🎯Excited to share my second Python practical on Central Tendency of Measures – Mean, Median, and Mode! This practical helped me understand how to summarize and interpret data effectively using Python.📊 Learning how these measures provide insights into data distribution is such a valuable step in data analysis! 📁 Here's the Google drive : linkhttps://lnkd.in/gxfhQ8cB 🔗GitHub account : https://lnkd.in/gcCiRDfS #Python #DataAnalysis #LearningJourney #CentralTendency

Day 56 of my #100DaysOfCode Today, I started learning about one of the most important topics in Python – Lists Here’s what I explored today: 🔹 Python’s 4 built-in data structures 🔹 How to create a list 🔹 List of lists (nested lists) 🔹 Finding the length of a list using len() 🔹 Accessing list items using indexing 🔹 Iterating over a list using loops 🔹 Concatenating lists 🔹 Adding elements to a list using append() and extend() 🔹 List slicing 🔹 Extended slicing techniques 🔹 Converting other data types to lists 🔹 Understanding that Lists are mutable 🔹 And why Strings are immutable in Python #Day56 #100DaysOfCode #Python #ListsInPython #DataStructures #CodingJourney #LearningInPublic #WomenInTech #NxtWave #ProblemSolving

💡 Today’s Python Lesson: Functions as First-Class Objects In computer science, a first-class object is something that supports all the operations generally available to other objects. When we say Python functions are first-class objects, it means you can treat them just like numbers, strings, or lists. That means you can: ✅ Assign them to a variable ✅ Pass them as an argument to another function ✅ Return them as the result of a function ✅ Store them in data structures (like lists or dictionaries) This simple exercise made me realize how powerful and flexible Python really is — it’s not just about writing code, it’s about thinking in functions 🧠🐍 #Python #CodingJourney #100DaysOfCode #PythonDeveloper #LearningInPublic #CodeNewbie #SoftwareDevelopment #ProgrammingConcepts #TechCommunity #PythonProgramming #WomenInTech #Developers #FunctionProgramming

📘 Day 18 of My #50DaysOfPython Challenge 🐍 ✅ Task: Count Word Frequency in a Sentence This task helped me understand how to: 🔹 Work with strings and lists in Python 🔹 Use dictionaries to store key-value pairs 🔹 Implement loops and conditional checks 🔹 Handle case sensitivity in text 🧠 Concept Recap: The program takes a sentence, splits it into words, and counts how many times each word appears. By using a dictionary, each word becomes a key, and its frequency is stored as the value. 💡 Example Output: Enter a sentence: Python is fun and learning python is easy Word Frequency: python: 2 is: 2 fun: 1 and: 1 learning: 1 easy: 1 This small yet powerful task strengthened my understanding of text manipulation and data mapping in Python! 🚀 #Python #CodingChallenge #LearningInPublic #50DaysOfPython #ProgrammingJourney

🍍 Learning Python Built-in Functions – enumerate() Today I explored the enumerate() function in Python! 🐍 It helps in looping through a list while automatically keeping track of the index — and we can even choose where to start counting! Example: fruits = ["mango", "apple", "banana", "orange", "pineapple"] for ind, fruit in enumerate(fruits, start=60): print(ind, fruit) 🔹 Output: 60 mango 61 apple 62 banana 63 orange 64 pineapple This makes iteration more readable and efficient compared to using manual index counters. #Python #Coding #LearningJourney #PythonDeveloper #Programming 10000 Coders@Battula Venkata Narayana

Python Day 4 Tip: Recursion in Python . Recursion is when a function calls itself to solve smaller instances of a problem. It’s often used for tasks like factorial, Fibonacci, or traversing data structures (like trees). Example: def factorial(n): if n == 1: return 1 else: return n * factorial(n - 1) print(factorial(5)) # Output: 120 How it works: 1) Each function call waits for the next call to finish. 2) The base case stops the recursion. Pro Tip: Always define a base case to avoid infinite recursion and RecursionError. #Python #Coding #PythonTips #30DaysOfPythoncode #LearnToCode #Recursion

🐍 Exploring the id() Function in Python — Understanding How Objects Live in Memory! Today, I learned about one of Python’s simplest yet most interesting built-in functions: id(). This function returns the unique identity (or memory address) of an object — helping us understand how Python stores and manages data internally. 🔍 What I learned: ✔️ Every variable in Python is actually a reference to an object in memory. ✔️ id() shows where that object is stored. ✔️ If two variables have the same ID, they point to the same object. ✔️ This is especially useful for understanding mutable vs immutable data types in Python. Learning this helped me see Python from a deeper perspective — not just how code works, but how Python thinks behind the scenes. A huge thanks to Talal Ahmed for explaining this concept so clearly and making it easy to understand the internal mechanics of Python. 🙌 #Python #Programming #LearningJourney #PythonBasics #idFunction #TechSkills #SMIT #AgenticAI

Welcome back to our Python Learning Series Today’s topic: Built-in Data Structures in Python — the core of how Python stores and organizes data! Python gives us four powerful data structures that you’ll use in almost every project. Here’s what you’ll learn in this post: 🔹 Lists — Ordered & Mutable 🔹 Tuples — Ordered & Immutable 🔹 Sets — Unordered & Unique 🔹 Dictionaries — Key-Value Mappings Swipe ➡️ to explore each data structure with simple examples and clear explanations. Save this post for quick revision later! #Python #LearnPython #PythonSeries #PythonProgramming #PythonForBeginners #DataAnalytics #DataScience #CodingJourney #CodeNewbie #100DaysOfCode #Programming #TechLearning #Upskill #StudyNotes #KnowledgeSharing

Python Trick of the Day! 🐍 Let’s test your Python knowledge 👇 👉 What will be the output of this code? result = min(0.0, -0.0) print(result) At first glance, both 0.0 and -0.0 look identical… right? But Python’s floating-point arithmetic has a twist! 😯 💡 Hint: In IEEE 754 floating-point representation, -0.0 actually exists and is considered less than 0.0. ✅ So, the output will be: -0.0 📘 Concept takeaway: Even though 0.0 == -0.0 evaluates to True, they can behave differently in comparisons and certain mathematical operations. 🔹 These subtle details make Python fascinating and powerful to master! 🔹 Keep exploring small concepts — they often lead to deep understanding. #Python #Programming #Learning #Developers #CodingChallenge #PythonTips #DataScience #MachineLearning #AliAhmad #CodeWithAli

💡 What Python Data Types taught me about understanding people Today I learned about data types in Python — int, float, str, bool, list, tuple, dict… all different, all unique. At first, I saw them as just technical categories. But then I realized — they’re just like people. Some are integers — simple, direct, no confusion. Some are floats — they see things with more precision. Some are strings — they express everything through words. Some are booleans — it’s either yes or no, no in-between. And some are lists or dictionaries — full of variety, storing multiple perspectives together. It made me think — just like in Python, life works better when we understand each “data type” of person we deal with. Each type brings value in its own way — we just need to know how to handle them. If you were a Python data type, which one would you be? 😄 #Python #DataScience #StorytellingWithCode #CodingJourney #LearningEveryday #LifelongLearning