Update aggregator.py

aggregator.py

@@ -179,8 +179,8 @@ def get_articles_sentiment(ticker, model):
         if len(vantage_negatives) > 0:
             vantage_negative_score_mean = float(sum(d['score'] for d in vantage_negatives)) / len(vantage_negatives)
 
-    total_positives = len(bezinga_positives) + len(finhub_positives) + len(marketaux_positives) + len(newsapi_positives) + len(newsdata_positives) + len(vantage_positives)
-    total_negatives = len(bezinga_negatives) + len(finhub_negatives) + len(marketaux_negatives) + len(newsapi_negatives) + len(newsdata_negatives) + len(vantage_negatives)
+    total_positives = len(bezinga_positives) + len(finhub_positives) + len(newsapi_positives) + len(newsdata_positives) + len(vantage_positives)
+    total_negatives = len(bezinga_negatives) + len(finhub_negatives) + len(newsapi_negatives) + len(newsdata_negatives) + len(vantage_negatives)
 
     results_dict = {
         "bezinga": {