Day 1 of Data Structures in Python 🚀 Today I learned the basics of: • Lists • Tuples • Sets • Dictionaries Practiced few basic operations like insert, delete, and search. Understanding how data is stored and accessed is the first step toward better problem-solving. Looking forward to applying these concepts in real problems 🔍 #Python #DSA #LearningJourney #DataStructures
Python Data Structures Basics
More Relevant Posts
-
Started learning Python for Data Analysis 🐍 Not going to lie — it feels confusing at times. But I’m focusing on: • Small steps • Practicing daily • Understanding concepts Progress may be slow, but it’s happening. #Python #DataAnalytics #LearningJourney #Consistency
To view or add a comment, sign in
-
Get started with machine learning using Python and discover how to build intelligent systems that can learn from data and improve their performance over time with this comprehensive guide https://lnkd.in/gDJ28K-Y #MachineLearningWithPython Read the full article https://lnkd.in/gDJ28K-Y
To view or add a comment, sign in
-
-
🐍 Day2 of Python Learning Today, We explored: -What variables are and why they matter ✅ Numbers → int, float ✅ Text → str ✅ Boolean → True, False ✅ Using print() to display values It’s amazing how these simple concepts form the backbone of everything we build in Python. Every program starts with storing and manipulating data and today was a solid step toward that 💪 #Python #LearnPython #15DaysOfPython #Day2 #CodingJourney #Variables #DataTypes #PythonForBeginners #KeepLearning #GrowTogether
To view or add a comment, sign in
-
-
Today, I learned how to take user input in Python using the input() function. This allows programs to interact with users and collect data such as name, age, and city. I also learned how to convert input into numbers using int() and float(), which is very important for calculations and data processing. #Day2 #Python #LearningJourney #DataScience #MachineLearning #Consistency
To view or add a comment, sign in
-
Day 2 of learning Pandas Today was all about cleaning data handled missing values, dropped unnecessary columns, and did some basic filtering. Starting to see how messy data becomes usable with the right steps #Python #Pandas #DataScience #LearningJourney
To view or add a comment, sign in
-
Python Hack: Sum Numbers Hidden in a String! Ever had a string like "2456Linkedin876" and wondered how to quickly add all the numbers inside? Python makes it super easy: s = "2456Linkedin876" total = sum(int(char) for char in s if char.isdigit()) print(total) # Output: 40 ✨ How it works: Loop through each character in the string Pick only the digits Convert them to integers and sum them 🎯 Perfect for data cleaning, quick calculations, or just showing off your Python skills! 💡 Pro Tip: This trick works on any string with numbers hidden in text. #PythonTips #CodingMadeEasy #DataProcessing #LearnPython #DeveloperLife
To view or add a comment, sign in
-
𝗗𝗮𝘆 𝟭 | 𝗦𝘁𝗮𝗿𝘁𝗶𝗻𝗴 𝗺𝘆 𝗣𝘆𝘁𝗵𝗼𝗻 𝗷𝗼𝘂𝗿𝗻𝗲𝘆 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 Today was my first step into Python, and I kept the focus on understanding the basics instead of trying to learn too many things at once. 𝗧𝗼𝗽𝗶𝗰𝘀 𝗰𝗼𝘃𝗲𝗿𝗲𝗱: 💠 What Python is and why it is widely used, especially in data analysis Basic syntax and writing simple programs 💠 Understanding how Python executes code line by line I spent some time running small pieces of code just to get comfortable with the environment. Python feels quite readable, and that made the starting phase less overwhelming. Focusing on the basics at this stage is helping me build confidence for the topics ahead. #Python #DataAnalysis #LearningJourney #PythonBasics #Beginner #TechSkills
To view or add a comment, sign in
-
I built a Python metadata introspection tool for visualising attribute origination across: • Classes • Instances • MRO • Metaclasses • Other objects It is useful for exploring Python’s object model beyond standard dir() style introspection. GitHub: https://lnkd.in/eniV5Yu8 YouTube: https://lnkd.in/e9fatuQt #python #oop #metaprogramming #introspection Example output for a class:
To view or add a comment, sign in
-
-
🚀 Day 3 — Python Journey Today’s focus was on float operations in Python (working with decimal numbers). 📌 What I learned: Float declaration Addition, subtraction, multiplication, division Rounding values using round() Scientific notation Precision handling in floats 💡 What I found interesting: Float values are not always 100% accurate due to precision limitations. Even simple calculations can sometimes give unexpected results. Understanding this early is important, especially for real-world applications like finance or data science. Step by step, trying to build a strong foundation. #Day3 #Python #CodingJourney #LearnInPublic #Consistency
To view or add a comment, sign in
-
-
🚀 Built a simple Day/Night image classifier from scratch using Python. This project is a simple machine learning pipeline built from scratch that classifies images as day or night using handcrafted features and a custom linear SVM. 💾 Source code: https://lnkd.in/dp9kmRmN 💻 Tutorial: https://lnkd.in/d5epPRnt
To view or add a comment, sign in
-
Explore content categories
- Career
- Productivity
- Finance
- Soft Skills & Emotional Intelligence
- Project Management
- Education
- Technology
- Leadership
- Ecommerce
- User Experience
- Recruitment & HR
- Customer Experience
- Real Estate
- Marketing
- Sales
- Retail & Merchandising
- Science
- Supply Chain Management
- Future Of Work
- Consulting
- Writing
- Economics
- Artificial Intelligence
- Employee Experience
- Workplace Trends
- Fundraising
- Networking
- Corporate Social Responsibility
- Negotiation
- Communication
- Engineering
- Hospitality & Tourism
- Business Strategy
- Change Management
- Organizational Culture
- Design
- Innovation
- Event Planning
- Training & Development