old_contents: # -*- coding: utf-8 -*-
  """Creating heat demand profiles using the bdew method.
  """
  
  import pandas as pd
  import demandlib.bdew as bdew
  from matplotlib import pyplot as plt
  import datetime
  import os
  
  # read example temperature series
  datapath = os.path.join(os.path.dirname(__file__), 'example_data.csv')
  temperature = pd.read_csv(datapath)["temperature"]
  
  # The following dictionary is create by "workalendar"
  # pip3 install workalendar
  # >>> from workalendar.europe import Germany
  # >>> cal = Germany()
  # >>> holidays = dict(cal.holidays(2010))
  
  
  def heat_example():
  	holidays = {
  	    datetime.date(2010, 5, 24): 'Whit Monday',
  	    datetime.date(2010, 4, 5): 'Easter Monday',
  	    datetime.date(2010, 5, 13): 'Ascension Thursday',
  	    datetime.date(2010, 1, 1): 'New year',
  	    datetime.date(2010, 10, 3): 'Day of German Unity',
  	    datetime.date(2010, 12, 25): 'Christmas Day',
  	    datetime.date(2010, 5, 1): 'Labour Day',
  	    datetime.date(2010, 4, 2): 'Good Friday',
  	    datetime.date(2010, 12, 26): 'Second Christmas Day'}
  
  	# Create DataFrame for 2010
  	demand = pd.DataFrame(
  	    index=pd.date_range(pd.datetime(2010, 1, 1, 0), periods=8760, freq='H'))
  
  	demand['efh'] = bdew.HeatBuilding(
  	    demand.index, holidays=holidays, temperature=temperature, shlp_type='EFH',
  	    building_class=1, wind_class=1, annual_heat_demand=25000,
  	    name='EFH').get_bdew_profile()
  
  	demand['mfh'] = bdew.HeatBuilding(
  	    demand.index, holidays=holidays, temperature=temperature, shlp_type='MFH',
  	    building_class=2, wind_class=0, annual_heat_demand=80000,
  	    name='MFH').get_bdew_profile()
  
  	# Plot demand of building
  	ax = demand.plot()
  	ax.set_xlabel("Date")
  	ax.set_ylabel("Heat demand in MW")
  	plt.show()
  if __name__ == '__main__':
      heat_example()
  
new_contents: # -*- coding: utf-8 -*-
  """Creating heat demand profiles using the bdew method.
  """
  
  import pandas as pd
  import demandlib.bdew as bdew
  from matplotlib import pyplot as plt
  import datetime
  import os
  
  # read example temperature series
  datapath = os.path.join(os.path.dirname(__file__), 'example_data.csv')
  temperature = pd.read_csv(datapath)["temperature"]
  
  
  # The following dictionary is create by "workalendar"
  # pip3 install workalendar
  # >>> from workalendar.europe import Germany
  # >>> cal = Germany()
  # >>> holidays = dict(cal.holidays(2010))
  
  
  def heat_example():
      holidays = {
          datetime.date(2010, 5, 24): 'Whit Monday',
          datetime.date(2010, 4, 5): 'Easter Monday',
          datetime.date(2010, 5, 13): 'Ascension Thursday',
          datetime.date(2010, 1, 1): 'New year',
          datetime.date(2010, 10, 3): 'Day of German Unity',
          datetime.date(2010, 12, 25): 'Christmas Day',
          datetime.date(2010, 5, 1): 'Labour Day',
          datetime.date(2010, 4, 2): 'Good Friday',
          datetime.date(2010, 12, 26): 'Second Christmas Day'}
  
      # Create DataFrame for 2010
      demand = pd.DataFrame(
          index=pd.date_range(pd.datetime(2010, 1, 1, 0), periods=8760, freq='H'))
  
      demand['efh'] = bdew.HeatBuilding(
          demand.index, holidays=holidays, temperature=temperature,
          shlp_type='EFH',
          building_class=1, wind_class=1, annual_heat_demand=25000,
          name='EFH').get_bdew_profile()
  
      demand['mfh'] = bdew.HeatBuilding(
          demand.index, holidays=holidays, temperature=temperature,
          shlp_type='MFH',
          building_class=2, wind_class=0, annual_heat_demand=80000,
          name='MFH').get_bdew_profile()
  
      demand['ghd'] = bdew.HeatBuilding(
          demand.index, holidays=holidays, temperature=temperature,
          shlp_type='ghd', wind_class=0, annual_heat_demand=140000,
          name='ghd').get_bdew_profile()
  
      # Plot demand of building
      ax = demand.plot()
      ax.set_xlabel("Date")
      ax.set_ylabel("Heat demand in MW")
      plt.show()
  
  
  if __name__ == '__main__':
      heat_example()
  
subject: fix example and add commercial profile