add read sell data
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								read_data.py
									
									
									
									
									
								
							| @@ -5,6 +5,7 @@ import csv | ||||
| sunlight_file_name = 'lightintensity.xlsx' | ||||
| factory_demand_file_name = 'factory_power1.xlsx' | ||||
| electricity_price_data = 'electricity_price_data.csv' | ||||
| electricity_price_data_sell = 'electricity_price_data_sell.csv' | ||||
|  | ||||
| df_sunlight = pd.read_excel(sunlight_file_name, header=None, names=['SunlightIntensity']) | ||||
|  | ||||
| @@ -27,40 +28,27 @@ print(df_power.head()) | ||||
| df_combined = df_sunlight_resampled.join(df_power) | ||||
|  | ||||
|      | ||||
| df_combined.to_csv('combined_data.csv', index=True, index_label='Time') | ||||
|  | ||||
| def read_csv(file_path): | ||||
|     return pd.read_csv(file_path, index_col='Time', usecols=['Time', 'ElectricityPrice']) | ||||
|  | ||||
| # price_data = np.random.uniform(0.3, 0.3, len(times)) | ||||
|  | ||||
| # 创建DataFrame | ||||
| price_df = read_csv(electricity_price_data) | ||||
| price_df = pd.read_csv(electricity_price_data, index_col='Time', usecols=['Time', 'ElectricityBuy']) | ||||
| price_df.index = pd.to_datetime(price_df.index) | ||||
| price_df = price_df.reindex(df_combined.index) | ||||
|  | ||||
| # price_df.set_index('Time', inplace=True) | ||||
|  | ||||
| # 保存到CSV文件 | ||||
| # price_df.to_csv('electricity_price_data.csv', index=True) | ||||
| print("price____") | ||||
| print(price_df.index) | ||||
| print("df_combined____") | ||||
| print(df_combined.index) | ||||
|  | ||||
| print("Electricity price data generated and saved.") | ||||
|  | ||||
|  | ||||
| df_combined2 = df_combined.join(price_df) | ||||
| print(df_combined2.head()) | ||||
| # 保存结果 | ||||
|  | ||||
| sell_df = pd.read_csv(electricity_price_data_sell, index_col='Time', usecols=['Time', 'ElectricitySell']) | ||||
| sell_df.index = pd.to_datetime(sell_df.index) | ||||
| sell_df = sell_df.reindex(df_combined.index) | ||||
|  | ||||
| df_combined3 = df_combined2.join(sell_df) | ||||
|  | ||||
| with open('combined_data.csv', 'w', newline='') as file: | ||||
|     writer = csv.writer(file) | ||||
|     writer.writerow(['time', 'sunlight', 'demand','price']) | ||||
|     writer.writerow(['time', 'sunlight', 'demand','buy', 'sell']) | ||||
|     cnt = 0 | ||||
|     for index, row in df_combined2.iterrows(): | ||||
|     for index, row in df_combined3.iterrows(): | ||||
|         time_formatted = index.strftime('%H:%M') | ||||
|         writer.writerow([time_formatted, row['SunlightIntensity'], row['FactoryPower'],row['ElectricityPrice']]) | ||||
|         writer.writerow([time_formatted, row['SunlightIntensity'], row['FactoryPower'],row['ElectricityBuy'], row['ElectricitySell']]) | ||||
|          | ||||
|     print('The file is written to combined_data.csv') | ||||
|  | ||||
|   | ||||
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