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
  
  # read example temperature series
  temperature = pd.read_csv("example_data.csv")["temperature"]
  
  # The following dictionary is create by "workalendar"
  # pip3 install workalendar
  # >>> from workalendar.europe import Germany
  # >>> cal = Germany()
  # >>> holidays = dict(cal.holidays(2010))
  
  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()
  
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))
  
  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()
  
subject: Fix data path issue when installed via pip