Update app.py

app.py

@@ -724,169 +724,502 @@ st.markdown(f"""
 # </div>
 # """, unsafe_allow_html=True)
 st.markdown("""
-<h3 class="objective-title">OBJECTIVE 3: Alarm Frequency Analysis — When, Where, and Which Tyres Matter Most?</h3>
-<small>*Showing all alarm types: Normal (Green), Amber (Yellow), Red (Red)</small>
+<h3 class="objective-title">OBJECTIVE 3: Alarm Frequency Analysis — Shift-Based Radial Charts</h3>
+<small>*Showing alarm types by shift: Normal (Green), Amber (Yellow), Red (Red)</small>
 """, unsafe_allow_html=True)
 
 # Filter semua data (termasuk alarm normal)
 alarm_data = dff.copy()
 
-col_b, col_a = st.columns(2)
-
-# =============== COL B: Donut Charts (Distribusi Alarm per Position - Semua Jenis) ===============
-with col_b:
-    st.markdown('<h5 style="text-align:center; margin-top: 0;">Alarm Distribution by Position</h5>', unsafe_allow_html=True)
+col1, col2 = st.columns(2)
 
-    if alarm_data.empty:
-        st.warning("No data to display.")
+# =============== COL 1: Position 1 & 3 (Pagi & Sore) ===============
+with col1:
+    # Position 1 Pagi
+    st.markdown('<h6 style="text-align:center; margin-top: 0;">Position 1 (06:00–18:00)</h6>', unsafe_allow_html=True)
+    if not alarm_data[alarm_data['Position'] == 1].empty:
+        pos1_data = alarm_data[alarm_data['Position'] == 1].copy()
+        pos1_data = pos1_data[pos1_data['hour'].between(6, 17, inclusive='both')]
+
+        if not pos1_data.empty:
+            hourly_status_counts = pos1_data.groupby(['hour', 'Alarm Status']).size().unstack(fill_value=0)
+
+            hourly_normal = hourly_status_counts.get('No Alarm', pd.Series(0, index=range(6, 18))).reindex(range(6, 18), fill_value=0)
+            hourly_amber = hourly_status_counts.get('Amber High Pressure', pd.Series(0, index=range(6, 18))).reindex(range(6, 18), fill_value=0)
+            hourly_red = hourly_status_counts.get('Red High Pressure', pd.Series(0, index=range(6, 18))).reindex(range(6, 18), fill_value=0)
+
+            theta = [(h - 6) * 30 for h in range(6, 18)]  # 12 jam * 30° = 360°
+
+            fig1 = go.Figure()
+            fig1.add_trace(go.Barpolar(
+                r=hourly_normal.values,
+                theta=theta,
+                name='Normal',
+                marker_color='#2E7D32',
+                opacity=0.8
+            ))
+            fig1.add_trace(go.Barpolar(
+                r=hourly_amber.values,
+                theta=theta,
+                name='Amber',
+                marker_color='#FFC107',
+                opacity=0.8
+            ))
+            fig1.add_trace(go.Barpolar(
+                r=hourly_red.values,
+                theta=theta,
+                name='Red',
+                marker_color='#D32F2F',
+                opacity=0.8
+            ))
+            fig1.update_layout(
+                polar=dict(
+                    angularaxis=dict(
+                        direction="clockwise",
+                        period=12,
+                        rotation=0,
+                        tickvals=[0, 90, 180, 270],
+                        ticktext=["06:00", "12:00", "18:00", "24:00"],
+                        tickfont=dict(size=10)
+                    ),
+                    radialaxis=dict(visible=True)
+                ),
+                showlegend=False,
+                margin=dict(t=30, b=20, l=20, r=20),
+                height=250
+            )
+            st.plotly_chart(fig1, use_container_width=True)
+        else:
+            st.warning("No data for Position 1 (06:00–18:00)")
     else:
-        # Group alarm status sesuai permintaan Anda
-        alarm_data['Alarm_Category'] = alarm_data['Alarm Status'].apply(
-            lambda x: 'Normal' if x == 'No Alarm'
-            else 'Red Alarm' if x == 'Red High Pressure'
-            else 'Amber Alarm'
-        )
-
-        # Buat 4 donut chart
-        fig_donut = make_subplots(
-            rows=2, cols=2,
-            specs=[[{'type':'domain'}, {'type':'domain'}],
-                   [{'type':'domain'}, {'type':'domain'}]],
-            subplot_titles=['Position 1', 'Position 2', 'Position 3', 'Position 4']
-        )
-
-        for i, pos in enumerate([1, 2, 3, 4], 1):
-            pos_data = alarm_data[alarm_data['Position'] == pos]
-            if not pos_data.empty:
-                counts = pos_data['Alarm_Category'].value_counts()
-                labels = counts.index.tolist()
-                values = counts.values.tolist()
-
-                # Warna: Hijau (Normal), Kuning (Amber), Merah (Red)
-                color_map = {
-                    'Normal': '#2E7D32',      # Hijau
-                    'Amber Alarm': '#FFC107', # Kuning
-                    'Red Alarm': '#D32F2F'    # Merah
-                }
-                colors = [color_map[label] for label in labels]
-
-                fig_donut.add_trace(
-                    go.Pie(
-                        labels=labels,
-                        values=values,
-                        name=f'Position {pos}',
-                        hole=0.4,
-                        marker_colors=colors
+        st.warning("No data for Position 1")
+
+    # Position 1 Sore
+    st.markdown('<h6 style="text-align:center; margin-top: 0;">Position 1 (18:00–06:00)</h6>', unsafe_allow_html=True)
+    if not alarm_data[alarm_data['Position'] == 1].empty:
+        pos1_data = alarm_data[alarm_data['Position'] == 1].copy()
+        pos1_data = pos1_data[~pos1_data['hour'].between(6, 17, inclusive='both')]
+
+        if not pos1_data.empty:
+            hourly_status_counts = pos1_data.groupby(['hour', 'Alarm Status']).size().unstack(fill_value=0)
+
+            hourly_normal = pd.concat([hourly_status_counts.get('No Alarm', pd.Series(0, index=range(18, 24))).reindex(range(18, 24), fill_value=0),
+                                      hourly_status_counts.get('No Alarm', pd.Series(0, index=range(0, 6))).reindex(range(0, 6), fill_value=0)]).values
+            hourly_amber = pd.concat([hourly_status_counts.get('Amber High Pressure', pd.Series(0, index=range(18, 24))).reindex(range(18, 24), fill_value=0),
+                                     hourly_status_counts.get('Amber High Pressure', pd.Series(0, index=range(0, 6))).reindex(range(0, 6), fill_value=0)]).values
+            hourly_red = pd.concat([hourly_status_counts.get('Red High Pressure', pd.Series(0, index=range(18, 24))).reindex(range(18, 24), fill_value=0),
+                                   hourly_status_counts.get('Red High Pressure', pd.Series(0, index=range(0, 6))).reindex(range(0, 6), fill_value=0)]).values
+
+            theta = [(h - 18) * 30 for h in range(18, 24)] + [(h + 6) * 30 for h in range(0, 6)]  # 12 jam * 30° = 360°
+
+            fig2 = go.Figure()
+            fig2.add_trace(go.Barpolar(
+                r=hourly_normal,
+                theta=theta,
+                name='Normal',
+                marker_color='#2E7D32',
+                opacity=0.8
+            ))
+            fig2.add_trace(go.Barpolar(
+                r=hourly_amber,
+                theta=theta,
+                name='Amber',
+                marker_color='#FFC107',
+                opacity=0.8
+            ))
+            fig2.add_trace(go.Barpolar(
+                r=hourly_red,
+                theta=theta,
+                name='Red',
+                marker_color='#D32F2F',
+                opacity=0.8
+            ))
+            fig2.update_layout(
+                polar=dict(
+                    angularaxis=dict(
+                        direction="clockwise",
+                        period=12,
+                        rotation=0,
+                        tickvals=[0, 90, 180, 270],
+                        ticktext=["18:00", "24:00", "06:00", "12:00"],
+                        tickfont=dict(size=10)
                     ),
-                    row=(i - 1) // 2 + 1,
-                    col=(i - 1) % 2 + 1
-                )
-
-        fig_donut.update_layout(
-            height=500,
-            showlegend=True,
-            margin=dict(t=40, b=20, l=20, r=20),
-            legend=dict(
-                orientation="h",
-                yanchor="bottom",
-                y=1.02,
-                xanchor="right",
-                x=1
+                    radialaxis=dict(visible=True)
+                ),
+                showlegend=False,
+                margin=dict(t=30, b=20, l=20, r=20),
+                height=250
             )
-        )
-        st.plotly_chart(fig_donut, use_container_width=True)
-
-# =============== COL A: Radial Charts (Count Alarm per Jam - Stacked by Status) ===============
-with col_a:
-    st.markdown('<h5 style="text-align:center; margin-top: 0;">Alarm Count by Hour (Radial - Stacked)</h5>', unsafe_allow_html=True)
-
-    if alarm_data.empty:
-        st.warning("No data to display.")
+            st.plotly_chart(fig2, use_container_width=True)
+        else:
+            st.warning("No data for Position 1 (18:00–06:00)")
     else:
-        # Buat 4 radial chart
-        fig_radial = make_subplots(
-            rows=2, cols=2,
-            specs=[[{'type': 'polar'}, {'type': 'polar'}],
-                   [{'type': 'polar'}, {'type': 'polar'}]],
-            subplot_titles=['Position 1', 'Position 2', 'Position 3', 'Position 4']
-        )
-
-        for i, pos in enumerate([1, 2, 3, 4], 1):
-            pos_data = alarm_data[alarm_data['Position'] == pos].copy()
-            if not pos_data.empty:
-                # Kelompokkan jam dan status
-                hourly_status_counts = pos_data.groupby(['hour', 'Alarm Status']).size().unstack(fill_value=0)
-
-                # Ambil masing-masing kategori
-                hourly_normal = hourly_status_counts.get('No Alarm', pd.Series(0, index=range(24)))
-                hourly_amber = hourly_status_counts.get('Amber High Pressure', pd.Series(0, index=range(24)))  # Ganti sesuai nama kolom Anda
-                hourly_red = hourly_status_counts.get('Red High Pressure', pd.Series(0, index=range(24)))
-
-                # Total per jam
-                total_per_hour = hourly_normal + hourly_amber + hourly_red
-
-                # Sudut: jam 3 → 0° (atas), jam 12 → 90° (kanan), jam 9 → 180° (bawah), jam 6 → 270° (kiri)
-                theta = [(h - 3) * 15 % 360 for h in range(24)]  # Jam 3 pagi = 0°
-
-                # Tambahkan bar polar untuk Normal (hijau)
-                fig_radial.add_trace(
-                    go.Barpolar(
-                        r=hourly_normal.values,
-                        theta=theta,
-                        name='Normal',
-                        marker_color='#2E7D32',  # Hijau
-                        opacity=0.8
+        st.warning("No data for Position 1")
+
+    # Position 3 Pagi
+    st.markdown('<h6 style="text-align:center; margin-top: 0;">Position 3 (06:00–18:00)</h6>', unsafe_allow_html=True)
+    if not alarm_data[alarm_data['Position'] == 3].empty:
+        pos3_data = alarm_data[alarm_data['Position'] == 3].copy()
+        pos3_data = pos3_data[pos3_data['hour'].between(6, 17, inclusive='both')]
+
+        if not pos3_data.empty:
+            hourly_status_counts = pos3_data.groupby(['hour', 'Alarm Status']).size().unstack(fill_value=0)
+
+            hourly_normal = hourly_status_counts.get('No Alarm', pd.Series(0, index=range(6, 18))).reindex(range(6, 18), fill_value=0)
+            hourly_amber = hourly_status_counts.get('Amber High Pressure', pd.Series(0, index=range(6, 18))).reindex(range(6, 18), fill_value=0)
+            hourly_red = hourly_status_counts.get('Red High Pressure', pd.Series(0, index=range(6, 18))).reindex(range(6, 18), fill_value=0)
+
+            theta = [(h - 6) * 30 for h in range(6, 18)]  # 12 jam * 30° = 360°
+
+            fig3 = go.Figure()
+            fig3.add_trace(go.Barpolar(
+                r=hourly_normal.values,
+                theta=theta,
+                name='Normal',
+                marker_color='#2E7D32',
+                opacity=0.8
+            ))
+            fig3.add_trace(go.Barpolar(
+                r=hourly_amber.values,
+                theta=theta,
+                name='Amber',
+                marker_color='#FFC107',
+                opacity=0.8
+            ))
+            fig3.add_trace(go.Barpolar(
+                r=hourly_red.values,
+                theta=theta,
+                name='Red',
+                marker_color='#D32F2F',
+                opacity=0.8
+            ))
+            fig3.update_layout(
+                polar=dict(
+                    angularaxis=dict(
+                        direction="clockwise",
+                        period=12,
+                        rotation=0,
+                        tickvals=[0, 90, 180, 270],
+                        ticktext=["06:00", "12:00", "18:00", "24:00"],
+                        tickfont=dict(size=10)
                     ),
-                    row=(i - 1) // 2 + 1,
-                    col=(i - 1) % 2 + 1
-                )
-
-                # Tambahkan bar polar untuk Amber (kuning) — ditumpuk di atas Normal
-                fig_radial.add_trace(
-                    go.Barpolar(
-                        r=hourly_amber.values,
-                        theta=theta,
-                        name='Amber',
-                        marker_color='#FFC107',  # Kuning
-                        opacity=0.8
+                    radialaxis=dict(visible=True)
+                ),
+                showlegend=False,
+                margin=dict(t=30, b=20, l=20, r=20),
+                height=250
+            )
+            st.plotly_chart(fig3, use_container_width=True)
+        else:
+            st.warning("No data for Position 3 (06:00–18:00)")
+    else:
+        st.warning("No data for Position 3")
+
+    # Position 3 Sore
+    st.markdown('<h6 style="text-align:center; margin-top: 0;">Position 3 (18:00–06:00)</h6>', unsafe_allow_html=True)
+    if not alarm_data[alarm_data['Position'] == 3].empty:
+        pos3_data = alarm_data[alarm_data['Position'] == 3].copy()
+        pos3_data = pos3_data[~pos3_data['hour'].between(6, 17, inclusive='both')]
+
+        if not pos3_data.empty:
+            hourly_status_counts = pos3_data.groupby(['hour', 'Alarm Status']).size().unstack(fill_value=0)
+
+            hourly_normal = pd.concat([hourly_status_counts.get('No Alarm', pd.Series(0, index=range(18, 24))).reindex(range(18, 24), fill_value=0),
+                                      hourly_status_counts.get('No Alarm', pd.Series(0, index=range(0, 6))).reindex(range(0, 6), fill_value=0)]).values
+            hourly_amber = pd.concat([hourly_status_counts.get('Amber High Pressure', pd.Series(0, index=range(18, 24))).reindex(range(18, 24), fill_value=0),
+                                     hourly_status_counts.get('Amber High Pressure', pd.Series(0, index=range(0, 6))).reindex(range(0, 6), fill_value=0)]).values
+            hourly_red = pd.concat([hourly_status_counts.get('Red High Pressure', pd.Series(0, index=range(18, 24))).reindex(range(18, 24), fill_value=0),
+                                   hourly_status_counts.get('Red High Pressure', pd.Series(0, index=range(0, 6))).reindex(range(0, 6), fill_value=0)]).values
+
+            theta = [(h - 18) * 30 for h in range(18, 24)] + [(h + 6) * 30 for h in range(0, 6)]  # 12 jam * 30° = 360°
+
+            fig4 = go.Figure()
+            fig4.add_trace(go.Barpolar(
+                r=hourly_normal,
+                theta=theta,
+                name='Normal',
+                marker_color='#2E7D32',
+                opacity=0.8
+            ))
+            fig4.add_trace(go.Barpolar(
+                r=hourly_amber,
+                theta=theta,
+                name='Amber',
+                marker_color='#FFC107',
+                opacity=0.8
+            ))
+            fig4.add_trace(go.Barpolar(
+                r=hourly_red,
+                theta=theta,
+                name='Red',
+                marker_color='#D32F2F',
+                opacity=0.8
+            ))
+            fig4.update_layout(
+                polar=dict(
+                    angularaxis=dict(
+                        direction="clockwise",
+                        period=12,
+                        rotation=0,
+                        tickvals=[0, 90, 180, 270],
+                        ticktext=["18:00", "24:00", "06:00", "12:00"],
+                        tickfont=dict(size=10)
                     ),
-                    row=(i - 1) // 2 + 1,
-                    col=(i - 1) % 2 + 1
-                )
+                    radialaxis=dict(visible=True)
+                ),
+                showlegend=False,
+                margin=dict(t=30, b=20, l=20, r=20),
+                height=250
+            )
+            st.plotly_chart(fig4, use_container_width=True)
+        else:
+            st.warning("No data for Position 3 (18:00–06:00)")
+    else:
+        st.warning("No data for Position 3")
 
-                # Tambahkan bar polar untuk Red (merah) — ditumpuk di atas Amber
-                fig_radial.add_trace(
-                    go.Barpolar(
-                        r=hourly_red.values,
-                        theta=theta,
-                        name='Red',
-                        marker_color='#D32F2F',  # Merah
-                        opacity=0.8
+# =============== COL 2: Position 2 & 4 (Pagi & Sore) ===============
+with col2:
+    # Position 2 Pagi
+    st.markdown('<h6 style="text-align:center; margin-top: 0;">Position 2 (06:00–18:00)</h6>', unsafe_allow_html=True)
+    if not alarm_data[alarm_data['Position'] == 2].empty:
+        pos2_data = alarm_data[alarm_data['Position'] == 2].copy()
+        pos2_data = pos2_data[pos2_data['hour'].between(6, 17, inclusive='both')]
+
+        if not pos2_data.empty:
+            hourly_status_counts = pos2_data.groupby(['hour', 'Alarm Status']).size().unstack(fill_value=0)
+
+            hourly_normal = hourly_status_counts.get('No Alarm', pd.Series(0, index=range(6, 18))).reindex(range(6, 18), fill_value=0)
+            hourly_amber = hourly_status_counts.get('Amber High Pressure', pd.Series(0, index=range(6, 18))).reindex(range(6, 18), fill_value=0)
+            hourly_red = hourly_status_counts.get('Red High Pressure', pd.Series(0, index=range(6, 18))).reindex(range(6, 18), fill_value=0)
+
+            theta = [(h - 6) * 30 for h in range(6, 18)]  # 12 jam * 30° = 360°
+
+            fig5 = go.Figure()
+            fig5.add_trace(go.Barpolar(
+                r=hourly_normal.values,
+                theta=theta,
+                name='Normal',
+                marker_color='#2E7D32',
+                opacity=0.8
+            ))
+            fig5.add_trace(go.Barpolar(
+                r=hourly_amber.values,
+                theta=theta,
+                name='Amber',
+                marker_color='#FFC107',
+                opacity=0.8
+            ))
+            fig5.add_trace(go.Barpolar(
+                r=hourly_red.values,
+                theta=theta,
+                name='Red',
+                marker_color='#D32F2F',
+                opacity=0.8
+            ))
+            fig5.update_layout(
+                polar=dict(
+                    angularaxis=dict(
+                        direction="clockwise",
+                        period=12,
+                        rotation=0,
+                        tickvals=[0, 90, 180, 270],
+                        ticktext=["06:00", "12:00", "18:00", "24:00"],
+                        tickfont=dict(size=10)
                     ),
-                    row=(i - 1) // 2 + 1,
-                    col=(i - 1) % 2 + 1
-                )
-
-        fig_radial.update_layout(
-            height=600,
-            showlegend=False,
-            margin=dict(t=60, b=20, l=20, r=20),
-            polar=dict(
-                angularaxis=dict(
-                    direction="clockwise",
-                    period=24,
-                    rotation=0,  # Jam 3 pagi di atas
-                    tickvals=[0, 90, 180, 270],
-                    ticktext=["03:00", "12:00", "21:00", "18:00"],
-                    tickfont=dict(size=12)
+                    radialaxis=dict(visible=True)
                 ),
-                radialaxis=dict(
-                    visible=True,
-                    range=[0, max(total_per_hour.max() * 1.1, 1)]
-                )
+                showlegend=False,
+                margin=dict(t=30, b=20, l=20, r=20),
+                height=250
             )
-        )
-        st.plotly_chart(fig_radial, use_container_width=True)
+            st.plotly_chart(fig5, use_container_width=True)
+        else:
+            st.warning("No data for Position 2 (06:00–18:00)")
+    else:
+        st.warning("No data for Position 2")
+
+    # Position 2 Sore
+    st.markdown('<h6 style="text-align:center; margin-top: 0;">Position 2 (18:00–06:00)</h6>', unsafe_allow_html=True)
+    if not alarm_data[alarm_data['Position'] == 2].empty:
+        pos2_data = alarm_data[alarm_data['Position'] == 2].copy()
+        pos2_data = pos2_data[~pos2_data['hour'].between(6, 17, inclusive='both')]
+
+        if not pos2_data.empty:
+            hourly_status_counts = pos2_data.groupby(['hour', 'Alarm Status']).size().unstack(fill_value=0)
+
+            hourly_normal = pd.concat([hourly_status_counts.get('No Alarm', pd.Series(0, index=range(18, 24))).reindex(range(18, 24), fill_value=0),
+                                      hourly_status_counts.get('No Alarm', pd.Series(0, index=range(0, 6))).reindex(range(0, 6), fill_value=0)]).values
+            hourly_amber = pd.concat([hourly_status_counts.get('Amber High Pressure', pd.Series(0, index=range(18, 24))).reindex(range(18, 24), fill_value=0),
+                                     hourly_status_counts.get('Amber High Pressure', pd.Series(0, index=range(0, 6))).reindex(range(0, 6), fill_value=0)]).values
+            hourly_red = pd.concat([hourly_status_counts.get('Red High Pressure', pd.Series(0, index=range(18, 24))).reindex(range(18, 24), fill_value=0),
+                                   hourly_status_counts.get('Red High Pressure', pd.Series(0, index=range(0, 6))).reindex(range(0, 6), fill_value=0)]).values
+
+            theta = [(h - 18) * 30 for h in range(18, 24)] + [(h + 6) * 30 for h in range(0, 6)]  # 12 jam * 30° = 360°
+
+            fig6 = go.Figure()
+            fig6.add_trace(go.Barpolar(
+                r=hourly_normal,
+                theta=theta,
+                name='Normal',
+                marker_color='#2E7D32',
+                opacity=0.8
+            ))
+            fig6.add_trace(go.Barpolar(
+                r=hourly_amber,
+                theta=theta,
+                name='Amber',
+                marker_color='#FFC107',
+                opacity=0.8
+            ))
+            fig6.add_trace(go.Barpolar(
+                r=hourly_red,
+                theta=theta,
+                name='Red',
+                marker_color='#D32F2F',
+                opacity=0.8
+            ))
+            fig6.update_layout(
+                polar=dict(
+                    angularaxis=dict(
+                        direction="clockwise",
+                        period=12,
+                        rotation=0,
+                        tickvals=[0, 90, 180, 270],
+                        ticktext=["18:00", "24:00", "06:00", "12:00"],
+                        tickfont=dict(size=10)
+                    ),
+                    radialaxis=dict(visible=True)
+                ),
+                showlegend=False,
+                margin=dict(t=30, b=20, l=20, r=20),
+                height=250
+            )
+            st.plotly_chart(fig6, use_container_width=True)
+        else:
+            st.warning("No data for Position 2 (18:00–06:00)")
+    else:
+        st.warning("No data for Position 2")
+
+    # Position 4 Pagi
+    st.markdown('<h6 style="text-align:center; margin-top: 0;">Position 4 (06:00–18:00)</h6>', unsafe_allow_html=True)
+    if not alarm_data[alarm_data['Position'] == 4].empty:
+        pos4_data = alarm_data[alarm_data['Position'] == 4].copy()
+        pos4_data = pos4_data[pos4_data['hour'].between(6, 17, inclusive='both')]
+
+        if not pos4_data.empty:
+            hourly_status_counts = pos4_data.groupby(['hour', 'Alarm Status']).size().unstack(fill_value=0)
+
+            hourly_normal = hourly_status_counts.get('No Alarm', pd.Series(0, index=range(6, 18))).reindex(range(6, 18), fill_value=0)
+            hourly_amber = hourly_status_counts.get('Amber High Pressure', pd.Series(0, index=range(6, 18))).reindex(range(6, 18), fill_value=0)
+            hourly_red = hourly_status_counts.get('Red High Pressure', pd.Series(0, index=range(6, 18))).reindex(range(6, 18), fill_value=0)
+
+            theta = [(h - 6) * 30 for h in range(6, 18)]  # 12 jam * 30° = 360°
+
+            fig7 = go.Figure()
+            fig7.add_trace(go.Barpolar(
+                r=hourly_normal.values,
+                theta=theta,
+                name='Normal',
+                marker_color='#2E7D32',
+                opacity=0.8
+            ))
+            fig7.add_trace(go.Barpolar(
+                r=hourly_amber.values,
+                theta=theta,
+                name='Amber',
+                marker_color='#FFC107',
+                opacity=0.8
+            ))
+            fig7.add_trace(go.Barpolar(
+                r=hourly_red.values,
+                theta=theta,
+                name='Red',
+                marker_color='#D32F2F',
+                opacity=0.8
+            ))
+            fig7.update_layout(
+                polar=dict(
+                    angularaxis=dict(
+                        direction="clockwise",
+                        period=12,
+                        rotation=0,
+                        tickvals=[0, 90, 180, 270],
+                        ticktext=["06:00", "12:00", "18:00", "24:00"],
+                        tickfont=dict(size=10)
+                    ),
+                    radialaxis=dict(visible=True)
+                ),
+                showlegend=False,
+                margin=dict(t=30, b=20, l=20, r=20),
+                height=250
+            )
+            st.plotly_chart(fig7, use_container_width=True)
+        else:
+            st.warning("No data for Position 4 (06:00–18:00)")
+    else:
+        st.warning("No data for Position 4")
+
+    # Position 4 Sore
+    st.markdown('<h6 style="text-align:center; margin-top: 0;">Position 4 (18:00–06:00)</h6>', unsafe_allow_html=True)
+    if not alarm_data[alarm_data['Position'] == 4].empty:
+        pos4_data = alarm_data[alarm_data['Position'] == 4].copy()
+        pos4_data = pos4_data[~pos4_data['hour'].between(6, 17, inclusive='both')]
+
+        if not pos4_data.empty:
+            hourly_status_counts = pos4_data.groupby(['hour', 'Alarm Status']).size().unstack(fill_value=0)
+
+            hourly_normal = pd.concat([hourly_status_counts.get('No Alarm', pd.Series(0, index=range(18, 24))).reindex(range(18, 24), fill_value=0),
+                                      hourly_status_counts.get('No Alarm', pd.Series(0, index=range(0, 6))).reindex(range(0, 6), fill_value=0)]).values
+            hourly_amber = pd.concat([hourly_status_counts.get('Amber High Pressure', pd.Series(0, index=range(18, 24))).reindex(range(18, 24), fill_value=0),
+                                     hourly_status_counts.get('Amber High Pressure', pd.Series(0, index=range(0, 6))).reindex(range(0, 6), fill_value=0)]).values
+            hourly_red = pd.concat([hourly_status_counts.get('Red High Pressure', pd.Series(0, index=range(18, 24))).reindex(range(18, 24), fill_value=0),
+                                   hourly_status_counts.get('Red High Pressure', pd.Series(0, index=range(0, 6))).reindex(range(0, 6), fill_value=0)]).values
+
+            theta = [(h - 18) * 30 for h in range(18, 24)] + [(h + 6) * 30 for h in range(0, 6)]  # 12 jam * 30° = 360°
+
+            fig8 = go.Figure()
+            fig8.add_trace(go.Barpolar(
+                r=hourly_normal,
+                theta=theta,
+                name='Normal',
+                marker_color='#2E7D32',
+                opacity=0.8
+            ))
+            fig8.add_trace(go.Barpolar(
+                r=hourly_amber,
+                theta=theta,
+                name='Amber',
+                marker_color='#FFC107',
+                opacity=0.8
+            ))
+            fig8.add_trace(go.Barpolar(
+                r=hourly_red,
+                theta=theta,
+                name='Red',
+                marker_color='#D32F2F',
+                opacity=0.8
+            ))
+            fig8.update_layout(
+                polar=dict(
+                    angularaxis=dict(
+                        direction="clockwise",
+                        period=12,
+                        rotation=0,
+                        tickvals=[0, 90, 180, 270],
+                        ticktext=["18:00", "24:00", "06:00", "12:00"],
+                        tickfont=dict(size=10)
+                    ),
+                    radialaxis=dict(visible=True)
+                ),
+                showlegend=False,
+                margin=dict(t=30, b=20, l=20, r=20),
+                height=250
+            )
+            st.plotly_chart(fig8, use_container_width=True)
+        else:
+            st.warning("No data for Position 4 (18:00–06:00)")
+    else:
+        st.warning("No data for Position 4")
 
 # =============== INSIGHT 3 ===============
 if alarm_data.empty:
@@ -932,6 +1265,7 @@ st.markdown(f"""
     </div>
 </div>
 """, unsafe_allow_html=True)
+
 # ================= OBJECTIVE 3 =================
 st.markdown('<h3 class="objective-title">OBJECTIVE 4: Correlation — How Does Heat Influence Pressure and Which Tyres Trigger Red Alarms?</h3>', unsafe_allow_html=True)