flasc.data_processing.filtering.df_mark_turbdata_as_faulty

flasc.data_processing.filtering.df_mark_turbdata_as_faulty#

flasc.data_processing.filtering.df_mark_turbdata_as_faulty(df, cond, turbine_list, exclude_columns=[])[source]#

Mark turbine data as faulty based on a condition.

Parameters:

  • df (pd.DataFrame) -- Dataframe containing the turbine data, formatted in the generic SCADA data format.

  • cond (iteratible) -- List or array-like variable with bool entries depicting whether the condition is met or not. These should be situations in which you classify the data as faulty. For example, high wind speeds but low power productions, or NaNs, self-flagged status variables.

  • turbine_list (int, list) -- Turbine identifier(s) for which the data should be flagged as faulty when the condition is met.

  • exclude_columns (list, optional) -- List of columns that should not be considered for the filtering. Defaults to [].

Returns:

Dataframe with the faulty measurements marked as None.

Return type:

pd.DataFrame

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