class_docstr: Returns datasets included in the library in `pandas.DataFrame` format.
  
  Attributes
  ----------
  available_datasets : `list` [`str`]
      The names of the available datasets.
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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
  -------
  df : `pandas.DataFrame` object with Parking data.
      Has the following columns:
  
          "LastUpdated" : time, rounded to the nearest half hour.
          "Capacity" : car park capacity
          "Occupancy" : car park occupancy rate
          "OccupancyRatio" : ``Occupancy`` divided by ``Capacity``.
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code: def load_parking(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
      -------
      df : `pandas.DataFrame` object with Parking data.
          Has the following columns:
  
              "LastUpdated" : time, rounded to the nearest half hour.
              "Capacity" : car park capacity
              "Occupancy" : car park occupancy rate
              "OccupancyRatio" : ``Occupancy`` divided by ``Capacity``.
      """
      data_path = self.get_data_home(
          data_dir=None, data_sub_dir="hourly"
      )
      df = self.get_df(data_path=data_path, data_name="hourly_parking")
  
      # Rounds time column to nearest half hour point
      df["LastUpdated"] = pd.to_datetime(df["LastUpdated"]).dt.round(
          "30min"
      )
      df["OccupancyRatio"] = df["Occupancy"] / df["Capacity"]
      if system_code_number is None:
          df = df.groupby("LastUpdated", as_index=False).mean()
      else:
          df = df[
              df["SystemCodeNumber"] == system_code_number
          ].reset_index(drop=True)
      return df
  
imports: import datetime
  import os
  import warnings
  from pathlib import Path
  import pandas
  from greykite.common.constants import TIME_COL
label_desc: Use image node_id 8 for calling the DataLoader obj's underlying member method code with example usage: obj.load_parking(system_code_number) and returns: df