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 Bike Sharing Count dataset with possible aggregations.
  
  This dataset contains aggregated hourly count of the number of rented bikes.
  The data also includes weather data: Maximum Daily temperature (tmax);
  Minimum Daily Temperature (tmin); Precipitation (pn)
  The raw bike-sharing data is provided by Capital Bikeshare.
  Source: https://www.capitalbikeshare.com/system-data
  The raw weather data (Baltimore-Washington INTL Airport)
  https://www.ncdc.noaa.gov/data-access/land-based-station-data
  
  Below is the dataset attribute information:
  
      ts : hour and date
      count : number of shared bikes
      tmin : minimum daily temperature
      tmax : maximum daily temperature
      pn : precipitation
  
  Parameters
  ----------
  Refer to the input of function `get_aggregated_data`.
  
  Returns
  -------
  df : `pandas.DataFrame` with bikesharing data.
      If no ``freq`` was specified, the returned data has the following columns:
  
          "date" : day of year
          "ts" : hourly timestamp
          "count" : number of rented bikes across Washington DC.
          "tmin" : minimum daily temperature
          "tmax" : maximum daily temperature
          "pn" : precipitation
      Otherwise, only ``agg_col`` column is returned.
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code: def load_bikesharing(self, agg_freq=None, agg_func=None):
      """Loads the Hourly Bike Sharing Count dataset with possible aggregations.
  
      This dataset contains aggregated hourly count of the number of rented bikes.
      The data also includes weather data: Maximum Daily temperature (tmax);
      Minimum Daily Temperature (tmin); Precipitation (pn)
      The raw bike-sharing data is provided by Capital Bikeshare.
      Source: https://www.capitalbikeshare.com/system-data
      The raw weather data (Baltimore-Washington INTL Airport)
      https://www.ncdc.noaa.gov/data-access/land-based-station-data
  
      Below is the dataset attribute information:
  
          ts : hour and date
          count : number of shared bikes
          tmin : minimum daily temperature
          tmax : maximum daily temperature
          pn : precipitation
  
      Parameters
      ----------
      Refer to the input of function `get_aggregated_data`.
  
      Returns
      -------
      df : `pandas.DataFrame` with bikesharing data.
          If no ``freq`` was specified, the returned data has the following columns:
  
              "date" : day of year
              "ts" : hourly timestamp
              "count" : number of rented bikes across Washington DC.
              "tmin" : minimum daily temperature
              "tmax" : maximum daily temperature
              "pn" : precipitation
          Otherwise, only ``agg_col`` column is returned.
      """
      data_path = self.get_data_home(
          data_dir=None, data_sub_dir="hourly"
      )
      df = self.get_df(
          data_path=data_path, data_name="hourly_bikesharing"
      )
      return self.get_aggregated_data(
          df=df, agg_freq=agg_freq, agg_func=agg_func
      )
  
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 9 for calling the DataLoader obj's underlying member method code with example usage: obj.load_bikesharing(agg_freq, agg_func) and returns: self