Update app.py

app.py

@@ -108,38 +108,64 @@ def score_news(parsed_news_df):
     
     return parsed_and_scored_news
 
-def plot_hourly_sentiment(parsed_and_scored_news, ticker):
+def plot_hourly_sentiment_with_confidence(parsed_and_scored_news, ticker):
     mean_scores = parsed_and_scored_news['sentiment_score'].resample('h').mean()
+    mean_confidence = parsed_and_scored_news['confidence'].resample('h').mean()
     
-    fig = px.bar(mean_scores, x=mean_scores.index, y='sentiment_score', 
+    fig = px.bar(mean_scores, x=mean_scores.index, y='sentiment_score',
                  title=f'{ticker} Hourly Sentiment Scores',
                  color='sentiment_score',
                  color_continuous_scale=['red', 'yellow', 'green'],
                  range_color=[-1, 1])
-    
-    fig.update_layout(coloraxis_colorbar=dict(
-        title="Sentiment",
-        tickvals=[-1, 0, 1],
-        ticktext=["Negative", "Neutral", "Positive"],
-    ))
+
+    fig.add_scatter(x=mean_confidence.index, y=mean_confidence,
+                    mode='lines', name='Confidence Score',
+                    line=dict(color='blue', width=2), yaxis='y2')
+
+    fig.update_layout(
+        yaxis2=dict(
+            title="Confidence Score",
+            overlaying='y',
+            side='right',
+            range=[0, 1]
+        ),
+        coloraxis_colorbar=dict(
+            title="Sentiment",
+            tickvals=[-1, 0, 1],
+            ticktext=["Negative", "Neutral", "Positive"],
+        )
+    )
     
     return fig
 
-def plot_daily_sentiment(parsed_and_scored_news, ticker):
+def plot_daily_sentiment_with_confidence(parsed_and_scored_news, ticker):
     mean_scores = parsed_and_scored_news['sentiment_score'].resample('D').mean()
-    
+    mean_confidence = parsed_and_scored_news['confidence'].resample('D').mean()
+
     fig = px.bar(mean_scores, x=mean_scores.index, y='sentiment_score', 
                  title=f'{ticker} Daily Sentiment Scores',
                  color='sentiment_score',
                  color_continuous_scale=['red', 'yellow', 'green'],
                  range_color=[-1, 1])
-    
-    fig.update_layout(coloraxis_colorbar=dict(
-        title="Sentiment",
-        tickvals=[-1, 0, 1],
-        ticktext=["Negative", "Neutral", "Positive"],
-    ))
-    
+
+    fig.add_scatter(x=mean_confidence.index, y=mean_confidence,
+                    mode='lines', name='Confidence Score',
+                    line=dict(color='blue', width=2), yaxis='y2')
+
+    fig.update_layout(
+        yaxis2=dict(
+            title="Confidence Score",
+            overlaying='y',
+            side='right',
+            range=[0, 1]
+        ),
+        coloraxis_colorbar=dict(
+            title="Sentiment",
+            tickvals=[-1, 0, 1],
+            ticktext=["Negative", "Neutral", "Positive"],
+        )
+    )
+
     return fig
 
 def get_recommendation(sentiment_scores):
@@ -170,8 +196,8 @@ try:
         # Display a disclaimer
         st.warning("Disclaimer: This recommendation is based solely on recent news sentiment and should not be considered as financial advice. Always do your own research and consult with a qualified financial advisor before making investment decisions.")
         
-        fig_hourly = plot_hourly_sentiment(parsed_and_scored_news, ticker)
-        fig_daily = plot_daily_sentiment(parsed_and_scored_news, ticker) 
+        fig_hourly = plot_hourly_sentiment_with_confidence(parsed_and_scored_news, ticker)
+        fig_daily = plot_daily_sentiment_with_confidence(parsed_and_scored_news, ticker) 
         
         st.plotly_chart(fig_hourly)
         st.plotly_chart(fig_daily)