Update app.py

app.py

@@ -255,10 +255,10 @@ with news_analysis:
     print(events.shape, events.columns)
     
     # Add a new column for positive values of column A
-    events['Positive_Impacts'] = events[events['Events_Impact'] > 0]['Events_Impact']
+    events['Positive_Impacts'] = events[events['Events_Impact'] >= 4.7]['Events_Impact']
 
     # Add a new column for negative values of column A
-    events['Negative_Impacts'] = events[events['Events_Impact'] < 0]['Events_Impact']
+    events['Negative_Impacts'] = events[events['Events_Impact'] <= -4.7]['Events_Impact']
 
     # Fill NaN values in the new columns with 0
     events['Positive_Impacts'].fillna("", inplace=True)
@@ -275,7 +275,7 @@ with news_analysis:
     )
     # Create dummy traces for the legend
     dummy_positive = go.Scatter(x=[None], y=[None], mode='lines', name='Positive Impacts',
-        marker=dict(color='black', size=15), showlegend=True,
+        marker=dict(color='green', size=15), showlegend=True,
         # visible='legendonly'
         )
     dummy_negative = go.Scatter(x=[None], y=[None], mode='lines', name='Negative Impacts',
@@ -366,11 +366,18 @@ with news_analysis:
         news[col] = news[col].apply(convert_str_to_list)
     # Extract only the date part
     news['Date'] = news['Date'].dt.date
+    # Sort DataFrame based on the 'Date' column in descending order
+    news = news.sort_values(by='Date', ascending=False)
+
+    # Reset index to reflect the new order
+    news.reset_index(drop=True, inplace=True)
     st.subheader("News Events")
     # st.dataframe(news, hide_index=True)
     # st.table(news)
     dates = list(news['Date'].unique())
     dates = np.sort(dates)
+    # Reverse the array to have the latest date at index 0
+    dates = dates[::-1]
     print(dates, len(dates))
     num_dates = len(dates)
     items_per_page = min(num_dates, 5)