facebook/prophet

Prophet is a forecasting tool made by Facebook's data science team for predicting future values in time series data, that is, data measured over time, like daily sales figures, website traffic, or energy consumption. It is designed to produce high-quality forecasts with minimal manual tuning, making it accessible to analysts who are not forecasting specialists. The core of Prophet is an "additive model," which means it decomposes a time series into separate components, trend, yearly seasonality, weekly seasonality, daily seasonality, and the effects of holidays or special events, and adds them together to make predictions. This structure makes it particularly effective for business data that has strong repeating patterns (such as higher sales on weekends, or a spike every December) and data that spans several years of history. Prophet is also designed to handle missing data gracefully and is robust to outliers and shifts in the trend. The tool is available as both a Python and R package, installable via pip or conda (Python) or from CRAN (R). Under the hood it uses Stan, a statistical modeling platform, to fit the model parameters. You would use Prophet when you need to generate forecasts for business metrics, capacity planning, or any time-ordered dataset where you want to account for seasonality and holidays automatically, without manually specifying complex statistical models. It is well-suited for analysts and data scientists who want a reliable baseline forecast without deep time series expertise.