naming things is hard

app.py

@@ -352,14 +352,14 @@ with st.form("choose_model"):
         # nn.metric(f'N{operator}{"" if do_not_play else score_fmt}',value=num_obs)
 
         top_of_fold = pd.DataFrame(
-            index=[''], 
+            index=['Results'], 
             data = {
                 'Confidence':[f'{text_cond} {score:.1%}'],
                 'Success':[f'{historical_proba:.1%}'],
                 f'N{operator}{score:.1%}':[f'{num_obs} / {len(data)}']
             })
 
-        results = pd.DataFrame(index=[
+        prices = pd.DataFrame(index=[
             'PrevClose',
             'CurrClose'
         ], data = [
@@ -367,7 +367,7 @@ with st.form("choose_model"):
             f"{curr_close:.2f}"
             ])
 
-        results.columns = ['']
+        prices.columns = ['']
 
         # st.subheader('New Prediction')
 
@@ -501,12 +501,12 @@ with st.form("choose_model"):
             f"{len(data.query('High > VIX_EM_15_High | Low < VIX_EM_15_Low')) / len(data):.1%}"
             ]
         
-        st.dataframe(top_of_fold.set_index('Confidence', drop=True), use_container_width=True)
+        st.dataframe(top_of_fold, use_container_width=True)
 
         tab1, tab2, tab3, tab4 = st.tabs(["🤖 Stats", "✨ New Data", "📚 Historical", "📊 Performance"])
 
         with tab1:
-            st.dataframe(results.T.set_index('PrevClose', drop=True))
+            st.dataframe(prices.T.set_index('PrevClose', drop=True))
             st.write(df_probas)
             st.text(f'VIX EM ({curr_em:.2f} / {fwd_em:.2f})')
             st.write(df_em)