solarforecastarbiter.metrics.preprocessing.apply_fill¶
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solarforecastarbiter.metrics.preprocessing.
apply_fill
(fx_data, forecast, forecast_fill_method, start, end)[source]¶ Apply fill procedure to the data from the start to end timestamps.
Parameters: - fx_data (pandas.Series or pandas.DataFrame) – Forecast data with pandas.DatetimeIndex.
- forecast (datamodel.Forecast) –
- forecast_fill_method ({'drop', 'forward', float}) –
- Indicates what process to use for handling missing forecasts.
- _’drop’_ drops all missing values for any row with a missing value.
- _’forward’_ fills missing values with the most recent real value. If any leading missing values fill with zeros.
- _float_ fills any missing values with the given value.
- start (pandas.Timestamp) –
- end (pandas.Timestamp) –
Returns: - filled (pandas.Series or pandas.DataFrame) – Forecast filled according to the specified logic
- count (int) – Number of values filled or dropped