Update app.py

app.py

@@ -1268,6 +1268,11 @@ import plotly.graph_objects as go
 import numpy as np
 import pandas as pd
 
+import streamlit as st
+import plotly.graph_objects as go
+import numpy as np
+import pandas as pd
+
 # =================== OBJECTIVE 6 - Predictive Dashboard & Early Warning Signals ===================
 st.markdown("<h3 class='section-title'>OBJECTIVE 6 — Predictive Dashboard & Early Warning Signals</h3>", unsafe_allow_html=True)
 
@@ -1476,7 +1481,8 @@ def predict_creators(df):
             except:
                 continue
     df_res = pd.DataFrame(results)
-    return df_res.sort_values('Trend Slope', ascending=True) if not df_res.empty else df_res  # most negative first
+    # ✅ Ambil 10 creator dengan slope paling negatif (paling turun)
+    return df_res.sort_values('Trend Slope', ascending=True).head(10) if not df_res.empty else df_res
 
 # ——————— 3. Issues: ONLY Coverage=100% & Trend Slope > 0 → Avg/Month ———————
 def predict_issues(df):
@@ -1541,7 +1547,7 @@ df_issue = predict_issues(df_filtered)
 
 # 🎯 PANEL 1: Creators (FILTERED: Coverage < 90% & Slope < 0) — Non-Positive Only
 st.markdown("<div class='predictive-panel'>", unsafe_allow_html=True)
-st.markdown("<div class='predictive-header'>1. Which Reporters Are Predicted to Have No Future Inspections? (Non-Positive Only)</div>", unsafe_allow_html=True)
+st.markdown("<div class='predictive-header'>1. Which Reporters Are Predicted to Have No Future Inspections? (Top 10 Most Declining)</div>", unsafe_allow_html=True)
 if not df_creator.empty:
     cols = ['Creator', 'Avg Reports/Month', 'Coverage (%)', 'Trend Slope', 'Trend', 'Reason']
 
@@ -1575,10 +1581,55 @@ if not df_creator.empty:
     # )
 st.markdown("</div>", unsafe_allow_html=True)
 
+# 🎯 PANEL 3: Issues (FILTERED: Coverage=100% & Rising) — Hanya Non-Positive
+st.markdown("<div class='predictive-panel'>", unsafe_allow_html=True)
+st.markdown(
+    "<div class='predictive-header'>"
+    "3. Which Issue Categories Are Likely to Appear in the Next 3 Months (Non-Positive Only)"
+    "<span style='font-size:0.75em; font-weight:400; color:#003DA5;'>"
+    " &nbsp;&nbsp;(* Categorization uses NLP — Natural Language Processing from random text)"
+    "</span>"
+    "</div>",
+    unsafe_allow_html=True
+)
+
+if not df_issue.empty:
+    cols = ['Category', 'Avg/Month', 'Coverage (%)', 'Trend Slope', 'Status', 'Trend']
+
+    # 🔵 Rename ONLY for display
+    df_display = df_issue[cols].rename(columns={
+        "Status": "Status Issue for Next Month"
+    })
+
+    html = df_display.to_html(escape=False, index=False, table_id="tbl-issues")
+    st.markdown(f"<div class='predictive-table-wrapper'>{html}</div>", unsafe_allow_html=True)
+
+#     st.markdown(
+#         "<div class='predictive-note'>"
+#         "<strong>Filtered:</strong> Reported every month (100% coverage) with increasing trend. "
+#         "<strong>Avg/Month</strong> = total ÷ months. "
+#         "<span class='trend-rising'>High-Risk Rising</span> = slope > 0.2."
+#         "</div>",
+#         unsafe_allow_html=True
+#     )
+
+# else:
+#     st.markdown(
+#         "<div class='predictive-table-wrapper'>"
+#         "<p style='text-align:center; color:#c62828; padding:24px; font-weight:500;'>"
+#         "⚠️ No rising categories with 100% monthly coverage."
+#         "</p>"
+#         "<p style='text-align:center; color:#666; font-size:0.9em;'>"
+#         "Consider relaxing coverage filter if data is sparse."
+#         "</p></div>",
+#         unsafe_allow_html=True
+#     )
+
+st.markdown("</div>", unsafe_allow_html=True)
 
 
 # =================== WHITEBOARD STYLE CHART FOR PANEL 3 ===================
-st.markdown("<h4 style='text-align: center; color: #2c3e50;'>2. Which Issue Categories Are Likely to Appear in the Next 3 Months</h4>", unsafe_allow_html=True)
+st.markdown("<h4 style='text-align: center; color: #2c3e50;'>Whiteboard Insight: Trend vs Frequency</h4>", unsafe_allow_html=True)
 
 # Buat chart scatter dengan gaya whiteboard
 if not df_issue.empty:
@@ -1682,7 +1733,6 @@ if not df_issue.empty:
     st.markdown(insight_text, unsafe_allow_html=True)
 else:
     st.info("No data available for non-positive issues with 100% coverage and positive trend.")
-
 # =================== 6. ✅ AI INSIGHT ENGINE (BARU - BERDASARKAN DATA & RATIO) ===================
 
 st.markdown("<h3 class='section-title'>OBJECTIVE 7 - Insight and Recommendation</h3>", unsafe_allow_html=True)