sentiment analysis

app.py

@@ -78,31 +78,36 @@ def get_news_sentiment(news):
     return postive, neutral, negative
 
 # APP
+col1, col2 = st.columns(2)
+
 st.title('Financial News Headlines Summarization and Sentiment')
-st.write('Enter the stock ticker and period for which you want financial news headlines.')
-stock_ticker = st.text_input('Stock Ticker:', 'AAPL')
-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.write(news)
-
-st.header('Financial News Sentiment')
-with st.spinner('finbert model getting sentiment...'):
-    positive, neutral, negative = get_news_sentiment(news)
-
-# white: #D0D3D4
-# red: #E74C3C
-# green: #2ECC71
-sentiment_df = pd.DataFrame(
-    {
-        'sentiment_labels':['positive', 'neutral', 'negative'],
-        'sentiment':[positive, neutral, negative],
-        'color':['#2ECC71', '#D0D3D4', '#E74C3C']
-    }
-)
-st.bar_chart(sentiment_df, x='sentiment_labels', y='sentiment', color='color', horizontal=True)
-
-st.header('Financial News Summary')
-with st.spinner('facebook bart model is summarizing the news...'):
-    news_summary = get_news_summary(news)
-st.write(news_summary)
+
+with col1:
+    st.write('Enter the stock ticker and period for which you want financial news headlines.')
+    stock_ticker = st.text_input('Stock Ticker:', 'AAPL')
+    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.write(news)
+
+with col2:
+    st.header('Financial News Sentiment')
+    with st.spinner('finbert model getting sentiment...'):
+        positive, neutral, negative = get_news_sentiment(news)
+
+    # white: #D0D3D4
+    # red: #E74C3C
+    # green: #2ECC71
+    sentiment_df = pd.DataFrame(
+        {
+            'sentiment_labels':['positive', 'neutral', 'negative'],
+            'sentiment':[positive, neutral, negative],
+            'color':['#2ECC71', '#D0D3D4', '#E74C3C']
+        }
+    )
+    st.bar_chart(sentiment_df, x='sentiment_labels', y='sentiment', color='color', horizontal=True)
+
+    st.header('Financial News Summary')
+    with st.spinner('facebook bart model is summarizing the news...'):
+        news_summary = get_news_summary(news)
+    st.write(news_summary)