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Facebook Prophet
Additive time series forecasting with automatic seasonality handling
What it is
An open-source forecasting procedure from Facebook's Core Data Science team that fits additive models with non-linear trends, yearly, weekly, and daily seasonality, and holiday effects. It is designed for time series with strong seasonal effects and multiple seasons of history, and is robust to missing data, trend shifts, and outliers. Quants who need quick baseline forecasts for seasonal data will find it approachable. The project is now in maintenance mode, accepting only bug fixes, dependency updates, and R parity changes, with no new features planned.
At a glance
Worth watchingOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Professional quants |
|---|---|
| Used for | Data analysis, Strategy research |
| Markets | Multi-market |
| Stack | Python |
| Learning curve | Easy to start |
| Practical value | Medium practical value |
| Cost | Free and open source |
| Hardware | No GPU needed |
| Maintenance | Last commit 6 days ago |
GitHub stars, last 30 days
Daily snapshots since 2026-09-12 (up to 30 days): +38 over the period, now 20,434. Gaps mean no snapshot was taken that day.
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
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