class_docstr: Returns datasets included in the library in `pandas.DataFrame` or
  `~greykite.framework.input.univariate_time_series.UnivariateTimeSeries` format.
  
  Extends `~greykite.common.data_loader.DataLoader`
class_docstr_tok: ["Returns","datasets","included","in","the","library","in","`","pandas.DataFrame","`","or","`","~greykite.framework.input.univariate_time_series.UnivariateTimeSeries","`","format",".","Extends","`","~greykite.common.data_loader.DataLoader","`"]
docstr: Loads the Hourly Parking dataset.
  
  This dataset contains occupancy rates (8:00 to 16:30) from 2016/10/04 to 2016/12/19
  from car parks in Birmingham that are operated by NCP from Birmingham City Council.
  Source: https://archive.ics.uci.edu/ml/datasets/Parking+Birmingham
  UK Open Government Licence (OGL)
  
  Below is the dataset attribute information:
  
      SystemCodeNumber: car park ID
      Capacity: car park capacity
      Occupancy: car park occupancy rate
      LastUpdated: date and time of the measure
  
  Parameters
  ----------
  system_code_number : `str` or None, default None
      If None, occupancy rate is averaged across all the ``SystemCodeNumber``.
      Else only the occupancy rate of the given ``system_code_number`` is returned.
  
  Returns
  -------
  ts : `~greykite.framework.input.univariate_time_series.UnivariateTimeSeries`
      Parking data. Time and value column:
  
          ``time_col`` : "LastUpdated"
              Date and Time of the Occupancy Rate, rounded to the nearest half hour.
          ``value_col`` : "OccupancyRatio"
              ``Occupancy`` divided by ``Capacity``.
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code: def load_parking_ts(self, system_code_number=None):
      """Loads the Hourly Parking dataset.
  
      This dataset contains occupancy rates (8:00 to 16:30) from 2016/10/04 to 2016/12/19
      from car parks in Birmingham that are operated by NCP from Birmingham City Council.
      Source: https://archive.ics.uci.edu/ml/datasets/Parking+Birmingham
      UK Open Government Licence (OGL)
  
      Below is the dataset attribute information:
  
          SystemCodeNumber: car park ID
          Capacity: car park capacity
          Occupancy: car park occupancy rate
          LastUpdated: date and time of the measure
  
      Parameters
      ----------
      system_code_number : `str` or None, default None
          If None, occupancy rate is averaged across all the ``SystemCodeNumber``.
          Else only the occupancy rate of the given ``system_code_number`` is returned.
  
      Returns
      -------
      ts : `~greykite.framework.input.univariate_time_series.UnivariateTimeSeries`
          Parking data. Time and value column:
  
              ``time_col`` : "LastUpdated"
                  Date and Time of the Occupancy Rate, rounded to the nearest half hour.
              ``value_col`` : "OccupancyRatio"
                  ``Occupancy`` divided by ``Capacity``.
      """
      df = self.load_parking(system_code_number=system_code_number)
      ts = UnivariateTimeSeries()
      ts.load_data(
          df=df,
          time_col="LastUpdated",
          value_col="OccupancyRatio",
          freq="30min",
      )
      return ts
  
file_path: greykite/greykite/framework/benchmark/data_loader_ts.py
imports: from greykite.common.constants import TIME_COL
  from greykite.common.constants import VALUE_COL
  from greykite.common.data_loader import DataLoader
  from greykite.framework.input.univariate_time_series import UnivariateTimeSeries
label_desc: Use image node_id 3 for calling the DataLoaderTS obj's underlying member method code with example usage: obj.load_parking_ts(system_code_number) and returns: ts