Module 1 · Foundations of Python and Data Handling

Section 1: Introduction to Python and VSCode Setup

Why Python · Installation · VSCode · First Script · Library Overview

🐍 Why Python for Visualization?
  • Bridges data analysis and visualization in one language
  • Free, open-source, and industry-standard for data science
  • Outperforms Excel for large datasets and automation
  • Ecosystem: pandas, matplotlib, seaborn, plotly
⚙️ Installing Python
  • Download Python 3.x from python.org
  • Add Python to PATH during installation
  • Verify: python --version in terminal
  • Install packages: pip install matplotlib pandas seaborn plotly
🖥️ VSCode Setup
  • Install VSCode + Python extension (Microsoft)
  • Select interpreter: Ctrl+Shift+P → "Python: Select Interpreter"
  • Integrated terminal for running scripts
  • Jupyter notebook support built-in
📝 First Python Script
  • Variables, print statements, and comments
  • Running a .py file vs interactive notebook
  • Understanding output and error messages
  • Script structure: imports → data → logic → output
📦 Core Libraries Overview
  • pandas — data loading and manipulation
  • matplotlib — foundational static plotting
  • seaborn — statistical visualizations
  • plotly — interactive charts and dashboards
🧪 Lab 1 — Python & VSCode Orientation
  • Install Python, VSCode, and required libraries
  • Write and run a first Python script
  • Load a CSV file with pandas and inspect it
  • Create a simple plot to confirm environment works