Update app.py

app.py

@@ -254,7 +254,17 @@ def analyze_competitors(row, co, custom_url=None, country_code=None):
     our_position = next((r['position'] for r in results if r['url'] == our_url), len(results) + 1)
     results.append({'position': our_position, 'url': our_url, 'relevancy_score': our_score})
     
-    results_df = pd.DataFrame(results).sort_values('position')
+    # Sort results by the original position
+    results = sorted(results, key=lambda x: x['position'])
+    
+    # Re-number positions starting from 1 and format URLs
+    for idx, item in enumerate(results, start=1):
+        item['position'] = idx
+        if item['url'] == our_url:
+            item['url'] = f"**{item['url']}**"  # Mark our URL in bold
+    
+    # Keep only 'position', 'url', and 'relevancy_score' columns
+    results_df = pd.DataFrame(results)[['position', 'url', 'relevancy_score']]
     
     return results_df
 
@@ -264,32 +274,36 @@ def show_competitor_analysis(row, co, country_code):
         with st.spinner('Analyzing competitors...'):
             results_df = analyze_competitors(row, co, country_code=country_code)
             
-            # Remove duplicates, keeping the first occurrence
-            results_df = results_df.drop_duplicates(subset='url', keep='first')
-            
-            # Format our result in bold
-            results_df['URL'] = results_df.apply(
-                lambda x: f"**{x['url']}**" if x['url'] == row['page'] else x['url'], axis=1
-            )
+            # Rename columns to have a proper header
+            results_df.columns = ['Position', 'URL', 'Score']
             
-            # Display the results
-            st.write("Relevancy Score Comparison:")
-            st.markdown(results_df[['position', 'URL', 'relevancy_score']].to_markdown(index=False), unsafe_allow_html=True)
+            # Convert 'Position' to integer for proper sorting and display
+            results_df['Position'] = results_df['Position'].astype(int)
             
-            our_result = results_df[results_df['url'] == row['page']]
-            our_rank = our_result['position'].values[0]
-            total_results = len(results_df)
-            our_score = our_result['relevancy_score'].values[0]
+            # Convert the DataFrame to Markdown with bold URLs where applicable
+            markdown_table = results_df.to_markdown(index=False)
             
-            st.write(f"Our page ranks {our_rank} out of {total_results} in Google search results.")
-            st.write(f"Our relevancy score: {our_score:.4f}")
+            # Display the Markdown table
+            st.markdown(markdown_table, unsafe_allow_html=True)
             
-            if our_rank == 1:
-                st.success("Your page has the highest position in Google search results!")
-            elif our_rank <= 3:
-                st.info("Your page is among the top 3 Google search results.")
-            elif our_rank > total_results / 2:
-                st.warning("Your page's position is in the lower half of the Google search results. Consider optimizing your content for better visibility.")
+            # Extract our result for additional insights
+            our_result = results_df[results_df['URL'].str.contains("**" + row['page'] + "**")]
+            if not our_result.empty:
+                our_rank = our_result['Position'].values[0]
+                total_results = len(results_df)
+                our_score = our_result['Score'].values[0]
+                
+                st.write(f"Our page ranks **{our_rank}** out of **{total_results}** in Google search results.")
+                st.write(f"Our relevancy score: **{our_score:.4f}**")
+                
+                if our_rank == 1:
+                    st.success("Your page has the highest position in Google search results!")
+                elif our_rank <= 3:
+                    st.info("Your page is among the top 3 Google search results.")
+                elif our_rank > total_results / 2:
+                    st.warning("Your page's position is in the lower half of the Google search results. Consider optimizing your content for better visibility.")
+            else:
+                st.error("Our page was not found in the competitor analysis results.")
 
 def process_gsc_data(df):
     #logging.info("Processing GSC data")