68 lines
1.9 KiB
Python
68 lines
1.9 KiB
Python
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import pandas as pd
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import glob
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import os
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main_df = pd.read_csv('../your_output_file.csv')
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final_columns = main_df.columns.tolist()
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def process_archetype_file(filepath):
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filename = os.path.basename(filepath)
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base_name = filename.replace('_Results.csv', '')
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parts = base_name.split('_', 1)
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usage = parts[0]
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vintage = parts[1] if len(parts) > 1 else ''
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df = pd.read_csv(filepath, encoding='latin-1')
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column_mapping = {
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'Heating Demand [kWh/m²]': 'Heating',
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'Cooling Demand [kWh/m²]': 'Cooling',
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'SHW Demand [kWh/m²]': 'DHW',
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'Electricity Demand [kWh/m²]': 'Equipment and lighting',
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'Superficie [m²]': 'Surface'
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}
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for old_col, new_col in column_mapping.items():
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if old_col in df.columns:
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df.rename(columns={old_col: new_col}, inplace=True)
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if 'Date/Time' in df.columns:
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df['Date/Time'] = pd.to_datetime(df['Date/Time'], errors='coerce')
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df.rename(columns={'Date/Time': 'Timestamps'}, inplace=True)
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else:
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pass
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if 'Type_of_building' not in df.columns:
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df['Type_of_building'] = ''
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if 'Equipment' not in df.columns:
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df['Equipment'] = 0
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if 'Lighting' not in df.columns:
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df['Lighting'] = 0
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if 'Heating' not in df.columns:
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df['Heating'] = 0
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if 'Cooling' not in df.columns:
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df['Cooling'] = 0
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if 'DHW' not in df.columns:
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df['DHW'] = 0
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if 'Equipment and lighting' not in df.columns:
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df['Equipment and lighting'] = 0
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if 'Surface' not in df.columns:
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df['Surface'] = 0
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if 'Timestamps' not in df.columns:
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df['Timestamps'] = pd.NaT
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df['Usage'] = usage
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df['Vintage'] = vintage
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df = df[final_columns]
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return df
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for filepath in glob.glob("./data/*_Results.csv"):
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archetype_df = process_archetype_file(filepath)
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main_df = pd.concat([main_df, archetype_df], ignore_index=True)
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main_df.to_csv("energy_demand_data_combined.csv", index=False)
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