pastas.stats.core.mean

pastas.stats.core.mean(series: pandas.Series | None = None, weighted: bool = True, max_gap: int = 30, **kwargs) → pastas.typing.ArrayLike

Compute the (weighted) mean of a time series.

Parameters:

• series (pandas.Series) – Series with the values and a DatetimeIndex as an index.

• weighted (bool, optional) – Weight the values by the normalized time step to account for irregular time series. Default is True.

• max_gap (int, optional) – maximum allowed gap period in days to use for the computation of the weights. All time steps larger than max_gap are replace with the mean weight. Default value is 90 days.

Notes

The (weighted) mean for a time series x is computed as:

\[\begin{split}\\bar{x} = \\sum_{i=1}^{N} w_i x_i\end{split}\]

where \(w_i\) are the weights, taken as the time step between observations, normalized by the sum of all time steps.