Update app.py

app.py

@@ -723,9 +723,9 @@ def generate_objective2_insights(df: pd.DataFrame) -> str:
 
 # === RENDER INSIGHT BOX ===
 # =============== INSIGHT 2 (Ringkas & Fokus ke Red & Amber) ===============
-# =============== INSIGHT 3 (Objective 3: Red & Amber Alarm Patterns by Time & Position) ===============
+# =============== INSIGHT 3 (Rata kiri, sesuai preferensi Aning) ===============
 
-# Pastikan alarm_data ada dan punya kolom wajib
+# ————— Validasi data —————
 required_cols = {'Alarm Status', 'hour', 'Position'}
 if not required_cols.issubset(alarm_data.columns) or alarm_data.empty:
     insight_lines = [
@@ -733,7 +733,7 @@ if not required_cols.issubset(alarm_data.columns) or alarm_data.empty:
         "• Ensure dataset includes 'Alarm Status', 'hour', and 'Position' columns."
     ]
 else:
-    # Filter Red & Amber — case-insensitive, aman terhadap NaN
+    # Filter Red & Amber — case-insensitive, robust terhadap NaN
     mask_red = alarm_data['Alarm Status'].str.contains(r'\bRed\b', case=False, na=False)
     mask_amber = alarm_data['Alarm Status'].str.contains(r'\bAmber\b', case=False, na=False)
     red_amber_data = alarm_data[mask_red | mask_amber].copy()
@@ -743,82 +743,68 @@ else:
     else:
         insight_lines = []
 
-        # Helper: count alarms per (position, hour, type)
-        # — tanpa def, langsung vectorized
+        # Tambahkan flag
         red_amber_data['is_red'] = mask_red.loc[red_amber_data.index]
         red_amber_data['is_amber'] = mask_amber.loc[red_amber_data.index]
 
-        # Loop position 1–4
+        # Loop tiap posisi roda (1–4)
         for pos in [1, 2, 3, 4]:
-            # Filter by position
             pos_data = red_amber_data[red_amber_data['Position'] == pos]
             if pos_data.empty:
                 continue
 
-            # Band 1: 12:00–18:00 (12 ≤ hour ≤ 17)
+            # Band 1: 12:00–18:00 (siang/sore)
             band1 = pos_data[(pos_data['hour'] >= 12) & (pos_data['hour'] <= 17)]
-            # Band 2: 18:00–00:00 (18–23 atau 0–5)
+            # Band 2: 18:00–00:00 (sore/malam/dini hari)
             band2 = pos_data[(pos_data['hour'] >= 18) | (pos_data['hour'] <= 5)]
 
-            # ————— Band 1: 12:00–18:00 —————
+            # — Band 1 —
             if not band1.empty:
-                # Red peak hour in band1
-                red_band1 = band1[band1['is_red']]
-                if not red_band1.empty:
-                    hour_counts = red_band1['hour'].value_counts()
-                    peak_h = int(hour_counts.idxmax())
-                    count = int(hour_counts.max())
-                    insight_lines.append(f"• Position {pos}, 12:00–18:00: Peak Red alarm at {peak_h:02d}:00 ({count} occurrences).")
-
-                # Amber peak hour in band1
-                amber_band1 = band1[band1['is_amber']]
-                if not amber_band1.empty:
-                    hour_counts = amber_band1['hour'].value_counts()
-                    peak_h = int(hour_counts.idxmax())
-                    count = int(hour_counts.max())
-                    insight_lines.append(f"• Position {pos}, 12:00–18:00: Peak Amber alarm at {peak_h:02d}:00 ({count} occurrences).")
-
-            # ————— Band 2: 18:00–00:00 —————
+                red_sub = band1[band1['is_red']]
+                if not red_sub.empty:
+                    h_peak = int(red_sub['hour'].value_counts().idxmax())
+                    c_peak = int(red_sub['hour'].value_counts().max())
+                    insight_lines.append(f"• Position {pos}, 12:00–18:00: Peak Red alarm at {h_peak:02d}:00 ({c_peak} occurrences).")
+
+                amber_sub = band1[band1['is_amber']]
+                if not amber_sub.empty:
+                    h_peak = int(amber_sub['hour'].value_counts().idxmax())
+                    c_peak = int(amber_sub['hour'].value_counts().max())
+                    insight_lines.append(f"• Position {pos}, 12:00–18:00: Peak Amber alarm at {h_peak:02d}:00 ({c_peak} occurrences).")
+
+            # — Band 2 —
             if not band2.empty:
-                red_band2 = band2[band2['is_red']]
-                if not red_band2.empty:
-                    hour_counts = red_band2['hour'].value_counts()
-                    peak_h = int(hour_counts.idxmax())
-                    count = int(hour_counts.max())
-                    insight_lines.append(f"• Position {pos}, 18:00–00:00: Peak Red alarm at {peak_h:02d}:00 ({count} occurrences).")
-
-                amber_band2 = band2[band2['is_amber']]
-                if not amber_band2.empty:
-                    hour_counts = amber_band2['hour'].value_counts()
-                    peak_h = int(hour_counts.idxmax())
-                    count = int(hour_counts.max())
-                    insight_lines.append(f"• Position {pos}, 18:00–00:00: Peak Amber alarm at {peak_h:02d}:00 ({count} occurrences).")
-
-        # Jika insight_lines masih kosong (misal: semua alarm di pos 5+), tambahkan fallback
+                red_sub = band2[band2['is_red']]
+                if not red_sub.empty:
+                    h_peak = int(red_sub['hour'].value_counts().idxmax())
+                    c_peak = int(red_sub['hour'].value_counts().max())
+                    insight_lines.append(f"• Position {pos}, 18:00–00:00: Peak Red alarm at {h_peak:02d}:00 ({c_peak} occurrences).")
+
+                amber_sub = band2[band2['is_amber']]
+                if not amber_sub.empty:
+                    h_peak = int(amber_sub['hour'].value_counts().idxmax())
+                    c_peak = int(amber_sub['hour'].value_counts().max())
+                    insight_lines.append(f"• Position {pos}, 18:00–00:00: Peak Amber alarm at {h_peak:02d}:00 ({c_peak} occurrences).")
+
+        # Jika tidak ada alarm di posisi 1–4
         if not insight_lines:
             insight_lines = ["• Red and Amber alarms occur outside standard wheel positions (1–4)."]
 
-# =============== TAMBAHKAN INSIGHT NARATIF (SESUAI YANG ANDA TULISKAN) ===============
-# Catatan: Ini bukan hasil komputasi, tapi insight profesional berdasarkan pola umum.
-# Disesuaikan dengan preferensi: business-ready, actionable, tanpa spekulasi root cause.
-
-# Cek apakah ada front tyre (pos 1/2) dan rear tyre (pos 3/4) Red/Amber
+# ————— Tambahkan insight naratif (sesuai contoh Anda) —————
 has_front_red = not red_amber_data[(red_amber_data['Position'].isin([1, 2])) & (red_amber_data['is_red'])].empty
 has_rear_amber = not red_amber_data[(red_amber_data['Position'].isin([3, 4])) & (red_amber_data['is_amber'])].empty
 
 if has_front_red or has_rear_amber:
-    # Tambahkan insight berbasis pola operasional (hard-coded, validasi berdasarkan pengalaman lapangan)
-    insight_lines.append("")
-    insight_lines.append("Front tyres:")
-    insight_lines.append("1. The front tyre pressure is high, close to threshold, with a small number of Red alarms. However, as operating time increases, the number of Red alarms rises significantly. Furthermore, during 04:00–06:00, operational slowdown likely occurs — leading to a decrease in Red alarm notifications.")
-
-    insight_lines.append("")
-    insight_lines.append("Rear tyres:")
-    insight_lines.append("2. When the unit begins operation, notifications often indicate pressure below the minimum threshold due to initially low rear tyre pressure. As a result, Amber alarms do not occur during operation since pressure remains within the defined threshold range.")
+    insight_lines.extend([
+        "• The front tyre pressure is high, close to threshold, with a small number of Red alarms. However, as operating time increases, the number of Red alarms rises significantly. Furthermore, during 04:00–06:00, operational slowdown likely occurs — leading to a decrease in Red alarm notifications.",
+        "• When the unit begins operation, notifications often indicate pressure below the minimum threshold due to initially low rear tyre pressure. As a result, Amber alarms do not occur during operation since pressure remains within the defined threshold range."
+    ])
 
-# =============== DISPLAY ===============
+# Gabungkan jadi satu string, tiap baris baru → \n
 insight_text = "\n".join(insight_lines)
 
+# ————— TAMPILKAN (RATA KIRI) —————
+st.markdown('<h4 style="text-align:center; margin:10px 0 5px 0; font-weight:bold;">INSIGHTS</h4>', unsafe_allow_html=True)
 st.markdown(f"""
 <div class="insight-box">
     <div class="content" style="