Update app.py

app.py

@@ -762,11 +762,11 @@ for col in candidate_executor_cols:
 if EXECUTOR_INDIV_COL is None:
     # Fallback — gunakan creator_name (dengan warning transparan)
     EXECUTOR_INDIV_COL = 'nama_pic'
-    st.warning(
-        "⚠️ No dedicated executor column (e.g., 'pic', 'responsible') found. "
-        "Using 'creator_name' as proxy for executor — insights may conflate reporters & executors. "
-        "Consider adding an executor identifier column for accuracy."
-    )
+    # st.warning(
+    #     "⚠️ No dedicated executor column (e.g., 'pic', 'responsible') found. "
+    #     "Using 'creator_name' as proxy for executor — insights may conflate reporters & executors. "
+    #     "Consider adding an executor identifier column for accuracy."
+    # )
 
 
 # ─── Hitung semua metrik ─────────────────────────────────────────────────────
@@ -895,7 +895,7 @@ with col_3b:
     else:
         sort_opt = st.selectbox(
             "Show:", 
-            ["Top 10 Fastest", "Bottom 10 Slowest"], 
+            ["Top 10", "Bottom 10"], 
             key='sort_3b'
         )
 
@@ -903,7 +903,7 @@ with col_3b:
         full_sorted = avg_leadtime_nama.sort_values('avg_monthly_leadtime', ascending=True)
         
         # Ambil subset sesuai pilihan
-        if sort_opt == "Top 10 Fastest":
+        if sort_opt == "Top 10":
             # 10 tercepat: ascending (kecil → besar), tetap diurut ascending → tercepat di atas
             subset = full_sorted.head(10).copy()
         else:  # "Bottom 10 Slowest"
@@ -965,13 +965,13 @@ with col_3d:
     else:
         sort_opt = st.selectbox(
             "Show:", 
-            ["Top 10 Fastest", "Bottom 10 Slowest"], 
+            ["Top 10", "Bottom 10"], 
             key='sort_3d'
         )
 
         full_sorted = avg_leadtime_per_indiv.sort_values('avg_monthly_leadtime', ascending=True)
 
-        if sort_opt == "Top 10 Fastest":
+        if sort_opt == "Top 10":
             subset = full_sorted.head(10).copy()
         else:  # "Bottom 10 Slowest"
             subset = full_sorted.tail(10).sort_values('avg_monthly_leadtime', ascending=False)