Update app.py

app.py

@@ -893,36 +893,57 @@ with col_3b:
     if avg_leadtime_nama.empty:
         st.warning("No data for division-level executor analysis.")
     else:
-        sort_opt = st.selectbox("Show:", ["Top 10", "Bottom 10"], key='sort_3b')
-        
-        full_sorted = avg_leadtime_nama.sort_values('avg_monthly_leadtime', ascending=True)  # cepat → lambat
-        if sort_opt == "Fastest 10":
-            subset = full_sorted.head(10).sort_values('avg_monthly_leadtime', ascending=True)  # descending dalam subset (cepat di bawah)
-        else:
-            subset = full_sorted.tail(10).sort_values('avg_monthly_leadtime', ascending=False)  # lambat di atas
+        sort_opt = st.selectbox(
+            "Show:", 
+            ["Top 10 Fastest", "Bottom 10 Slowest"], 
+            key='sort_3b'
+        )
+
+        # Sort penuh sekali — ascending: tercepat → terlambat
+        full_sorted = avg_leadtime_nama.sort_values('avg_monthly_leadtime', ascending=True)
         
-        # Warna: 5 terlama → merah
-        colored = add_color_by_global_rank(avg_leadtime_nama, 'avg_monthly_leadtime', worst_n=5, high_is_good=False)
+        # Ambil subset sesuai pilihan
+        if sort_opt == "Top 10 Fastest":
+            # 10 tercepat: ascending (kecil → besar), tetap diurut ascending → tercepat di atas
+            subset = full_sorted.head(10).copy()
+        else:  # "Bottom 10 Slowest"
+            # 10 terlambat: descending (besar → kecil), agar terlambat di atas
+            subset = full_sorted.tail(10).sort_values('avg_monthly_leadtime', ascending=False)
+
+        # Warna: 5 terlambat secara global (bukan di subset!) → warna merah
+        colored = add_color_by_global_rank(
+            avg_leadtime_nama, 
+            'avg_monthly_leadtime', 
+            worst_n=5, 
+            high_is_good=False  # lebih tinggi = buruk
+        )
         subset = subset.merge(colored[['nama', 'color']], on='nama', how='left').fillna({'color': '#1f77b4'})
-        
-        # Reverse agar Slowest 10: tertinggi di atas
-        if sort_opt == "Slowest 10":
-            subset = subset.iloc[::-1]
-        
+
         fig = px.bar(
-            subset, x='avg_monthly_leadtime', y='nama', orientation='h',
-            title=f'{sort_opt}',
+            subset, 
+            x='avg_monthly_leadtime', 
+            y='nama', 
+            orientation='h',
+            title=sort_opt,
             labels={'avg_monthly_leadtime': 'Avg Lead Time (Days)', 'nama': 'Division'},
-            color='color', color_discrete_map={c: c for c in subset['color'].unique()},
+            color='color', 
+            color_discrete_map={c: c for c in subset['color'].unique()},
             text=subset['avg_monthly_leadtime'].apply(lambda x: f'{x:.1f}')
         )
-        fig.update_layout(height=450, showlegend=False, yaxis={'categoryorder': 'array', 'categoryarray': subset['nama'].tolist()})
+        fig.update_layout(
+            height=450, 
+            showlegend=False, 
+            yaxis={'categoryorder': 'array', 'categoryarray': subset['nama'].tolist()}
+        )
         fig.update_traces(textposition='auto')
         st.plotly_chart(fig, use_container_width=True)
-        
+
         if len(full_sorted) >= 2:
-            min_lt, max_lt, mean_lt = full_sorted['avg_monthly_leadtime'].min(), full_sorted['avg_monthly_leadtime'].max(), full_sorted['avg_monthly_leadtime'].mean()
-            fastest, slowest = full_sorted.iloc[0]['nama'], full_sorted.iloc[-1]['nama']
+            min_lt = full_sorted['avg_monthly_leadtime'].min()
+            max_lt = full_sorted['avg_monthly_leadtime'].max()
+            mean_lt = full_sorted['avg_monthly_leadtime'].mean()
+            fastest = full_sorted.iloc[0]['nama']
+            slowest = full_sorted.iloc[-1]['nama']
             st.markdown(
                 f"<div class='ai-insight'>"
                 f"<strong>Insight:</strong> Resolution time ranges from {min_lt:.1f} to {max_lt:.1f} days (avg: {mean_lt:.1f}). "
@@ -935,51 +956,69 @@ with col_3b:
 
 # ─── 3d: Executor by Individual ──────────────────────────────────────────────
 with col_3d:
-    st.markdown(f"<h5 style='text-align:center;'>3d. Avg Lead Time per Executor ({EXECUTOR_INDIV_COL})</h5>", unsafe_allow_html=True)
+    st.markdown(
+        f"<h5 style='text-align:center;'>3d. Avg Lead Time per Executor ({EXECUTOR_INDIV_COL})</h5>", 
+        unsafe_allow_html=True
+    )
     if avg_leadtime_per_indiv.empty:
         st.warning(f"No data for individual executor analysis (column: '{EXECUTOR_INDIV_COL}').")
     else:
-        sort_opt = st.selectbox("Show:", ["Top 10", "Bottom 10"], key='sort_3d')
-        
+        sort_opt = st.selectbox(
+            "Show:", 
+            ["Top 10 Fastest", "Bottom 10 Slowest"], 
+            key='sort_3d'
+        )
+
         full_sorted = avg_leadtime_per_indiv.sort_values('avg_monthly_leadtime', ascending=True)
-        if sort_opt == "Fastest 10":
-            subset = full_sorted.head(10).sort_values('avg_monthly_leadtime', ascending=True)
-        else:
-            subset = full_sorted.tail(10).sort_values('avg_monthly_leadtime', ascending=False)
 
+        if sort_opt == "Top 10 Fastest":
+            subset = full_sorted.head(10).copy()
+        else:  # "Bottom 10 Slowest"
+            subset = full_sorted.tail(10).sort_values('avg_monthly_leadtime', ascending=False)
 
-            
-        # Warna: 5 terlama → merah
-        colored = add_color_by_global_rank(avg_leadtime_per_indiv, 'avg_monthly_leadtime', worst_n=5, high_is_good=False)
+        # Warna berdasarkan ranking global
+        colored = add_color_by_global_rank(
+            avg_leadtime_per_indiv, 
+            'avg_monthly_leadtime', 
+            worst_n=5, 
+            high_is_good=False
+        )
         id_col = EXECUTOR_INDIV_COL
         subset = subset.merge(colored[[id_col, 'color']], on=id_col, how='left').fillna({'color': '#1f77b4'})
-        
-        if sort_opt == "Slowest 10":
-            subset = subset.iloc[::-1]
-        
+
         fig = px.bar(
-            subset, x='avg_monthly_leadtime', y=id_col, orientation='h',
-            title=f'{sort_opt}',
+            subset, 
+            x='avg_monthly_leadtime', 
+            y=id_col, 
+            orientation='h',
+            title=sort_opt,
             labels={'avg_monthly_leadtime': 'Avg Lead Time (Days)', id_col: 'Executor'},
-            color='color', color_discrete_map={c: c for c in subset['color'].unique()},
+            color='color', 
+            color_discrete_map={c: c for c in subset['color'].unique()},
             text=subset['avg_monthly_leadtime'].apply(lambda x: f'{x:.1f}')
         )
-        fig.update_layout(height=450, showlegend=False, yaxis={'categoryorder': 'array', 'categoryarray': subset[id_col].tolist()})
+        fig.update_layout(
+            height=450, 
+            showlegend=False, 
+            yaxis={'categoryorder': 'array', 'categoryarray': subset[id_col].tolist()}
+        )
         fig.update_traces(textposition='auto')
         st.plotly_chart(fig, use_container_width=True)
-        
+
         if len(full_sorted) >= 2:
-            min_lt, max_lt, mean_lt = full_sorted['avg_monthly_leadtime'].min(), full_sorted['avg_monthly_leadtime'].max(), full_sorted['avg_monthly_leadtime'].mean()
+            min_lt = full_sorted['avg_monthly_leadtime'].min()
+            max_lt = full_sorted['avg_monthly_leadtime'].max()
+            mean_lt = full_sorted['avg_monthly_leadtime'].mean()
             slowest_exec = full_sorted.iloc[-1][id_col]
+            fastest_exec = full_sorted.iloc[0][id_col]
             st.markdown(
                 f"<div class='ai-insight'>"
                 f"<strong>Insight:</strong> Executor performance ranges from {min_lt:.1f} to {max_lt:.1f} days (avg: {mean_lt:.1f}). "
                 f"<strong>{slowest_exec}</strong> requires support to meet SLA. "
-                f"<strong>Recommendation:</strong> Assign mentor to executors >7 days; document & share best practices from top performers."
+                f"<strong>Recommendation:</strong> Assign mentor to executors >7 days; document & share best practices from top performers (e.g., {fastest_exec})."
                 f"</div>",
                 unsafe_allow_html=True
             )
-
 #Objective 4
 try:
     from wordcloud import WordCloud