Country Data Scraper Built with Python and BeautifulSoup

📘 Quick Python Libraries Cheat Sheet covering NumPy, Pandas, Matplotlib, and Seaborn. Continuing to build strong foundations in data analysis and visualization. #Python #DataScience #LearningJourney

Day 2 of my Data Science Journey 💻✨ Today I explored basics of Pandas in Python. Learned how to work with datasets and understand data better 📊 Every small step is bringing me closer to my goal 😊 Still learning… still improving 🚀 What did you learn today? 👇 #DataScience #Python #LearningJourney #Pandas #CodingLife

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

Excited to share my latest blog on Getting Started with Matplotlib in Python! 📊 In this article, I’ve covered the basics of data visualization using Matplotlib and how we can turn raw data into meaningful insights. This project helped me strengthen my understanding of Python and data visualization concepts. 🔗 Read here: https://lnkd.in/g5HZZ4jt I’d love to hear your feedback! #Python #Matplotlib #DataVisualization #MediumBlog #LearningJourney

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

🚀 Escape Sequences & Raw Strings in Python (Beginner Friendly!) 🐍 Understanding strings is one of the first steps to writing clean Python code. 🔹 Escape Sequences Special characters used inside strings: - "\n" → New line - "\t" → Tab space - "\\" → Backslash 🔹 Raw Strings (r"") Treat backslash as normal text (no special meaning) 👉 Example: print("Hello\nWorld") print(r"C:\Users\Name\Documents") 🎥 I’ve explained this clearly with examples in my latest video 👇 👉 [https://lnkd.in/gv45tifv] 💡 This is very useful when working with: ✔ File paths ✔ Regular expressions ✔ Clean string formatting If you're starting Python or Data Science, this is a must-know concept! #Python #CodingForBeginners #DataScience #LearnPython #YouTubeLearning

🚢 Completed Titanic Survival Analysis! Tools: Python | Pandas | Seaborn | Matplotlib Key Findings: ✅ Females had higher survival rate ✅ First class passengers survived more ✅ Higher fare = better survival chance GitHub: https://lnkd.in/gTsrns4y #DataAnalysis #Python #Pandas #DataScience

Most people think better analysis comes from complex code. In reality, it comes from using simple operations correctly. If your projects feel messy or inconsistent… this is the foundation you’re missing. Master these Pandas basics once and every dataset starts making more sense. #Pandas #DataScience #Python #Analytics #LearnData

I help businesses summarize and understand their data using Python, Pandas, and Jupyter Notebooks. From mean, median. I turn raw numbers into actionable knowledge. Explore my service on Khamsat: [https://lnkd.in/dHBTA3xF] #DataAnalysis #DescriptiveStatistics #Python #Business

Python Series — Day 1 Answer + Day 2 Question 🚀 🧠 Day 2 Question What will be the output of this code? a = [1, 2, 3] b = a b.append(4) print(a) Options: A. [1, 2, 3] B. [1, 2, 3, 4] C. Error D. Depends on Python version Drop your answer 👇 (And don’t Google 😄) Answer tomorrow 🚀 #Python #CodingChallenge #DataEngineering #LearningInPublic #Tech