CERC/monthly_energy_balance_workflow
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cleaned formatting

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Pilar Monsalvete 2023-05-18 11:36:45 -04:00
parent 8ec092a1ae
commit c04493b8a1
1 changed files with 7 additions and 4 deletions
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results.py
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@ -38,15 +38,18 @@ class Results:
dhw_results = pd.DataFrame(array, columns=[f'{building.name} domestic hot water demand Wh']) dhw_results = pd.DataFrame(array, columns=[f'{building.name} domestic hot water demand Wh'])
if cte.MONTH in building.heating_consumption.keys(): if cte.MONTH in building.heating_consumption.keys():
heating_consumption_results = pd.DataFrame(building.heating_consumption[cte.MONTH], columns=[f'{building.name} heating consumption Wh']) heating_consumption_results = pd.DataFrame(building.heating_consumption[cte.MONTH],
columns=[f'{building.name} heating consumption Wh'])
else: else:
heating_consumption_results = pd.DataFrame(array, columns=[f'{building.name} heating consumption Wh']) heating_consumption_results = pd.DataFrame(array, columns=[f'{building.name} heating consumption Wh'])
if cte.MONTH in building.cooling_consumption.keys(): if cte.MONTH in building.cooling_consumption.keys():
cooling_consumption_results = pd.DataFrame(building.cooling_consumption[cte.MONTH], columns=[f'{building.name} cooling consumption Wh']) cooling_consumption_results = pd.DataFrame(building.cooling_consumption[cte.MONTH],
columns=[f'{building.name} cooling consumption Wh'])
else: else:
cooling_consumption_results = pd.DataFrame(array, columns=[f'{building.name} cooling consumption Wh']) cooling_consumption_results = pd.DataFrame(array, columns=[f'{building.name} cooling consumption Wh'])
if cte.MONTH in building.domestic_hot_water_consumption.keys(): if cte.MONTH in building.domestic_hot_water_consumption.keys():
dhw_consumption_results = pd.DataFrame(building.domestic_hot_water_consumption[cte.MONTH], columns=[f'{building.name} domestic hot water consumption Wh']) dhw_consumption_results = pd.DataFrame(building.domestic_hot_water_consumption[cte.MONTH],
columns=[f'{building.name} domestic hot water consumption Wh'])
else: else:
dhw_consumption_results = pd.DataFrame(array, columns=[f'{building.name} domestic hot water consumption Wh']) dhw_consumption_results = pd.DataFrame(array, columns=[f'{building.name} domestic hot water consumption Wh'])