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Prophet is a time series forecasting algorithm based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality. ... NPTS is especially useful when working with sparse or intermittent time series. Forecast provides four algorithm variants: Standard NPTS, Seasonal NPTS, Climatological Forecaster, and Seasonal. The idea that economic data are informative enough to identify sparse predictive models might be an illusion. a. A. Stephen Redding, David Weinstein. The recent availability of large datasets, combined with advances in. In older versions of pandas, the SparseSeries and SparseDataFrame classes (documented below) were the preferred way to work with sparse data. With the advent of extension arrays, these subclasses are no longer needed. Their purpose is better served by using a regular Series or DataFrame with sparse values instead. Note.