Forecasting Time Series Data

This one handles time series forecasting using ARIMA and Prophet models to predict future values from historical data. It analyzes trends, seasonality, and autocorrelation, then trains a model and spits out predictions with confidence intervals. You'd reach for this when forecasting sales, predicting traffic patterns, or analyzing stock price trends. The skill automates model selection based on data characteristics, which saves you from manually testing different approaches. It's practical for business forecasting scenarios where you need quick predictions without building a custom pipeline, though you'll want clean data going in since garbage data means garbage forecasts regardless of the model.