Pandas Time Series

Work with timestamps, date ranges, and frequency resampling.

❮ Previous Next ❯

Pandas has extensive capabilities for working with time-series data: parsing dates (to_datetime), creating timestamp ranges (date_range), and resampling time intervals (resample).

Key Takeaways: Pandas Time Series

Mastering Pandas Time Series helps you write clean and reliable Pandas code. Follow standard conventions, test edge cases, and keep logic simple. Try running the code example below and complete the exercises to build confidence.

Pandas Time Series Code Example

Pandas

import pandas as pd

dates = pd.date_range("2026-01-01", periods=3, freq="D")
ts = pd.Series([10.5, 12.0, 14.2], index=dates)
print("Time Series Data:\n", ts)

Output

Time Series Data:
 2026-01-01    10.5
2026-01-02    12.0
2026-01-03    14.2
Freq: D, dtype: float64

Free sign-in required · Google login available

Finished this lesson?

Mark it complete to track your progress.

Stuck on something?

Ask the community in the CodesInTech forum.

Need a developer?

Learning on your own is great — and when you need professional help, our team builds custom software, websites and mobile apps for clients worldwide.

Explore Our Services

Pandas Time Series

💡 Key Takeaways: Pandas Time Series

Pandas Time Series Code Example

Key Takeaways: Pandas Time Series