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Pandas & Python Analytics
IntermediateData manipulation, cleaning, analysis, and visualisation with Python
PandasPythonEDA
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Overview
What it is, why it matters, architecture and key concepts
🔤Fundamentals
Core concepts and commands — hands-on from the start
⚡Intermediate
Real-world patterns, best practices, and deeper topics
🚀Advanced
Production patterns, performance, security hardening
🗺️Roadmap
Step-by-step structured learning path from zero to expert
🧪Labs
Hands-on exercises with real environments and scenarios
🏗️Projects
Portfolio-ready projects to demonstrate your skills
💬Interview Q&A
Most asked interview questions with detailed answers
🔧Troubleshooting
Debug common issues with root cause analysis
🏆Certification
Exam guides, practice questions, and prep strategies
📋Cheatsheets
Quick reference — commands, syntax, and patterns
📝Notes
Key takeaways, tips, and important points to remember
🌍Real World
Production stories, incidents, and how experts solve them
❓FAQ
Frequently asked questions and clear answers