Time Series Forecasting

Forecasting Methods

Time series forecasting predicts future values.

ARIMA

AutoRegressive Integrated Moving Average. SARIMAX for seasonality.

ACF/PACF identify parameters. statsmodels.tsa.arima.model.ARIMA.

Prophet

Facebook Prophet handles seasonality and holidays. Simple, robust.

prophet.fit(df). future = prophet.make_future_dataframe(). forecast = prophet.predict(future).

Prophet vs ARIMA

Prophet: easy to use, handles missing data. ARIMA: more control, better for short series.

Key Takeaways

1. ARIMA is classical time series method
2. Prophet handles seasonality easily
3. Choose based on data characteristics