diff --git a/starpy/Allocated_Score.py b/starpy/Allocated_Score.py
index a31ef93..87d859e 100644
--- a/starpy/Allocated_Score.py
+++ b/starpy/Allocated_Score.py
@@ -5,55 +5,55 @@ def Allocated_Score(K, W, S):
 
     #Normalize score matrix
     ballots = pd.DataFrame(S.values/K, columns=S.columns)
-    
+
     #Find number of voters and quota size
     V = ballots.shape[0]
     quota = V/W
     ballot_weight = pd.Series(np.ones(V),name='weights')
-    
+
     #Populate winners in a loop
     winner_list = []
     while len(winner_list) < W:
-    
+
         weighted_scores = ballots.multiply(ballot_weight, axis="index")
-    
+
         #Select winner
         w = weighted_scores.sum().idxmax()
         #print('winner',w)
-        
+
         #Add winner to list
         winner_list.append(w)
-    
+
         #remove winner from ballot
         ballots.drop(w, axis=1, inplace=True)
-    
+
         #Create lists for manipulation
-        cand_df = pd.concat([ballot_weight,weighted_scores[w]], axis=1).copy() 
-        cand_df_sort = cand_df.sort_values(by=[w], ascending=False).copy()  
-        
+        cand_df = pd.concat([ballot_weight,weighted_scores[w]], axis=1).copy()
+        cand_df_sort = cand_df.sort_values(by=[w], ascending=False).copy()
+
         #find the score where a quota is filled
         split_point = cand_df_sort[cand_df_sort['weights'].cumsum() < quota][w].min()
-        
+
         #Amount of ballot for voters who voted more than the split point
         spent_above = cand_df[cand_df[w] > split_point]['weights'].sum()
-        
+
         #Exhaust all ballots above split point
-        if spent_above>0:    
+        if spent_above>0:
             cand_df.loc[cand_df[w] > split_point, 'weights'] = 0.0
-    
+
         #if split point = 0 then the winner did not get a full quota of support
-        #otherwise there is a surplus    
+        #otherwise there is a surplus
 
         #Amount of ballot for voters who gave a score on the split point
         weight_on_split = cand_df[cand_df[w] == split_point]['weights'].sum()
 
-        if weight_on_split>0:     
+        if weight_on_split>0:
             #Fraction of ballot on split needed to be spent
             spent_value = (quota - spent_above)/weight_on_split
-    
+
             #Take the spent value from the voters on the threshold evenly
             cand_df.loc[cand_df[w] == split_point, 'weights'] = cand_df.loc[cand_df[w] == split_point, 'weights'] * (1 - spent_value)
-    
+
             #ballot_weight = cand_df['weights'].clip(0.0,1.0)
         ballot_weight = cand_df['weights']
-    return winner_list
\ No newline at end of file
+    return winner_list