Update app.py

app.py

@@ -5,9 +5,7 @@ import plotly.graph_objects as go
 import numpy as np
 from datetime import datetime
 
-# ==========================================
 # 1. PAGE CONFIGURATION
-# ==========================================
 st.set_page_config(
     page_title="Sentinel | UIDAI Fraud Detection",
     page_icon="🛡️",
@@ -15,9 +13,7 @@ st.set_page_config(
     initial_sidebar_state="expanded"
 )
 
-# ==========================================
 # 2. PROFESSIONAL STYLING (THEME OVERRIDE)
-# ==========================================
 st.markdown("""
     <style>
         /* IMPORT FONTS */
@@ -101,9 +97,7 @@ st.markdown("""
     </style>
 """, unsafe_allow_html=True)
 
-# ==========================================
-# 3. SMART DATA LOADING (FIXED MAPPING)
-# ==========================================
+# 3. SMART DATA LOADING (MAPPING)
 @st.cache_data
 def load_data():
     # 1. Load or Generate Data
@@ -114,7 +108,7 @@ def load_data():
         dates = pd.date_range(start="2025-01-01", periods=200)
         df = pd.DataFrame({
             'date': dates,
-            'state': np.random.choice(['Maharashtra', 'Uttar Pradesh', 'Bihar', 'Karnataka', 'Delhi', 'West Bengal', 'Tamil Nadu'], 200),
+            'state': np.random.choice(['Maharashtra', 'Uttar Pradesh', 'Bihar', 'Karnataka', 'Delhi', 'West Bengal', 'Tamil Nadu', 'Gujarat', 'Rajasthan', 'Kerala'], 200),
             'district': np.random.choice(['North', 'South', 'East', 'West', 'Central', 'Rural A', 'Urban B'], 200),
             'pincode': np.random.randint(110001, 800000, 200),
             'RISK_SCORE': np.random.uniform(15, 99, 200),
@@ -128,23 +122,45 @@ def load_data():
     if 'date' in df.columns:
         df['date'] = pd.to_datetime(df['date'])
     
-    # ---------------------------------------------------------
-    # SMART GEO-CLUSTERING LOGIC (THE FIX)
-    # ---------------------------------------------------------
-    # Define approximate center points for major states
+    # SMART GEO-CLUSTERING LOGIC
+    # Comprehensive Center Points for Indian States & UTs
     state_centers = {
-        'Maharashtra': (19.7515, 75.7139),
-        'Uttar Pradesh': (26.8467, 80.9462),
+        'Andaman and Nicobar Islands': (11.7401, 92.6586),
+        'Andhra Pradesh': (15.9129, 79.7400),
+        'Arunachal Pradesh': (28.2180, 94.7278),
+        'Assam': (26.2006, 92.9376),
         'Bihar': (25.0961, 85.3131),
-        'Karnataka': (15.3173, 75.7139),
+        'Chandigarh': (30.7333, 76.7794),
+        'Chhattisgarh': (21.2787, 81.8661),
+        'Dadra and Nagar Haveli and Daman and Diu': (20.4283, 72.8397),
         'Delhi': (28.7041, 77.1025),
-        'West Bengal': (22.9868, 87.8550),
-        'Tamil Nadu': (11.1271, 78.6569),
-        'Kerala': (10.8505, 76.2711),
+        'Goa': (15.2993, 74.1240),
         'Gujarat': (22.2587, 71.1924),
+        'Haryana': (29.0588, 76.0856),
+        'Himachal Pradesh': (31.1048, 77.1734),
+        'Jammu and Kashmir': (33.7782, 76.5762),
+        'Jharkhand': (23.6102, 85.2799),
+        'Karnataka': (15.3173, 75.7139),
+        'Kerala': (10.8505, 76.2711),
+        'Ladakh': (34.1526, 77.5770),
+        'Lakshadweep': (10.5667, 72.6417),
+        'Madhya Pradesh': (22.9734, 78.6569),
+        'Maharashtra': (19.7515, 75.7139),
+        'Manipur': (24.6637, 93.9063),
+        'Meghalaya': (25.4670, 91.3662),
+        'Mizoram': (23.1645, 92.9376),
+        'Nagaland': (26.1584, 94.5624),
+        'Odisha': (20.9517, 85.0985),
+        'Puducherry': (11.9416, 79.8083),
+        'Punjab': (31.1471, 75.3412),
         'Rajasthan': (27.0238, 74.2179),
-        'Assam': (26.2006, 92.9376),
-        'Meghalaya': (25.4670, 91.3662)
+        'Sikkim': (27.5330, 88.5122),
+        'Tamil Nadu': (11.1271, 78.6569),
+        'Telangana': (18.1124, 79.0193),
+        'Tripura': (23.9408, 91.9882),
+        'Uttar Pradesh': (26.8467, 80.9462),
+        'Uttarakhand': (30.0668, 79.0193),
+        'West Bengal': (22.9868, 87.8550)
     }
 
     def get_coords(row):
@@ -193,9 +209,7 @@ def load_data():
 # Load Data
 df = load_data()
 
-# ==========================================
 # 4. SIDEBAR & FILTERS
-# ==========================================
 with st.sidebar:
     st.markdown("### 🛡️ Sentinel Control")
     st.markdown("---")
@@ -229,12 +243,16 @@ with st.sidebar:
     if risk_filter:
         filtered_df = filtered_df[filtered_df['risk_category'].isin(risk_filter)]
     
+    st.markdown("---")
+    
+    # Links
+    st.markdown("**Resources**")
+    st.link_button("📊 Open Notebook in Colab", "https://colab.research.google.com/drive/1YAQ4nfxltvG_cts3fmGc_zi2JQc4oPOT?usp=sharing")
+
     st.markdown("---")
     st.info(f"**User:** UIDAI_Officer\n\n**Team:** UIDAI_4571")
 
-# ==========================================
 # 5. HEADER & KPI METRICS
-# ==========================================
 col1, col2 = st.columns([3, 1])
 with col1:
     st.title("Project Sentinel Dashboard")
@@ -264,12 +282,10 @@ m4.metric("Weekend Spikes", f"{weekend_alerts}", "Unauthorized", delta_color="of
 
 st.markdown("##") # Spacer
 
-# ==========================================
 # 6. MAIN TABS
-# ==========================================
 tab_map, tab_list, tab_charts = st.tabs(["🗺️ Geographic Risk", "📋 Priority List", "📊 Pattern Analytics"])
 
-# --- TAB 1: GEOGRAPHIC RISK (FIXED MAP) ---
+# TAB 1: GEOGRAPHIC RISK (MAP)
 with tab_map:
     col_map, col_details = st.columns([3, 1])
     
@@ -312,7 +328,7 @@ with tab_map:
                 </div>
                 """, unsafe_allow_html=True)
 
-# --- TAB 2: PRIORITY LIST (DATAFRAME) ---
+# TAB 2: PRIORITY LIST (DATAFRAME)
 with tab_list:
     st.subheader("Target Investigation List")
     st.markdown("Filter: *Showing centers with Risk Score > 75*")
@@ -381,9 +397,7 @@ with tab_charts:
         fig_hist.update_layout(bargap=0.1)
         st.plotly_chart(fig_hist, use_container_width=True)
 
-# ==========================================
 # 7. FOOTER
-# ==========================================
 st.markdown("---")
 st.markdown("""
 <div style="text-align: center; font-size: 13px; color: #94a3b8;">