Update pages/1_Earnings_Sentiment_Analysis_📈_.py

pages/1_Earnings_Sentiment_Analysis_📈_.py

@@ -14,9 +14,6 @@ st.subheader(title)
 
 earnings_passages = results['text']
 
-with st.expander("See Transcribed Earnings Text"):
-    st.write(earnings_passages)
-
 with open('earnings.txt','w') as f:
     f.write(earnings_passages)
     
@@ -25,6 +22,12 @@ with open('earnings.txt','r') as f:
     
 earnings_sentiment, earnings_sentences = sent_pipe(earnings_passages)
 
+with st.expander("See Transcribed Earnings Text"):
+    st.write(f"Number of Sentences: {len(earnings_ssentences)}")
+    
+    st.write(earnings_passages)
+
+
 ## Save to a dataframe for ease of visualization
 sen_df = pd.DataFrame(earnings_sentiment)
 sen_df['text'] = earnings_sentences
@@ -48,7 +51,9 @@ fig.update_layout(
     )
 )
 
-st.plotly_chart(fig)
+col1, col2 = st.columns(2)
+
+col1.plotly_chart(fig)
 
 ## Display sentiment score
 pos_perc = grouped[grouped['sentiment']=='Positive']['count'].iloc[0]*100/sen_df.shape[0]
@@ -81,6 +86,8 @@ fig.update_layout(
     )
 )
 
+col2.plotly_chart(fig)
+
 ## Display negative sentence locations
 fig = px.scatter(sen_df, y='label', color='label', size='score', hover_data=['text'], color_discrete_map={"Negative":"firebrick","Neutral":"navajowhite","Positive":"darkgreen"}, title='Sentiment Score Distribution')