Update README.md

README.md

@@ -95,26 +95,14 @@ def finance_sentiment_predictor(text):
     text = str(text)
     out = classifier(text)[0]
     scores = [sample['score'] for sample in out]
-    labels = [sample['label'] for sample in out]
-    label_map = {'LABEL_0': "Negative", 'LABEL_1': "Neutral", 'LABEL_2': "Positive"}
-    sentiments = [label_map[label] for label in labels]
-    
+    labels = [sample['label'] for sample in out ]
+    label_map = {'LABEL_0':"Negative",'LABEL_1':"Neutral",'LABEL_2':"Positive"}
+    sentiments = [label_map[label] for label  in labels]
     for i in range(len(scores)):
         print(f"{sentiments[i]} : {scores[i]}")
-    
     print(f"Sentiment of text is {sentiments[np.argmax(scores)]}")
-    
-    # Create the bar chart
     fig = go.Figure(
-        data=[
-            go.Bar(
-                x=sentiments,
-                y=scores,
-                marker=dict(color=["red", "blue", "green"]),
-                width=0.3  # Adjust bar width
-            )
-        ]
-    )
+        data=[go.Bar(x=sentiments,y=scores,marker=dict(color=["red", "blue", "green"]),width=0.3)])
     fig.update_layout(
         title="Sentiment Analysis Scores",
         xaxis_title="Sentiments",