Dataframe Hilfe

Datenaufbereitung.py

+import pandas as pd
+import datetime
+
+dftrans = pd.read_csv("Ergebnisse/Load_ECrafter_Wallbox_pricecharging_2021_trans.csv", sep = ";", index_col = 0)
+originalPreise = pd.read_csv("Input/Preise_kom.csv", sep=",", index_col = 0)
+newPrice = pd.DataFrame()
+List = []
+for x in range (0,347):
+    for y in range(0, 24):
+        for i in range(0,60):
+            #originalPreise["Zeit"][i+y*24+x*24]
+            test = i+y*60+x*24*60
+
+            datum = (datetime.datetime(year=2021, month = 1, day= 19, hour=0, minute = 0)+datetime.timedelta(minutes = i, hours = y, days= x))
+            List.append(datetime.datetime.strftime(datum,'%Y-%m-%d %H:%M:%S'))
+
+test = pd.DataFrame(List)
+test2 = []
+test3 = []
+for i in range (0,8328):
+    for x in range (0,60):
+        test2.append(originalPreise["Zeit"][i])
+        test3.append('=d%s*I%s' %(i*60+x, i*60+x))
+df = pd.DataFrame(test2)
+test3 = pd.DataFrame(test3)
+newdf = pd.concat((test,df, test3), axis = 1)
+
+newdf.columns = ["Zeit", "Preis", "Reale Kosten"]
+newdf.set_index('Zeit', inplace = True)
+new = dftrans.sort_index()
+Erganzt = pd.concat((new,newdf), axis=1, join = 'inner')
+for i in range (0,249045):
+
+    Erganzt["Reale Kosten"][i] = "=d%i*I%i" %(i+2,i+2)
+
+
+
+Erganzt.to_excel ("Ergebnisse/Load_ECrafter_Wallbox_pricecharging_2021_trans.xlsx")
+
+dftrans = pd.read_csv("Ergebnisse/Load_ECrafter_Wallbox_pricecharging_2021_ten.csv", sep = ";", index_col = 0)
+originalPreise = pd.read_csv("Input/Preise_kom.csv", sep=",", index_col = 0)
+newPrice = pd.DataFrame()
+List = []
+for x in range (0,347):
+    for y in range(0, 24):
+        for i in range(0,60):
+            #originalPreise["Zeit"][i+y*24+x*24]
+            test = i+y*60+x*24*60
+
+            datum = (datetime.datetime(year=2021, month = 1, day= 19, hour=0, minute = 0)+datetime.timedelta(minutes = i, hours = y, days= x))
+            List.append(datetime.datetime.strftime(datum,'%Y-%m-%d %H:%M:%S'))
+
+test = pd.DataFrame(List)
+test2 = []
+test3 = []
+for i in range (0,8328):
+    for x in range (0,60):
+        test2.append(originalPreise["Zeit"][i])
+        test3.append('=d%s*I%s' %(i*60+x, i*60+x))
+df = pd.DataFrame(test2)
+test3 = pd.DataFrame(test3)
+newdf = pd.concat((test,df, test3), axis = 1)
+
+newdf.columns = ["Zeit", "Preis", "Reale Kosten"]
+newdf.set_index('Zeit', inplace = True)
+new = dftrans.sort_index()
+Erganzt = pd.concat((new,newdf), axis=1, join = 'inner')
+for i in range (0,249045):
+
+    Erganzt["Reale Kosten"][i] = "=d%i*I%i" %(i+2,i+2)
+
+
+
+Erganzt.to_excel ("Ergebnisse/Load_ECrafter_Wallbox_pricecharging_2021_ten.xlsx")
+
+dftrans = pd.read_csv("Ergebnisse/Load_ECrafter_Wallbox_pricecharging_2021_50.csv", sep = ";", index_col = 0)
+originalPreise = pd.read_csv("Input/Preise_kom.csv", sep=",", index_col = 0)
+newPrice = pd.DataFrame()
+List = []
+for x in range (0,347):
+    for y in range(0, 24):
+        for i in range(0,60):
+            #originalPreise["Zeit"][i+y*24+x*24]
+            test = i+y*60+x*24*60
+
+            datum = (datetime.datetime(year=2021, month = 1, day= 19, hour=0, minute = 0)+datetime.timedelta(minutes = i, hours = y, days= x))
+            List.append(datetime.datetime.strftime(datum,'%Y-%m-%d %H:%M:%S'))
+
+test = pd.DataFrame(List)
+test2 = []
+test3 = []
+for i in range (0,8328):
+    for x in range (0,60):
+        test2.append(originalPreise["Zeit"][i])
+        test3.append('=d%s*I%s' %(i*60+x, i*60+x))
+df = pd.DataFrame(test2)
+test3 = pd.DataFrame(test3)
+newdf = pd.concat((test,df, test3), axis = 1)
+
+newdf.columns = ["Zeit", "Preis", "Reale Kosten"]
+newdf.set_index('Zeit', inplace = True)
+new = dftrans.sort_index()
+Erganzt = pd.concat((new,newdf), axis=1, join = 'inner')
+for i in range (0,249045):
+
+    Erganzt["Reale Kosten"][i] = "=d%i*I%i" %(i+2,i+2)
+
+
+
+Erganzt.to_excel ("Ergebnisse/Load_ECrafter_Wallbox_pricecharging_2021_50.xlsx")
+
+dftrans = pd.read_csv("Ergebnisse/Load_ECrafter_Wallbox_pricecharging_2021_amp.csv", sep = ";", index_col = 0)
+originalPreise = pd.read_csv("Input/Preise_kom.csv", sep=",", index_col = 0)
+newPrice = pd.DataFrame()
+List = []
+for x in range (0,347):
+    for y in range(0, 24):
+        for i in range(0,60):
+            #originalPreise["Zeit"][i+y*24+x*24]
+            test = i+y*60+x*24*60
+
+            datum = (datetime.datetime(year=2021, month = 1, day= 19, hour=0, minute = 0)+datetime.timedelta(minutes = i, hours = y, days= x))
+            List.append(datetime.datetime.strftime(datum,'%Y-%m-%d %H:%M:%S'))
+
+test = pd.DataFrame(List)
+test2 = []
+test3 = []
+for i in range (0,8328):
+    for x in range (0,60):
+        test2.append(originalPreise["Zeit"][i])
+        test3.append('=d%s*I%s' %(i*60+x, i*60+x))
+df = pd.DataFrame(test2)
+test3 = pd.DataFrame(test3)
+newdf = pd.concat((test,df, test3), axis = 1)
+
+newdf.columns = ["Zeit", "Preis", "Reale Kosten"]
+newdf.set_index('Zeit', inplace = True)
+new = dftrans.sort_index()
+Erganzt = pd.concat((new,newdf), axis=1, join = 'inner')
+for i in range (0,249045):
+
+    Erganzt["Reale Kosten"][i] = "=d%i*I%i" %(i+2,i+2)
+
+
+
+Erganzt.to_excel ("Ergebnisse/Load_ECrafter_Wallbox_pricecharging_2021_amp.xlsx")
+
+dftrans = pd.read_csv("Ergebnisse/Load_ECrafter_Wallbox_pricecharging_2021_real.csv", sep = ";", index_col = 0)
+new= dftrans.sort_index()
+new.to_excel("Ergebnisse/Load_ECrafter_Wallbox_pricecharging_2021_real.xlsx")
+
+dftrans = pd.read_csv("Ergebnisse/Load_ECrafter_Wallbox_pricecharging_2021_kom_simu.csv", sep = ";", index_col = 0)
+new = dftrans.sort_index()
+new.to_excel("Ergebnisse/Load_ECrafter_Wallbox_pricecharging_2021_kom_simu.xlsx")
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