fix comments etc.

dashboard.py

@@ -104,7 +104,7 @@ try:
             else:
                 st.sidebar.warning("No drugs found")
     
-    # OVERVIEW PAGE
+    # overview page
     if page == "Overview":
         st.header("Dataset Overview")
         
@@ -114,7 +114,7 @@ try:
         col3.metric("Repurposing Opportunities", f"{len(repurposing):,}")
         col4.metric("Analyzed Drugs", f"{len(super_drugs):,}")
         
-        # STATISTICS BOXES
+        # statistics boxes
         st.markdown("---")
         st.subheader("Key Statistics")
         
@@ -163,7 +163,7 @@ try:
                 xaxis_title="Gene",
                 yaxis_title="Number of Diseases"
             )
-            # Enable chart export
+            # enable chart export
             config = {'displayModeBar': True, 'displaylogo': False}
             st.plotly_chart(fig, use_container_width=True, config=config)
             
@@ -185,7 +185,7 @@ try:
             csv = top_diseases.to_csv(index=False).encode('utf-8')
             st.download_button("Download Data", csv, "top_diseases.csv", "text/csv")
     
-    # HOTSPOT GENES PAGE
+    # hotspot gene page
     elif page == "Hotspot Genes":
         st.header("Hotspot Genes - Most Disease Associations")
         
@@ -215,7 +215,7 @@ try:
         csv = filtered_genes.to_csv(index=False).encode('utf-8')
         st.download_button("Download Filtered Data", csv, "hotspot_genes.csv", "text/csv")
     
-    # DRUG REPURPOSING PAGE
+    # drug repurposing page
     elif page == "Drug Repurposing":
         st.header("Drug Repurposing Opportunities")
         
@@ -250,7 +250,7 @@ try:
             csv = filtered.to_csv(index=False).encode('utf-8')
             st.download_button("Download", csv, f"repurposing_{selected}.csv", "text/csv")
     
-    # POLYPHARMACY RISK PAGE
+    # polypharmacy risk page
     elif page == "Polypharmacy Risk":
         st.header("Polypharmacy Risk Analysis")
         
@@ -285,7 +285,7 @@ try:
         csv = filtered_risk.to_csv(index=False).encode('utf-8')
         st.download_button("Download Risk Data", csv, "polypharmacy_risk.csv", "text/csv")
     
-    # SYMPTOM TRIANGLE PAGE
+    # symptop triangle page
     elif page == "Symptom Triangle":
         st.header("Symptom-Disease-Drug Connections")
         
@@ -314,7 +314,7 @@ try:
         csv = top_symptoms.to_csv(index=False).encode('utf-8')
         st.download_button("Download Symptom Data", csv, "symptom_triangle.csv", "text/csv")
     
-    # SUPER DRUGS PAGE
+    # super drugs page
     elif page == "Super Drugs":
         st.header("Super-Drug Score (Best Benefit/Risk Ratio)")
         
@@ -352,7 +352,7 @@ try:
         csv = filtered_super.to_csv(index=False).encode('utf-8')
         st.download_button("Download Super Drugs", csv, "super_drugs.csv", "text/csv")
     
-    # DRUG CONFLICTS PAGE
+    # drug conflicts page
     elif page == "Drug Conflicts":
         st.header("Drug Conflicts - Overlapping Side Effects")
         
@@ -394,28 +394,28 @@ try:
         else:
             st.warning("Drug conflicts data not available. Run the ETL script to generate this analysis.")
     
-    # NETWORK GRAPH PAGE
+    # network graph page
     elif page == "Network Graph":
         st.header("Disease-Gene-Drug Network")
         
         if network_nodes is not None and network_edges is not None:
             st.info("Interactive network visualization showing connections between diseases, genes, and drugs")
             
-            # Create networkx graph
+            # create networkx graph
             G = nx.Graph()
             
-            # Add nodes
+            # add nodes
             for _, row in network_nodes.iterrows():
                 G.add_node(row['id'], label=row['label'], type=row['type'])
             
-            # Add edges
+            # add edges
             for _, row in network_edges.iterrows():
                 G.add_edge(row['source'], row['target'])
             
-            # Create layout
+            # create layout
             pos = nx.spring_layout(G, k=0.5, iterations=50)
-            
-            # Create edge trace
+        
+            # create edge trace
             edge_x = []
             edge_y = []
             for edge in G.edges():
@@ -431,7 +431,7 @@ try:
                 mode='lines'
             )
             
-            # Create node traces (separate by type for legend)
+            # create node traces (separate by type for legend)
             node_traces = []
             color_map = {
                 'Disease': '#ff4444',
@@ -466,7 +466,7 @@ try:
                     )
                     node_traces.append(node_trace)
             
-            # Create figure
+            # create figure
             fig = go.Figure(data=[edge_trace] + node_traces,
                           layout=go.Layout(
                               title='Disease-Gene-Drug Network',
@@ -488,7 +488,7 @@ try:
         else:
             st.warning("Network data not available. Run the ETL script to generate this visualization.")
     
-    # COMPARE DRUGS PAGE
+    # compare drugs page
     elif page == "Compare Drugs":
         st.header("⚖️ Compare Drugs Side-by-Side")
         
@@ -522,7 +522,7 @@ try:
                 st.metric("Side Effects", int(drug2_data['num_side_effects']))
                 st.metric("Super Score", f"{drug2_data['super_score']:.2f}")
             
-            # Comparison chart
+            # comparison chart
             comparison_df = pd.DataFrame({
                 'Metric': ['Diseases Treated', 'Side Effects', 'Super Score'],
                 drug1: [drug1_data['num_diseases_treated'], drug1_data['num_side_effects'], drug1_data['super_score']],
@@ -539,7 +539,7 @@ try:
             config = {'displayModeBar': True, 'displaylogo': False}
             st.plotly_chart(fig, use_container_width=True, config=config)
             
-            # Winner determination
+            # winner determination
             st.markdown("---")
             st.subheader("Recommendation")