🚀 Day 4/100 – Python Today I worked on solving a Quadratic Equation using Python. Instead of just writing code, I focused on understanding the logic behind it. Equation: ax² + bx + c = 0 Key learning from today: ✔ How to convert mathematical formulas into code ✔ Understanding the role of the discriminant (b² - 4ac) ✔ How different values of the discriminant affect the result ✔ Handling edge cases like negative values (using cmath) #100DaysOfCode #Python #ProblemSolving #LearningInPublic
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🚀 Day 2 — Python Journey Continuing with Python, today I focused on integer operations. 📌 What I learned: - Integer declaration - Addition, subtraction, multiplication - Division and modulus (remainder) - Power operation - Operator precedence (which operation runs first) 💡 What stood out: Understanding operator precedence is really important — the same expression can give different results if you don’t know the order of execution. Also, modulus (%) is more useful than it looks (especially for problems and logic building). Trying to stay consistent and build strong basics step by step. #Day2 #Python #CodingJourney #Consistency #LearnInPublic
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🧠 Python Trap You’ll Probably Hit Once When you create a list using multiplication like * 3, Python doesn’t create separate inner lists. Instead, it creates multiple references to the same list in memory. So when you modify one, all of them change together. But when you use a list comprehension, each inner list is created independently. That means changes stay isolated, exactly as you’d expect. This small difference is responsible for a lot of confusing bugs, especially in nested data structures. Reference: https://lnkd.in/gWBiknUH #pythonprogramming #learnpython #coding #python
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Back to consistency 💻🚀 Recently, I worked on implementing Pascal’s Triangle in Python — and it turned out to be a great exercise in logic building. While solving this, I learned: 🔹 How each row depends on the previous one 🔹 Better understanding of nested loops 🔹 Using mathematical logic instead of brute force It’s interesting how such a simple-looking pattern involves deeper thinking behind the scenes. Here’s my implementation 👇 Small steps like these are helping me build a strong foundation in Data Structures & Algorithms. #Python #DSA #CodingJourney #LearningInPublic #100DaysOfCode
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💻 Exploring Recursion in Python 🚀 Today I worked on implementing two classic recursive problems — Factorial and Fibonacci — in Python. At first, small mistakes like typos and function naming issues slowed me down, but debugging them helped me understand recursion much better. 🔁 Key Learnings: • Importance of base conditions in recursion • How recursive calls build up the final result • Debugging is where real learning happens Seeing the Fibonacci output finally work (233 for n=13) was a satisfying moment! 🙌 Step by step, getting closer to mastering problem-solving and logic building. #Python #CodingJourney #Recursion #LearningByDoing #Debugging #100DaysOfCode #DeveloperLife #Programming #TechSkills
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🔁 For Loop vs While Loop in Python — Simple Difference Understanding loops is one of the first steps in mastering Python. Here's a quick comparison: ✅ For Loop Used when the number of iterations is known. Example: Iterating through a list, string, or range. for i in range(5): print(i) ✅ While Loop Used when the number of iterations is unknown and depends on a condition. i = 0 while i < 5: print(i) i += 1 📌 Key Difference for loop → iterate over sequence while loop → run until condition becomes False 💡 Tip: Use for loops for cleaner and readable code when working with collections. Use while loops when waiting for a condition (like user input). #Python #Coding #Programming #PythonBasics #LearnPython
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Today’s focus was on string manipulation in Python, which is an essential part of handling real-world data. I practiced different operations to understand how strings can be processed and transformed efficiently. Here’s what I worked on: • Extracting characters at even indices • Replacing spaces with underscores • Checking if a string contains only digits • Reversing a string using slicing • Capitalizing the first letter of each word These exercises helped me improve my understanding of string handling, indexing, and built-in Python methods. Building consistency and strengthening fundamentals step by step. Big thanks to VASU KUMAR PALANI and PythonLife for the continuous guidance and support. #Python #CodingJourney #LearnInPublic #PythonStrings #Programming #100DaysOfCode #Consistency #TechSkills
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Python Mini Project: Snake-Water-Gun Game Developed a simple Snake-Water-Gun game in Python where the user plays against the computer. This project uses random module, dictionaries, and conditional logic to implement game rules and improve problem-solving skills. 🔗GitHub: https://Inkd.in/g2s4q6Um #Python #MiniProject #Learning #VsCode
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This one NumPy concept saved me hours of coding 👇 👉 Vectorization Earlier, I used loops for almost everything in Python. It worked… but it was slow and messy. Then I discovered this: Instead of processing data element by element, NumPy lets you operate on the entire array at once. Example: Adding 10 to every number Before (Python list): → loop through each element Now (NumPy): → one single line That’s it. This small shift leads to: - faster execution - cleaner code - better performance on large datasets The real change is in thinking: ❌ Think in loops ✅ Think in operations on data That’s when NumPy actually starts making sense. If you’re learning NumPy, focus on this concept early. #NumPy #Python #DataScience #DataEngineering #MachineLearning #CodingJourney #TechLearning
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Day 33/100 – #100DaysOfCode 🚀 Solved LeetCode #1480 – Running Sum of 1d Array (Python). Today I practiced prefix sum logic to compute the running sum of an array. Approach: 1) Initialize an empty list to store the running sum. 2) Maintain a variable sum = 0. 3) Traverse the array and keep adding each element to sum. 4) Append the updated sum to the result list. 5) Return the final running sum array. Time Complexity: O(n) Space Complexity: O(n) Understanding prefix sums helps solve many array problems efficiently 💪 #LeetCode #Python #DSA #Arrays #PrefixSum #ProblemSolving #100DaysOfCode
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Learn machine learning with Python and discover how to build and deploy AI-powered solutions with ease, with our comprehensive guide and tutorial https://lnkd.in/gTKhVnz5 #MachineLearningWithPython Read the full article https://lnkd.in/gTKhVnz5
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