read electricity data locally

read_data.py

@@ -4,6 +4,7 @@ import csv
 
 sunlight_file_name = 'lightintensity.xlsx'
 factory_demand_file_name = 'factory_power1.xlsx'
+electricity_price_data = 'electricity_price_data.csv'
 
 df_sunlight = pd.read_excel(sunlight_file_name, header=None, names=['SunlightIntensity'])
 
@@ -25,20 +26,31 @@ print(df_power.head())
 
 df_combined = df_sunlight_resampled.join(df_power)
 
+
 df_combined.to_csv('combined_data.csv', index=True, index_label='Time')
 
-price_data = np.random.uniform(0.3, 0.3, len(times))
+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 = pd.DataFrame(data={'Time': times, 'ElectricityPrice': price_data})
+price_df = read_csv(electricity_price_data)
+price_df.index = pd.to_datetime(price_df.index)
+price_df = price_df.reindex(df_combined.index)
 
-price_df.set_index('Time', inplace=True)
+# price_df.set_index('Time', inplace=True)
 
 # 保存到CSV文件
-price_df.to_csv('electricity_price_data.csv', index=True)
+# price_df.to_csv('electricity_price_data.csv', index=True)
-print(price_df.head())
+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