How to Navigate This Guide

Each section in this guide follows a clear Q&A format with:

  • Question — A real-world prompt or task
  • Explanation — The key concept and goal
  • Python Code — A full working solution in Python
  • R Code — The equivalent approach in R

This dual-language structure helps you compare approaches, build fluency, and expand your analytical thinking.

🔁 Tips for Side-by-Side Learning

  • Use the same dataset (e.g., data/iris.csv) for both Python and R
  • Run code independently in:
    • Jupyter Notebook or VSCode (Python)
    • RStudio or VSCode (R)
  • Modify code to explore variations
  • Compare outputs to understand differences in syntax and behavior

✅ What’s Next?

You’re ready to begin working with real data.

In the next section, you’ll:

  • Set up a clean project directory
  • Load your first dataset
  • Begin with Exploratory Data Analysis (EDA) in Python and R

Let’s get started.