Update app.py

app.py

@@ -598,75 +598,70 @@ findings_by_location_month = df_local.groupby(['created_month', 'nama_lokasi_ful
 creators_by_location_month = df_local.groupby(['created_month', 'nama_lokasi_full'])['creator_nid'].nunique().reset_index(name='unique_creators')
 # Gabung
 merged_loc = findings_by_location_month.merge(creators_by_location_month, on=['created_month', 'nama_lokasi_full'], how='outer')
-# Isi NaN dengan 0 untuk kolom yang mungkin hilang dari merge
+# Isi NaN dengan 0
 merged_loc = merged_loc.fillna({'findings_count': 0, 'unique_creators': 0})
-# Filter untuk menghindari pembagian dengan nol
+# Hindari pembagian dengan nol
 merged_loc = merged_loc[merged_loc['unique_creators'] > 0]
-# Hitung rasio (ignore NaN)
+# Hitung rasio
 merged_loc['ratio'] = merged_loc['findings_count'] / merged_loc['unique_creators']
 merged_loc['ratio'] = merged_loc['ratio'].replace([np.inf, -np.inf], np.nan)
 
 # Rata-rata bulanan per lokasi
 avg_ratio_per_location = merged_loc.groupby('nama_lokasi_full')['ratio'].mean().reset_index(name='avg_monthly_ratio')
-
-# Filter hasil akhir untuk menghindari NaN
 avg_ratio_per_location = avg_ratio_per_location.dropna(subset=['avg_monthly_ratio'])
 
 if avg_ratio_per_location.empty:
     st.write("Data kosong.")
 else:
-    # Treemap dengan gradasi warna merah → kuning → hijau
+    # Treemap — hanya dibuat & ditampilkan sekali
     fig_treemap = px.treemap(
         avg_ratio_per_location,
-        path=['nama_lokasi_full'],          # Hierarki (single level)
-        values='avg_monthly_ratio',         # Ukuran area
-        title='Avg Monthly Finding by Location',
+        path=['nama_lokasi_full'],
+        values='avg_monthly_ratio',
+        title='Avg Monthly Finding/Person Ratio by Location',
         labels={
             'avg_monthly_ratio': 'Avg Monthly Finding/Person Ratio',
             'nama_lokasi_full': 'Location'
         },
-        color='avg_monthly_ratio',          # Warna berdasarkan nilai rasio
+        color='avg_monthly_ratio',
         color_continuous_scale=[
-            [0.0, '#D32F2F'],   # Merah (rendah)
-            [0.5, '#FFB300'],   # Kuning (sedang)
-            [1.0, '#4CAF50']    # Hijau (tinggi)
-        ]
+            [0.0, '#D32F2F'],   # Red (low activity)
+            [0.5, '#FFB300'],   # Amber/orange-yellow (medium)
+            [1.0, '#4CAF50']    # Green (high activity)
+        ],
+        hover_data={'avg_monthly_ratio': ':.2f'}  # pastikan format hover sudah 2 desimal
     )
 
-    st.plotly_chart(fig_treemap, use_container_width=True)
-
-    # Format hover
+    # Perbaiki tata letak & hover — lakukan *sebelum* menampilkan
     fig_treemap.update_traces(
         hovertemplate="<b>%{label}</b><br>Avg Ratio: %{value:.2f}<extra></extra>"
     )
-    fig_treemap.update_layout(height=600)
-    st.plotly_chart(fig_treemap, use_container_width=True)
+    fig_treemap.update_layout(
+        title=dict(text='Avg Monthly Finding/Person Ratio by Location', x=0.5, xanchor='center'),
+        height=600,
+        margin=dict(t=50, l=25, r=25, b=25)
+    )
 
-    # AI Insight untuk Treemap Lokasi (Business-focused)
-    if not avg_ratio_per_location.empty:
-        # Temukan lokasi dengan rasio tertinggi dan terendah
-        top_location = avg_ratio_per_location.loc[avg_ratio_per_location['avg_monthly_ratio'].idxmax()]
-        low_location = avg_ratio_per_location.loc[avg_ratio_per_location['avg_monthly_ratio'].idxmin()]
-
-        st.markdown("### Insight")
-        insight_text = (
-            # f"<div class='ai-insight'>"
-            # f"The treemap visualizes the average finding-to-person ratio per location using a <strong>color gradient</strong>, indicating reporting activity levels. "
-            # f"Locations with <span style='color:#4CAF50; font-weight:bold;'>green</span> color have a high ratio, indicating high reporting activity or exposure. "
-            # f"Those with <span style='color:#FFB300; font-weight:bold;'>yellow</span> color have a medium ratio, indicating moderate reporting. "
-            # f"Locations with <span style='color:#D32F2F; font-weight:bold;'>red</span> color have a low ratio, indicating lower activity levels or potentially under-reporting. "
-            f"<strong>{top_location['nama_lokasi_full']}</strong> shows the highest activity level "
-            f"(<strong>{top_location['avg_monthly_ratio']:.2f}</strong>). "
-            f"<strong>{low_location['nama_lokasi_full']}</strong> is one of areas with the lowest activity level "
-            f"(<strong>{low_location['avg_monthly_ratio']:.2f}</strong>). "
-            f"Areas with high activity (green) warrant inspection into the underlying causes of frequent findings. "
-            f"Areas with low activity (red) should be reviewed to ensure reporting completeness and identify any hidden risks."
-            f"</div>"
-        )
-        st.markdown(insight_text, unsafe_allow_html=True)
-    else:
-        st.warning("No data available for location ratio calculation or all ratios are NaN.")
+    # Tampilkan hanya sekali!
+    st.plotly_chart(fig_treemap, use_container_width=True)
 
+    # === AI Insight ===
+    top_location = avg_ratio_per_location.loc[avg_ratio_per_location['avg_monthly_ratio'].idxmax()]
+    low_location = avg_ratio_per_location.loc[avg_ratio_per_location['avg_monthly_ratio'].idxmin()]
+
+    st.markdown("### Insight")
+    insight_text = (
+        f"<div class='ai-insight'>"
+        f"<strong>{top_location['nama_lokasi_full']}</strong> shows the highest activity level "
+        f"(<strong>{top_location['avg_monthly_ratio']:.2f}</strong> findings per person/month). "
+        f"In contrast, <strong>{low_location['nama_lokasi_full']}</strong> has the lowest activity level "
+        f"(<strong>{low_location['avg_monthly_ratio']:.2f}</strong>).<br><br>"
+        f"🟢 <strong>High-ratio (green)</strong> locations indicate either high reporting diligence or high exposure to risks — both warrant deeper root-cause analysis.<br>"
+        f"🔴 <strong>Low-ratio (red)</strong> locations may reflect under-reporting, lack of engagement, or low hazard visibility — recommend follow-up audits to verify data completeness.<br>"
+        f"🟡 Medium-ratio (yellow) areas need monitoring to ensure trends do not deteriorate."
+        f"</div>"
+    )
+    st.markdown(insight_text, unsafe_allow_html=True)
 # =================== OBJECTIVE 3 - Frequency & Response Time ===================
 st.markdown(
     """