diff --git a/website/dataVisualization/homePage/views.py b/website/dataVisualization/homePage/views.py
index 08f5441..c9cb176 100644
--- a/website/dataVisualization/homePage/views.py
+++ b/website/dataVisualization/homePage/views.py
@@ -292,7 +292,7 @@ def includeConcentationToDataFrame(df):
 def averaging_from_old_file(path, fileName):
     df = pd.read_csv("media/" + path, header=0, usecols=[1, 2, 5, 6, 7, 22, 19, 21, 25],
                      names=["oldDate", "Time", "Temperature", "Humidity", "CO2", "CO", "fig210_sens", "fig280_sens",
-                            "e2vo3_sens"], delimiter=",")
+                            "e2vo3_sens"], delimiter=",")[0,1,2,3,4,7,5,6,8]
 
     df['Date'] = pd.to_datetime(df['oldDate'] + ' ' + df['Time'])
 
@@ -344,7 +344,7 @@ def averaging_from_new_file(path, fileName):
     df = pd.read_csv("media/" + path, header=0, usecols=[1, 2, 5, 6, 7, 8, 9, 10, 25, 22, 24, 28],
                      names=["oldDate", "Time", "Temperature", "Humidity", "CO2", "PM1.0", "PM2.5", "PM10", "CO",
                             "fig210_sens", "fig280_sens",
-                            "e2vo3_sens"], delimiter=",")
+                            "e2vo3_sens"], delimiter=",")[0,1,2,3,4,5,6,7,10,8,9,11]
     
     df['Date'] = pd.to_datetime(df['oldDate'] + ' ' + df['Time'])
 
@@ -403,7 +403,7 @@ def averaging(path, fileName, fileType):
 
 # def hourAveraging(path,fileName):
 #     # # Hourly Averaging
-#     df = pd.read_csv("media/"+path,header=0,usecols=[1,2,5,6,7,19,21,25],names=["oldDate", "Time", "Temperature","Humidity","CO2","fig210_sens","fig280_sens","e2vo3_sens"],delimiter=",")
+#     df = pd.read_csv("media/"+path,header=0,usecols=[1,2,5,6,7,19,21,25],names=["oldDate", "Time", "Temperature","Humidity","CO2","fig210_sens","fig280_sens","e2vo3_sens"],delimiter=",")[0,1,2,3,4,7,5,6,8]
 #     df['Date'] = pd.to_datetime(df['oldDate'] + ' ' + df['Time'])
 #     times = pd.DatetimeIndex(df.Date)
 
@@ -415,7 +415,7 @@ def averaging(path, fileName, fileType):
 
 # # Daily Averaging
 
-# df = pd.read_csv('test.txt',header=0,usecols=[1,2,5,6,7,19,21,25],names=["oldDate", "Time", "Temperature","Humidity","CO2","fig210_sens","fig280_sens","e2vo3_sens"],delimiter=",")
+# df = pd.read_csv('test.txt',header=0,usecols=[1,2,5,6,7,19,21,25],names=["oldDate", "Time", "Temperature","Humidity","CO2","fig210_sens","fig280_sens","e2vo3_sens"],delimiter=",")[0,1,2,3,4,7,5,6,8]
 # df['Date'] = pd.to_datetime(df['oldDate'] + ' ' + df['Time'])
 # times = pd.DatetimeIndex(df.Date)
 # grouped = df.groupby([times.date])['Temperature','Humidity',"CO2","fig210_sens","fig280_sens","e2vo3_sens"].mean().reset_index()
@@ -525,7 +525,7 @@ def writeFromOldFile(writer,locationOfDocument1,filename):
              'CO_ppm', 'voc1_ppm', 'voc2_ppm', 'O3_ppb'])
     df = pd.read_csv("media/" + locationOfDocument1, header=0, usecols=[1, 2, 5, 6, 7, 22, 19, 21, 25],
                          names=["oldDate", "Time", "Temperature", "Humidity", "CO2", "CO", "fig210_sens", "fig280_sens",
-                                "e2vo3_sens"], delimiter=",")
+                                "e2vo3_sens"], delimiter=",")[0,1,2,3,4,7,5,6,8]
     df['Date'] = pd.to_datetime(df['oldDate'] + ' ' + df['Time'])
     VOC1_ppm_min = df.fig210_sens.min(axis=0)
     VOC2_ppm_min = df.fig280_sens.min(axis=0)
@@ -566,7 +566,7 @@ def writeFromNewFile(writer,locationOfDocument1,filename):
     df = pd.read_csv("media/" + locationOfDocument1, header=0, usecols=[1, 2, 5, 6, 7, 8, 9, 10, 25, 22, 24, 28],
                      names=["oldDate", "Time", "Temperature", "Humidity", "CO2", "PM1.0", "PM2.5", "PM10", "CO",
                             "fig210_sens", "fig280_sens",
-                            "e2vo3_sens"], delimiter=",")
+                            "e2vo3_sens"], delimiter=",")[0,1,2,3,4,5,6,7,10,8,9,11]
 
     df['Date'] = pd.to_datetime(df['oldDate'] + ' ' + df['Time'])
     VOC1_ppm_min = df.fig210_sens.min(axis=0)