What it does:

Pandas has powerful tools for working with dates and times.

Key Concepts:

• Parsing: Convert strings to dates with to_datetime().
• Resampling: Change time frequency (e.g., daily → monthly data).
• Date Offsets: Flexible time shifts (e.g., "3 business days").

Why it matters:

Time-series data (stock prices, sensor readings) requires special handling for accuracy.