Slow & Iterative. NumPy Arrays = C-Speed & Parallel. 🔊 Watch my 43-second animated Masterclass to see the data flow! Ever crashed a notebook with a bad loop? Let me know! 👇 #DataScience #NumPy #Python #MachineLearning #CodingJourney #BSCIT

⚠️ Strings look simple… until they aren’t. Back with my Python MahaRevision — and today’s focus was on: 📘 Chapter 3: Strings From basic text handling to powerful operations, this chapter showed me that strings are way more than just “text” in Python 👇 🔹 String slicing & indexing 🔹 String functions & methods 🔹 Escape sequences 🔹 Immutability of strings 🧠 Practice Set Completed! Worked on problems like: • Manipulating and slicing strings • Finding and replacing words • Formatting outputs • Real-world text-based logic 💡 Biggest takeaway: Small concepts like slicing and methods can solve surprisingly complex problems when used right. Learning in public. Staying consistent. Improving daily 🚀 #Python #CodingJourney #LearningInPublic #Programming #Tech #100DaysOfCode

🚀 **Day 6 – Gen AI Course** Today’s session focused on the fundamentals of Python programming. I learned about Python basic data types, variables, and wrote my first code in the Python environment. This session helped build a strong foundation for understanding how programming works before moving into more advanced AI concepts. Step by step, building the skills needed for my AI journey. 💻✨ #Python #GenAI #Programming #LearningJourney #ArtificialIntelligence #LearnInPublic

It’s funny how even code needs to “decide” what to do next. Today’s Python MahaRevision was all about making decisions in code 👇 📘 Chapter 6: Conditional Expressions Finally getting into the part where programs start to feel a bit “smart”: • if, elif, else • using logic to control flow • combining conditions with and/or/not 🧠 Did the practice set too: Tried problems like checking numbers, comparing values, simple decision-making stuff… nothing too crazy, but really made me think. Honestly, this chapter felt different. It’s not just about syntax anymore—it’s about how you think. Taking it one chapter at a time 🚀 #Python #LearningInPublic #CodingJourney #Programming

We just finished the first YouTube series on py-dss-toolkit. If you use OpenDSS with Python, this series shows practical ways to explore models, extract results, and visualize studies more efficiently. You can use py-dss-toolkit to: ✅ work with OpenDSS data in a more structured way 📊 move results into pandas DataFrames for analysis 💻 create visual workflows, including in Google Colab I’d love your feedback: what should the next series focus on? 🔎 Plotting? 🔎 QSTS? 🔎 Model exploration? 🔎 Automation? #OpenDSS #Python #PowerSystems

📚 Day 11 – Python Learning Journey Today’s focus was on For Loops in Python. I practiced how loops help automate repetitive tasks and process data efficiently. Things I worked on today: 🔹 Iterating through numbers using range() 🔹 Looping through strings and lists 🔹 Printing even and odd numbers 🔹 Calculating total marks from a list 🔹 Cleaning messy text data (city names) using strip() and title() 🔹 Using if conditions inside loops 🔹 Extracting parts of employee IDs using slicing Small steps every day, but moving closer to becoming better at Python and Data Analysis. 🚀 Thanks to Satish Dhawale sir Founder of SkillCourse #Python #CodingPractice #DataAnalytics #LearningJourney #11Day

I wish I had this when I started learning Python. 🐍 This single cheat sheet covers everything from the absolute basics to advanced concepts: 👉 Data Structures (Lists, Tuples, Sets, Dicts) 👉 OOP — Classes, Inheritance, Polymorphism 👉 NumPy, Pandas & Visualization 👉 Exception Handling & File I/O 👉 Built-in Functions & List Comprehension Bookmark this. Share it. Come back to it. The best programmers aren't the ones who memorize everything — they're the ones who know where to look. 💡 Drop a 🙌 if you found this helpful! #Python #ProgrammingTips #LearnPython #ArtificialIntelligence #MachineLearning #DataScience #Coding #100DaysOfCode #TechSkills

Day 1 was about probability foundations: sample space, events, union, intersection, complement, and the basic axioms. Main lesson: if the sample space is not defined clearly, the rest of the solution cannot be trusted. Also, an outcome is not the same as an event. That distinction matters. Wrote small Python scripts as well. Good reminder that coding exposes weak understanding quickly. The goal is not to move fast. The goal is to build correctly. #Probability #Python #Statistics

Week 1 of #100DaysOfCode — done. 🎉 This week wasn’t about writing complex code. It was about building consistency. This week I focused on Python fundamentals: • Control flow (if/else, loops) • Functions and scope • Imports and modules • Lists and tuples I’ve structured my learning into notes and practical examples to better understand the concepts : https://lnkd.in/epaBymnJ Still early in the journey, but the foundation is starting to form. Let’s keep going. 🚀 #100DaysOfCode #Python #LearningInPublic #CodingJourney

📅 Day 22 of Learning Python – Matrices 🧮 Today, I explored Matrices in Python using lists. A matrix is simply a list of lists, commonly used to represent: Rows & Columns Real-world data like scores, images, etc. 📌 Key Learnings: Indexing starts from 0 l[i] gives a full row l[i][j] gives a single element Nested loops help traverse rows and columns Feeling more confident with loops + matrices today 💪 Step by step, moving forward 🚀 #Python #LearningPython #Matrices #CodingJourney #Day22 #ProgrammingBasics #Consistency