Python Quiz: Mutable Objects in List Appending

Output: [9, 1, 1, 25, 81] 🧠 filter() + map() chained together! Step 1 — filter() keeps only odd numbers: [3, 1, 1, 5, 9] Step 2 — map() squares each one: [9, 1, 1, 25, 81] ✅ A cleaner, Pythonic way using list comprehension: result = [x**2 for x in nums if x % 2 != 0] Same result, more readable! 🎉 #python #pythonprogramming #coding #programming

Logic in its simplest form. I’ve been refining this Python script for a Rock, Paper, Scissors game. Beyond just the win/loss mechanics, I focused on making the user experience smoother—adding loops for continuous play and validation checks to handle unexpected inputs. It’s a small project, but a great reminder of how foundational conditional logic builds the backbone of any software. #PythonDevelopment #CodeSnippet #ProgrammingLogic #SoftwareEngineering #Python3 #LearnToCode

LeetCode Problem 1009: "Complement of base 10": The complement of an integer is the integer you get when you flip all the 0's to 1's and all the 1's to 0's in its binary representation. For example, The integer 5 is "101" in binary and its complement is "010" which is the integer 2. Given an integer n, return its complement. Approach: First get the binary string representation of given number using bin() and str() functions, second iterate through the string and append '0' to a new string variable if you get '1' and '1' if you get '0', last return the integer value of the new string variable using the int() function with base 2. #Python #Strings #LeetCode #CompetitiveProgramming #DataStructures #DSA #Algorithms #Programming #ProblemSolving

LeetCode Problem 1680: "Concatenation of consecutive binary numbers": Given an integer n, return the decimal value of the binary string formed by concatenating the binary representations of 1 to n in order, modulo 109 + 7. Approach: Simply initialize a string variable, run loop upto the given value of n, calculate binary representation of each number, convert it to string and concatenate it to the string variable. Convert this result into decimal using int() function and then return value after modulo 10^9 + 7. #Python #LeetCode #CompetitiveProgramming #DailyCoding #Programming #DataStructures #Algorithms #Math #BitManipulation #ProblemSolving

📌 NumPy Built-in Methods NumPy provides several built-in functions to quickly create arrays. 🔹 arange() – Creates an array with a range of numbers np.arange(0,10) 🔹 zeros() – Creates an array filled with zeros np.zeros(3) np.zeros((5,5)) → creates a 5×5 matrix of zeros 🔹 ones() – Creates an array filled with ones np.ones(3) np.ones((3,3)) → creates a 3×3 matrix of ones These built-in methods make array creation fast and efficient in NumPy. #Python #NumPy #Programming #DataAnalytics #LearningPython

One typo breaks your condition: if a = 0 instead of if a == 0. 🔀 = assigns. == compares. Mix them up and you get a syntax error — or worse, a bug that’s hard to spot. I wrote a short beginner’s guide that covers: ✅ Linear flow vs conditional flow (when different code runs) ✅ What a condition is (True or False) and how to build one ✅ Comparison operators: <, <=, >, >=, ==, != ✅ if and else: syntax, colon, indentation (4 spaces) ✅ Full program: positive or negative number ✅ Multiple statements in each block ✅ Practice problems + the == vs = fix ~5 min read. Straight to the point. https://lnkd.in/g-vTYtye #Python #Programming #Coding #Beginners #LearnToCode #ConditionalStatements #IfElse #ControlFlow #Tech #SoftwareDevelopment #CodingTips

Sharpening Python Basics: Conditional Statements & Loops 🐍 Focused on core control flow concepts today: 🔹 Conditionals • if, if-else, if-elif-else • Nested conditions → Used for decision-making and logic building 🔹 Loops • for loop (iterate over sequences) • while loop (run based on condition) • break, continue, pass (loop control) These fundamentals power automation, data processing, and problem-solving in real programs. Strong basics. Cleaner logic. Better code. #Python #Coding #Programming #LearningJourney #Developers #TechSkills

🚀 𝗗𝗮𝘆 𝟯 𝗼𝗳 𝗠𝘆 𝗣𝘆𝘁𝗵𝗼𝗻 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗝𝗼𝘂𝗿𝗻𝗲𝘆 Today I focused on understanding some of the core building blocks of programming in Python. 𝗧𝗼𝗱𝗮𝘆’𝘀 𝗧𝗼𝗽𝗶𝗰𝘀: • While Loop – Learned how to execute code repeatedly while a condition remains true. • For Loop – Used to iterate through ranges, lists, and sequences efficiently. • Functions – Understood how to organize code into reusable blocks. • Recursion – Explored how a function can call itself to solve problems step-by-step. 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝗱 𝗣𝗿𝗼𝗯𝗹𝗲𝗺𝘀: ✔ Printed star patterns using loops ✔ Built number triangle patterns ✔ Used recursion to print list elements ✔ Practiced loop logic with different pattern problems Example of a recursion concept I practiced: 𝘥𝘦𝘧 𝘱𝘳𝘪𝘯𝘵_𝘭𝘪𝘴𝘵(𝘢𝘳𝘳, 𝘪𝘥𝘹=0):   𝘪𝘧 𝘪𝘥𝘹 == 𝘭𝘦𝘯(𝘢𝘳𝘳):     𝘳𝘦𝘵𝘶𝘳𝘯   𝘱𝘳𝘪𝘯𝘵(𝘢𝘳𝘳[𝘪𝘥𝘹])   𝘱𝘳𝘪𝘯𝘵_𝘭𝘪𝘴𝘵(𝘢𝘳𝘳, 𝘪𝘥𝘹 + 1) This helped me understand how recursion works internally using the call stack. 💡 𝐊𝐞𝐲 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐓𝐨𝐝𝐚𝐲: Loops control repetition, functions organize logic, and recursion solves problems by breaking them into smaller parts. Every day I’m improving my problem-solving ability and programming mindset. On to 𝗗𝗮𝘆 𝟰 𝗼𝗳 𝗣𝘆𝘁𝗵𝗼𝗻 tomorrow. #Python #LearningInPublic #Programming #DeveloperJourney #100DaysOfCode

Topic 8/100 🚀 🧠 Topic 8 — Higher-Order Functions What if functions could take other functions as input… or even return them? 🤯 👉 What is it? Higher-order functions are functions that either: Accept other functions as arguments, OR Return a function as output 👉 Use Case: Used in real-world applications for: Functional programming patterns Data transformations (map, filter) Building reusable logic 👉 Why it’s Helpful: Promotes code reuse Makes logic more flexible Enables cleaner and modular design 💻 Example: def apply_operation(func, value): return func(value) def square(x): return x * x result = apply_operation(square, 5) print(result) 🧠 What’s happening here? We passed the square function as an argument to another function and executed it dynamically. ⚡ Pro Tip: Master this concept to unlock functional programming in Python. 💬 Follow this series for more Topics #Python #BackendDevelopment #100TopicOfCode #SoftwareEngineering #LearnInPublic

🚀 𝐃𝐚𝐲 10/60 – 60-𝐃𝐚𝐲 𝐏𝐲𝐭𝐡𝐨𝐧 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 Today's topic is "𝐋𝐨𝐨𝐩𝐬 ( )" In Python, loops enable repeated execution of a code block, with two primary structures: 𝐟𝐨𝐫  𝐰𝐡𝐢𝐥𝐞 The for loop iterates over a sequence (such as a list, tuple, or range) and is ideal when the number of iterations is known or determined by the iterable. The while loop continues as long as a specified condition remains true, making it suitable for scenarios with an unknown iteration count. Both loops can be augmented with break to exit early and continue to skip to the next iteration, and they can leverage else blocks for  𝒇𝒍𝒐𝒘 𝒄𝒐𝒏𝒕𝒓𝒐𝒍. Proper use of loop constructs enhances code clarity and efficiency while avoiding common pitfalls like infinite loops. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞     # For loop example: print numbers 0 through 4 𝘧𝘰𝘳 𝘪 𝘪𝘯 𝘳𝘢𝘯𝘨𝘦(5):   𝘱𝘳𝘪𝘯𝘵(𝘪)     # While loop example: print numbers 0 through 4 𝘫 = 0 𝘸𝘩𝘪𝘭𝘦 𝘫 < 5:   𝘱𝘳𝘪𝘯𝘵(𝘫)   𝘫 += 1 Understanding these operators made me realize how programs make decisions and perform actions based on logic. They may look like simple symbols, but they are essential for writing meaningful code. Step by step, building stronger logic. #learning #python #consistency #challenge #60days #coding #programming #loops