44 lines
1.4 KiB
Python
Executable File
44 lines
1.4 KiB
Python
Executable File
import pandas as pd
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file_path = './input/raw/postgres/total_electric_consumption_pg_id_40.csv'
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df = pd.read_csv(file_path)
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# Select only the necessary columns
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df = df[['start_ts', 'sum', 'state']]
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# Convert 'start_ts' column to datetime
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df['start_ts'] = pd.to_datetime(df['start_ts'], unit='s')
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# Save the data in the desired format to a text file
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output_file_path = './output/total_electric_consumption_pg_id_40.txt'
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with open(output_file_path, 'w') as f:
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for index, row in df.iterrows():
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f.write(f" - start: \"{row['start_ts']}+00:00\"\n")
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f.write(f" state: {row['state']}\n")
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f.write(f" sum: {row['sum']}\n")
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print(f"Data saved to: {output_file_path}")
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file_path = './input/raw/postgres/total_electric_consumption_cost_pg_id_41.csv'
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df = pd.read_csv(file_path)
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# Select only the necessary columns
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df = df[['start_ts', 'sum', 'state']]
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# Convert 'start_ts' column to datetime
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df['start_ts'] = pd.to_datetime(df['start_ts'], unit='s')
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# Save the data in the desired format to a text file
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output_file_path = './output/total_electric_consumption_cost_pg_id_41.txt'
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with open(output_file_path, 'w') as f:
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for index, row in df.iterrows():
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f.write(f" - start: \"{row['start_ts']}+00:00\"\n")
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f.write(f" state: {row['state']}\n")
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f.write(f" sum: {row['sum']}\n")
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print(f"Data saved to: {output_file_path}")
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