sentiment analysis

app.py

@@ -78,9 +78,16 @@ def get_news_sentiment(news):
     return postive, neutral, negative
 
 # APP
-col1, col2 = st.columns(2)
+
+st.set_page_config(
+    page_title="Financial News Headlines Summarization and Sentiment",
+    page_icon="$",
+    layout="wide",
+    initial_sidebar_state="expanded",
+)
 
 st.title('Financial News Headlines Summarization and Sentiment')
+col1, col2 = st.columns(2)
 
 with col1:
     st.write('Enter the stock ticker and period for which you want financial news headlines.')
@@ -88,10 +95,12 @@ with col1:
     start_date = st.date_input('Start Date:', datetime.datetime.today()-datetime.timedelta(days=20))
     end_date = st.date_input('End Date:', datetime.datetime.today())
     news = financial_news(stock_ticker, start_date, end_date)
+    st.divider()
+    st.subheader('News Headlines:')
     st.write(news)
 
 with col2:
-    st.header('Financial News Sentiment')
+    st.subheader('Financial News Sentiment')
     with st.spinner('finbert model getting sentiment...'):
         positive, neutral, negative = get_news_sentiment(news)
 
@@ -107,7 +116,7 @@ with col2:
     )
     st.bar_chart(sentiment_df, x='sentiment_labels', y='sentiment', color='color', horizontal=True)
 
-    st.header('Financial News Summary')
+    st.subheader('Financial News Summary')
     with st.spinner('facebook bart model is summarizing the news...'):
         news_summary = get_news_summary(news)
     st.write(news_summary)