Mastering Dictionaries in Python

#Day12 of learning Python 🐍 Today I learned about file handling in Python and how to work with files using different modes like read (r), write (w), and append (a). Also explored using the with statement (context manager) to handle files more safely and efficiently. Practiced tasks like counting words in a file, checking whether a specific word exists, and building a small function to verify if a password exists inside a file. Also revised how try–except–finally helps handle file-related errors like missing files. Working with files made me realize how Python programs can store and retrieve real data, which is an important step toward building practical applications. Day 12 complete — 88 days to go! 🚀 #Day12 #PythonLearning #FileHandling #PythonFiles #100DaysOfLearning #CodingJourney #SkillShikshya

Python Basics Cheat Sheet – From Me print("Hello") -> Display output len(data) -> Get data length type(x) -> Check data type int(), str(), float() -> Type conversion for i in range(5): -> Loop iteration if x > 10: -> Conditional statement def function(): -> Define a function list.append(x) -> Add item to list list.remove(x) -> Remove item from list dict["key"] -> Access dictionary value import math -> Import library Currently learning Python fundamentals and creating simple cheat sheets to stay consistent. Still learning, but enjoying the process. #Python #Programming #LearningJourney #DataAnalytics #CareerGrowth

📘 Today’s Learning: Python Lists 🐍 Today I explored one of the most important concepts in Python — Lists — guided by Satish Dhawale Sir from SkillCourse. 🔹 I learned how to: Create and store multiple values in a list Access elements using indexing Use loops to iterate through list items Modify and update list values Extract specific parts of data (like years from strings) 💡 One interesting practice I did was extracting years from product codes like "Laptop-2024" using slicing. It helped me understand how powerful lists and strings can be together. Consistent learning step by step is helping me build a strong foundation in Python and move closer to my goal in Data Analytics 🚀 #Python #PythonLearning #DataAnalytics #Programming #CodingJourney #SkillCourse #SatishDhawale #LearnToCode #BeginnerToPro #TechSkills #FutureReady

🚀 Just built my first Python project! I created a Student Performance Analyzer using Python. 🔹 Reads data from a CSV file 🔹 Calculates average marks 🔹 Assigns grades 🔹 Finds topper and lowest scorer This project helped me understand: - File handling - Loops & conditions - Functions It’s a simple project, but a solid step in my journey toward Data Science. Here’s the code: https://lnkd.in/dcuxkmQw More projects coming soon. 💪 #Python #DataScience #BeginnerProjects #LearningInPublic

Day 27 of #100Days my python learning journey 👩💻🚀 3 simple Python concepts I learned today: 1. Garbage Collector Python automatically removes unused data from memory. So we don’t need to clean it manually. It keeps code fast and memory safe. 2. 4 Pillars of OOPS →Encapsulation→ Keep data safe inside class →Abstraction → Hide extra details, show only important stuff →Inheritance→ Child class can use parent class features →Polymorphism→ Same name, different work. Like `+` for add & join 3. `pass` Statement Used when we don’t want to write code yet but need to keep empty space. Ex: `if True: pass` → Python won’t give error. Learning to write cleaner and smarter code step by step. Special thanks to the CEO G.R NARENDRA REDDY Sir for constant guidance and motivation. #Python #OOP #100DaysOfCode #LearningJourney

🚀 Learning Something New Every Day! Today I learned an important Python concept — *args and **kwargs. 🔹 *args allows a function to take multiple positional arguments (stored as a tuple) 🔹 **kwargs allows a function to take multiple keyword arguments (stored as a dictionary) 💡 This makes functions more flexible and reusable in real-world scenarios. Here’s a simple example: def demo(*args, **kwargs): print(args) print(kwargs) Step by step, I’m strengthening my Python fundamentals and building a strong base for data analytics. #Python #LearningJourney #Coding #DataAnalytics

#Day11 of learning Python 🐍 Today I learned about data comprehensions in Python, including list comprehension, dictionary comprehension, and set comprehension. Practiced creating lists of even and odd numbers, filtering names based on conditions, generating dictionaries from strings and lists, and even identifying prime numbers using comprehension logic. It was interesting to see how comprehensions make code more concise, readable, and efficient compared to traditional loops. Understanding comprehensions feels like a big step toward writing cleaner and more Pythonic code. Day 11 complete — 89 days to go! 🚀 #Day11 #PythonLearning #ListComprehension #DictionaryComprehension #SetComprehension #100DaysOfLearning #CodingJourney #SkillShikshya

🚀 Day 4: Learning Functions in Python Continuing my journey in Data Science with Python, today I focused on functions, a key concept that helps organize and reuse code efficiently. 📌 Topics Covered Today: ->Defining functions using def ->Passing parameters ->Returning values ->Writing reusable logic 💻 Practiced creating functions to perform specific tasks and avoid repeating code. ⚠️ One challenge I faced: I initially found it confusing when to use return instead of print, but practicing examples helped me understand the difference. 📊 Key Takeaways: ->Functions help break problems into smaller, manageable parts ->Code becomes cleaner and more reusable ->return allows us to reuse results in other parts of the program 🎯 Next Step: Moving towards data structures (lists, tuples, dictionaries) in Python. 📌 Would appreciate suggestions: What are the best ways to write efficient and clean functions? #Day4 #Python #DataScience #CodingJourney #Functions #LearningInPublic

🚀 Python Practice – Lambda Functions, Map & Filter Continuing my Python learning journey with more practical concepts 🐍 In this session, I explored: ✔️ Lambda Functions (anonymous functions) ✔️ Map() for transforming data ✔️ Filter() for selecting data ✔️ Using lambda with map & filter Practiced writing concise and efficient code using lambda functions and applied them with map() and filter() to work with lists and datasets. These concepts are helping me understand how to process and transform data more effectively 📊 A big thanks to Krish Naik for his amazing teaching and clear explanations 🙌 Documented all my practice in a Jupyter Notebook and shared it as a PDF to track my progress. Learning how to write cleaner and more optimized code step by step 💡 Next: Import Modules and Packages in Python 🚀 #Python #Lambda #Map #Filter #DataAnalytics #LearningJourney #Coding #KrishNaik