When the PandasHistoryClient creates aggregate timelines, any interval with count=0 will lead to a division by zero in mean_sum (and probably in interval_sum as well anyway). We probably want NaN there.
I'm not sure whether to fix this in the dataframe generation or in the TimeAggregate properties.
When the PandasHistoryClient creates aggregate timelines, any interval with count=0 will lead to a division by zero in
mean_sum(and probably ininterval_sumas well anyway). We probably want NaN there.I'm not sure whether to fix this in the dataframe generation or in the
TimeAggregateproperties.