Python filter() Function Examples and Practice

🐍 New on wcblog.in: Python Basics — Variables, Data Types, Loops & Functions Explained If you're starting out with Python (or need a solid refresher), I just published a practical, engineer-focused guide covering everything you need to write real Python code from day one: ✅ Variables & data types (int, str, list, dict, set...) ✅ String manipulation & f-strings ✅ Loops — for, while & list comprehensions ✅ Functions, *args, **kwargs ✅ Error handling with try/except ✅ A mini pipeline project to tie it all together Python is the backbone of data engineering, ML, and automation — and it all starts with these fundamentals. 👉 Read the full guide: https://lnkd.in/g92XrVSU #Python #DataEngineering #PythonBasics #LearnPython #Programming #DataEngineer #TechBlog

An exercise to help build the right mental model for Python data. - Solution: https://lnkd.in/e55Pr8nJ - Explanation: https://lnkd.in/ebPVvnhx - More exercises: https://lnkd.in/eQSdJdaW The “Solution” link visualizes execution and reveals what’s actually happening using 𝗺𝗲𝗺𝗼𝗿𝘆_𝗴𝗿𝗮𝗽𝗵: https://lnkd.in/e3sUM7wG

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

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

🚀 Day 1 of my Data Analytics Journey with Python After building a strong foundation in Excel, I’ve officially started learning Python 🐍 Today’s focus: Loops (for loop & while loop) 🔹 What I learned: - For Loop → Used when we know how many times we want to run a task - While Loop → Runs until a condition becomes false - How loops help in automating repetitive tasks 🔹 Example: Instead of writing the same code multiple times, loops help us do it efficiently in just a few lines 💡 🔹 My key takeaway: Understanding loops is important because they are the foundation for handling large datasets and automation in data analytics 📈 Learning step by step, improving every day #DataAnalytics #Python #LearningJourney #CareerGrowth #ExcelToPython #Consistency #FutureDataAnalyst #codewithharry

Python Hack: Sum Numbers Hidden in a String! Ever had a string like "2456Linkedin876" and wondered how to quickly add all the numbers inside? Python makes it super easy: s = "2456Linkedin876" total = sum(int(char) for char in s if char.isdigit()) print(total) # Output: 40 ✨ How it works: Loop through each character in the string Pick only the digits Convert them to integers and sum them 🎯 Perfect for data cleaning, quick calculations, or just showing off your Python skills! 💡 Pro Tip: This trick works on any string with numbers hidden in text. #PythonTips #CodingMadeEasy #DataProcessing #LearnPython #DeveloperLife

An exercise to help build the right mental model for Python data. - Solution: https://lnkd.in/eEi7JZ7t - Explanation: https://lnkd.in/ebPVvnhx - More exercises: https://lnkd.in/eQSdJdaW The “Solution” link visualizes execution and reveals what’s actually happening using 𝗺𝗲𝗺𝗼𝗿𝘆_𝗴𝗿𝗮𝗽𝗵: https://lnkd.in/e3sUM7wG

🐍 Python Insight: Generators vs Lists While working with large data, I realized something important: List: → Stores entire data in memory Generator: → Yields one value at a time Example: List: data = [i*i for i in range(1000000)] Generator: data = (i*i for i in range(1000000)) 👉 Generators are memory efficient and better for large datasets. Small change, but big impact on performance. #Python #Performance #AdvancedPython

🧠 Python Concept: lambda functions Write quick functions in one line 😎 ❌ Traditional Way def square(x): return x * x print(square(5)) ❌ Problem 👉 Extra lines 👉 Not always needed ✅ Pythonic Way square = lambda x: x * x print(square(5)) 🧒 Simple Explanation Think of lambda like a mini function ⚡ ➡️ No name needed ➡️ One-line function ➡️ Quick & simple 💡 Why This Matters ✔ Less code ✔ Useful for short operations ✔ Works great with map(), filter() ✔ Cleaner for small tasks ⚡ Bonus Example nums = [1, 2, 3, 4] even = list(filter(lambda x: x % 2 == 0, nums)) print(even) 🐍 Small functions, big impact 🐍 Keep it simple & Pythonic #Python #PythonTips #CleanCode #LearnPython #Programming #DeveloperLife #100DaysOfCode

Merging spreadsheets, cleaning exports, and splitting reports are necessary-but-boring tasks. These Python scripts handle the repetitive parts so you can focus on the actual work. https://lnkd.in/eJtC6Wae