Automate Monday Morning Tasks with Python

Python Series — Day 3 🧠 Let’s level it up a bit 👇 What will be the output of this code? def modify_list(lst): lst.append(4) a = [1, 2, 3] modify_list(a) print(a) Options: A. [1, 2, 3] B. [1, 2, 3, 4] C. Error D. None Think carefully 👀 (Hint: It’s not about functions… it’s about how Python handles data) Drop your answer 👇 Answer tomorrow 🚀 #Python #CodingChallenge #LearningInPublic #DataEngineering #Tech

Python Challenge – Can you solve this? Today was all about deep-diving into Lists vs. Sets and I came across a common mistake that we can sometimes overlook. Let’s test your Python understanding👇 numbers = [1, 2, 3] numbers.append([4, 5]) print(len(numbers)) A) 3 B) 4 C) 5 D) Error It’s a classic interview question that tests if you truly understand how Python handles memory and lists. Day 15/30 #30DaysOfCode #DataStructures #Day15 #PythonQuiz

Python Clarity Series – Episode 25 Topic: Mutable vs Immutable Function Behavior 📌 Why did my list change after function call? def modify(lst): lst.append(100) a = [1, 2] modify(a) print(a) Output: [1, 2, 100] 👉 Lists are mutable → changes reflect outside Now: def modify(x): x = x + 10 a = 5 modify(a) print(a) Output: 5 👉 Integers are immutable → no change outside 💡 Rule: Mutable → changes persist Immutable → changes don’t This confusion causes logic errors. #PythonBasics #FunctionConcepts #StudentClarity #python #clarity

Python Series — Day 1 Answer + Day 2 Question 🚀 🧠 Day 2 Question What will be the output of this code? a = [1, 2, 3] b = a b.append(4) print(a) Options: A. [1, 2, 3] B. [1, 2, 3, 4] C. Error D. Depends on Python version Drop your answer 👇 (And don’t Google 😄) Answer tomorrow 🚀 #Python #CodingChallenge #DataEngineering #LearningInPublic #Tech

Copying vs Reference 🐍 I thought this would create a copy: b = a It didn’t. a = [1, 2, 3] b = a b.append(4) print(a) 👉 [1, 2, 3, 4] Both variables point to the same list. No copy was made. In Python, variables are just labels, not containers. When you use =, you aren’t duplicating data, you’re just giving the same memory address a second name. To actually copy: b = a.copy() Looks the same. Behaves completely differently. 💡 And also: .copy() only goes one layer deep and that's why we need deep copy. ➡️ Assignment ≠ Copy Day 17/30 #Python #30DaysOfCode #SoftwareEngineering

🎯 Python Performance: List Comprehensions vs Loops List comprehensions are often faster and more readable: ```python # Slower squares = [] for x in range(1000): squares.append(x**2) # Faster and cleaner squares = [x**2 for x in range(1000)] ``` But be careful: • Don't nest too deep (hard to read) • Use generator expressions for large datasets • Sometimes loops are clearer Performance matters, but readability matters more. What's your favorite Python performance tip? #Python #Performance #ListComprehension #Optimization

Day 60/100 — #100DaysOfCodingChallenge 60 days in… consistency is slowly turning into a habit now. 🔹 Python (DSA) Solved Search a 2D Matrix — used binary search by treating the matrix like a flattened sorted array. It was a nice reminder of how powerful binary search can be when applied smartly. 🔹 SQL Did some light practice to keep concepts fresh and maintain the streak. #Python #SQL #DSA #LeetCode #Day60 #100DaysOfCode #LearningInPublic #Consistency

🚫 𝗦𝘁𝗼𝗽 𝗺𝗮𝗻𝘂𝗮𝗹 𝘀𝗰𝗿𝗮𝗽𝗶𝗻𝗴. 𝗨𝘀𝗲 𝘁𝗵𝗲 𝗬𝗼𝘂𝗧𝘂𝗯𝗲 𝗔𝗣𝗜. I just published a simple guide on Medium about fetching and visualizing YouTube data using Python. 𝗪𝗵𝗮𝘁'𝘀 𝗶𝗻𝘀𝗶𝗱𝗲: - Getting your API key. - Fetching channel stats. - Visualizing data with Python. - Exporting to Excel. Read the full guide here: https://lnkd.in/gkRijvnS #Python #YouTubeAPI #DataScience #Automation LinkedIn YouTube

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

🎥 Project Explanation Video Here is my explanation for Iris Flower Classification project using Machine Learning. 🔗 GitHub Link: https://lnkd.in/gKwJNFrr #DataScience #MachineLearning #Python #CodeAlpha