code: def standby(df, resolution='24h', time_window=None):
      
  
      if df.empty:
          raise EmptyDataFrame()
  
      df = pd.DataFrame(df)  # if df was a pd.Series, convert to DataFrame
      def parse_time(t):
          if isinstance(t, numbers.Number):
              return pd.Timestamp.utcfromtimestamp(t).time()
          else:
              return pd.Timestamp(t).time()
  
  
      # first filter based on the time-window
      if time_window is not None:
          t_start = parse_time(time_window[0])
          t_end = parse_time(time_window[1])
          if t_start > t_end:
              # start before midnight
              df = df[(df.index.time >= t_start) | (df.index.time < t_end)]
          else:
              df = df[(df.index.time >= t_start) & (df.index.time < t_end)]
  
      return df.resample(resolution).min()
docs: Compute standby power
  
      Parameters
      ----------
      df : pandas.DataFrame or pandas.Series
          Electricity Power
      resolution : str, default='d'
          Resolution of the computation.  Data will be resampled to this resolution (as mean) before computation
          of the minimum.
          String that can be parsed by the pandas resample function, example ='h', '15min', '6h'
      time_window : tuple with start-hour and end-hour, default=None
          Specify the start-time and end-time for the analysis.
          Only data within this time window will be considered.
          Both times have to be specified as string ('01:00', '06:30') or as datetime.time() objects
  
      Returns
      -------
      df : pandas.Series with DateTimeIndex in the given resolution