bigger top of fold

app.py

@@ -294,7 +294,7 @@ with st.form("choose_model"):
 
                 seq_proba = seq_predict_proba(new_pred, xgbr, seq2)
 
-        st.success(f"All done!", icon="✅")
+        st.success(f'🔮 for {option} on {curr_date} 👇🏽', icon="✅")
 
         green_proba = seq_proba[0]
         red_proba = 1 - green_proba
@@ -342,19 +342,24 @@ with st.form("choose_model"):
 
         score_fmt = f'{score:.1%}'
 
+        prev_close = data.loc[final_row,'Close']
+        curr_close = data['Close'].iloc[-1]
+
+        confidence, success, nn = st.columns(3)
+
+        confidence.metric('Confidence',value=f'{text_cond} {score:.1%}')
+        success.metric('SuccessRate',value=f'{historical_proba:.1%}')
+        nn.metric(f'N{operator}{"" if do_not_play else score_fmt}',value=num_obs)
+
         results = pd.DataFrame(index=[
             'PrevClose',
-            'Confidence Score',
-            'Success Rate',
-            f'NumObs {operator} {"" if do_not_play else score_fmt}',
+            'CurrClose'
         ], data = [
-            f"{data.loc[final_row,'Close']:.2f}",
-            f'{text_cond} {score:.1%}',
-            f'{historical_proba:.1%}', 
-            num_obs,
+            f"{prev_close:.2f}",
+            f"{curr_close:.2f}"
             ])
 
-        results.columns = ['Outputs']
+        results.columns = ['']
 
         # st.subheader('New Prediction')
 
@@ -487,12 +492,11 @@ with st.form("choose_model"):
             f"{len(data.query('Close <= VIX_EM_15_High & Close >= VIX_EM_15_Low')) / len(data):.1%}",
             f"{len(data.query('High > VIX_EM_15_High | Low < VIX_EM_15_Low')) / len(data):.1%}"
             ]
-        st.subheader(f'🔮 for {option} on {curr_date}')
-        st.write(results.T)
 
         tab1, tab2, tab3, tab4 = st.tabs(["🤖 Stats", "✨ New Data", "📚 Historical", "📊 Performance"])
 
         with tab1:
+            st.write(results.T)
             st.write(df_probas)
             st.text(f'VIX EM ({curr_em:.2f} / {fwd_em:.2f})')
             st.write(df_em)