read electricity data locally
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read_data.py
22
read_data.py
@ -4,6 +4,7 @@ import csv
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sunlight_file_name = 'lightintensity.xlsx'
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sunlight_file_name = 'lightintensity.xlsx'
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factory_demand_file_name = 'factory_power1.xlsx'
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factory_demand_file_name = 'factory_power1.xlsx'
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electricity_price_data = 'electricity_price_data.csv'
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df_sunlight = pd.read_excel(sunlight_file_name, header=None, names=['SunlightIntensity'])
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df_sunlight = pd.read_excel(sunlight_file_name, header=None, names=['SunlightIntensity'])
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@ -25,20 +26,31 @@ print(df_power.head())
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df_combined = df_sunlight_resampled.join(df_power)
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df_combined = df_sunlight_resampled.join(df_power)
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df_combined.to_csv('combined_data.csv', index=True, index_label='Time')
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df_combined.to_csv('combined_data.csv', index=True, index_label='Time')
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price_data = np.random.uniform(0.3, 0.3, len(times))
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def read_csv(file_path):
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return pd.read_csv(file_path, index_col='Time', usecols=['Time', 'ElectricityPrice'])
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# price_data = np.random.uniform(0.3, 0.3, len(times))
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# 创建DataFrame
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# 创建DataFrame
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price_df = pd.DataFrame(data={'Time': times, 'ElectricityPrice': price_data})
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price_df = read_csv(electricity_price_data)
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price_df.index = pd.to_datetime(price_df.index)
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price_df = price_df.reindex(df_combined.index)
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price_df.set_index('Time', inplace=True)
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# price_df.set_index('Time', inplace=True)
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# 保存到CSV文件
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# 保存到CSV文件
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price_df.to_csv('electricity_price_data.csv', index=True)
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# price_df.to_csv('electricity_price_data.csv', index=True)
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print(price_df.head())
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print("price____")
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print(price_df.index)
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print("df_combined____")
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print(df_combined.index)
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print("Electricity price data generated and saved.")
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print("Electricity price data generated and saved.")
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df_combined2 = df_combined.join(price_df)
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df_combined2 = df_combined.join(price_df)
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print(df_combined2.head())
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print(df_combined2.head())
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# 保存结果
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# 保存结果
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