Now, let’s move on to the next topic in the Data Science Learning Series: *Loops & Conditional Statements (Data Science Style)* In Data Science, we often deal with data in lists, dictionaries, or DataFrames. Loops and conditionals help us filter, transform, and understand that data. *1. Conditional Statements: if, elif, else* These help you make decisions based on data. Example: age = 25 if age < 18: print("Minor") elif age < 60: print("Adult") else: print("Senior") *Real-world use: Imagine you're categorizing customers based on age groups — you'll use conditionals for that!* *2. For Loop (Iterating over data)* Example: sales = [120, 340, 560, 90, 410] for amount in sales: if amount > 300: print("High Value Sale:", amount) *Use Case: Filter out big spenders from a transaction list.* *3. While Loop* Repeat something until a condition is met. count = 0 while count < 3: print("Running analysis...") count += 1 *4. Looping through a list of dictionaries* orders = [ {"item": "Pizza", "price": 300}, {"item": "Burger", "price": 150}, {"item": "Pasta", "price": 250} ] for order in orders: if order["price"] > 200: print(order["item"], "is Premium") *Mini Data Science Use Case:* Say you have a list of customer purchases and want to tag them as "low", "medium", or "high" value: purchases = [150, 500, 1200, 300] for amount in purchases: if amount < 300: print(amount, "= Low Value") elif amount <= 800: print(amount, "= Medium Value") else: print(amount, "= High Value") *React with ❤️ once you're ready for the quiz* Data Science Learning Series: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D/998 Python Cheatsheet: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L/1660