diff --git a/Analyser.py b/Analyser.py
index 934723f..da9656c 100644
--- a/Analyser.py
+++ b/Analyser.py
@@ -33,13 +33,10 @@ class Analyser:
 	
 		self.df = pd.read_csv('statsfile.csv')
 		self.df['dateRep'] = pd.to_datetime(self.df['dateRep'], format='%d/%m/%Y')
-		self.df = self.df.sort_values('dateRep')
-		self.df['totalCases'] = self.df['cases'].cumsum()
-		self.df['totalDeaths'] = self.df['deaths'].cumsum()
-		self.df['deathRate'] = self.df['deaths'] / self.df['cases'] * 100
 
 	def getAvailableCountries(self):
-		return self.df['countriesAndTerritories'].unique()
+		sorted = self.df.sort_values('countriesAndTerritories')
+		return sorted['countriesAndTerritories'].unique()
 
 	def getAvailableDates(self):
 		retList = []
@@ -65,6 +62,8 @@ class Analyser:
 			countryData = self.df[self.df['countriesAndTerritories'].isin([country])]
 			mask = (countryData['dateRep'] >= start_date) & (countryData['dateRep'] <= end_date)
 			countryTimeData = countryData.loc[mask]
+			countryTimeData = countryTimeData.sort_values('dateRep')
+			countryTimeData['totalCases'] = countryTimeData['cases'].cumsum()
 
 			countryTimeData.plot(ax=ax, x='dateRep', y='totalCases')
 
@@ -133,6 +132,8 @@ class Analyser:
 			countryData = self.df[self.df['countriesAndTerritories'].isin([country])]
 			mask = (countryData['dateRep'] >= start_date) & (countryData['dateRep'] <= end_date)
 			countryTimeData = countryData.loc[mask]
+			countryTimeData = countryTimeData.sort_values('dateRep')
+			countryTimeData['totalDeaths'] = countryTimeData['deaths'].cumsum()
 
 			countryTimeData.plot(ax=ax, x='dateRep', y='totalDeaths')
 
@@ -189,6 +190,10 @@ class Analyser:
 			countryData = self.df[self.df['countriesAndTerritories'].isin([country])]
 			mask = (countryData['dateRep'] >= start_date) & (countryData['dateRep'] <= end_date)
 			countryTimeData = countryData.loc[mask]
+			countryTimeData = countryTimeData.sort_values('dateRep')
+			countryTimeData['totalCases'] = countryTimeData['cases'].cumsum()
+			countryTimeData['totalDeaths'] = countryTimeData['deaths'].cumsum()
+			countryTimeData['deathRate'] = countryTimeData['totalDeaths'] / countryTimeData['totalCases'] * 100
 
 			countryTimeData.plot(ax=ax, x='dateRep', y='deathRate')