pastas.stats.core.mean
======================

.. py:function:: 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.

   :param series: Series with the values and a DatetimeIndex as an index.
   :type series: pandas.Series
   :param weighted: Weight the values by the normalized time step to account for irregular time
                    series. Default is True.
   :type weighted: bool, optional
   :param max_gap: 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.
   :type max_gap: int, optional

   .. rubric:: Notes

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

   .. math::

       \\bar{x} = \\sum_{i=1}^{N} w_i x_i

   where :math:`w_i` are the weights, taken as the time step between observations,
   normalized by the sum of all time steps.















   ..
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