Update app.py

app.py

@@ -636,19 +636,15 @@ def show_tabular_data(df, co, country_code):
         st.success(f"Calculated relevancy scores for {len(selected_indices)} selected rows.")
         st.experimental_rerun()
     
-    # Display column headers without the "Compare" column
-    cols = st.columns([0.5, 3, 2, 1, 1, 1, 1, 1])  # Removed the extra column for "Compare"
-    headers = ['Select', 'Page', 'Query', 'Clicks', 'Impressions', 'CTR', 'Position', 'Relevancy Score']
+    # Display column headers
+    cols = st.columns([0.5, 3, 2, 1, 1, 1, 1, 1, 1])
+    headers = ['Select', 'Page', 'Query', 'Clicks', 'Impressions', 'CTR', 'Position', 'Relevancy Score', 'Competitors']
     for col, header in zip(cols, headers):
         col.write(f"**{header}**")
 
-    # Variable to track which row's competitors are being shown
-    if 'competitor_display' not in st.session_state:
-        st.session_state.competitor_display = {}
-
     # Display each row
     for i, row in enumerate(df.iloc[start_idx:end_idx].itertuples(), start=start_idx):
-        cols = st.columns([0.5, 3, 2, 1, 1, 1, 1, 1])  # Removed the extra column for "Compare"
+        cols = st.columns([0.5, 3, 2, 1, 1, 1, 1, 1, 1])
         
         # Checkbox for row selection
         cols[0].checkbox("", key=f"select_{i}", value=st.session_state.selected_rows[i],
@@ -666,68 +662,69 @@ def show_tabular_data(df, co, country_code):
         cols[6].write(f"{row.position:.1f}")
         cols[7].write(f"{row.relevancy_score:.4f}" if not pd.isna(row.relevancy_score) and row.relevancy_score != 0 else "N/A")
         
-        # Competitors column with "Show" button
-        show_competitor = cols[7].button("Show", key=f"comp_{i}", disabled=pd.isna(row.relevancy_score) or row.relevancy_score == 0)
-        if show_competitor:
-            st.session_state.competitor_display[i] = True
-        if st.session_state.competitor_display.get(i, False):
-            st.write(f"Competitor Analysis for: {row.query}")
-            with st.spinner('Analyzing competitors...'):
-                results_df = analyze_competitors(row._asdict(), co, country_code=country_code)
-                
-                # Sort the results by Position in ascending order
-                results_df = results_df.sort_values('Position', ascending=True).reset_index(drop=True)
-                
-                # Update the Position for our URL
-                our_url_mask = results_df['URL'].str.contains('Our URL')
-                results_df.loc[our_url_mask, 'Position'] = row.position
-                
-                # Create a custom style function to highlight only our URL's row
-                def highlight_our_url(row_style):
-                    if 'Our URL' in row_style['URL']:
-                        return ['background-color: lightgreen'] * len(row_style)
-                    return [''] * len(row_style)
-                
-                # Apply the custom style and hide the index
-                styled_df = results_df.style.apply(highlight_our_url, axis=1).hide(axis="index")
-                
-                # Display the styled DataFrame
-                st.markdown(styled_df.to_html(), unsafe_allow_html=True)
-                
-                # Extract our result for additional insights
-                our_result = results_df[results_df['URL'].str.contains('Our URL')]
-                
-                if not our_result.empty:
-                    our_rank = our_result['Position'].values[0]
-                    total_results = len(results_df)
-                    our_score = our_result['Score'].values[0]
+        # Competitors column
+        if not pd.isna(row.relevancy_score) and row.relevancy_score != 0:
+            competitor_button = cols[8].button("Show", key=f"comp_{i}")
+            if competitor_button:
+                st.write(f"Competitor Analysis for: {row.query}")
+                with st.spinner('Analyzing competitors...'):
+                    results_df = analyze_competitors(row._asdict(), co, country_code=country_code)
                     
-                    st.write(f"Our page ranks {our_rank} out of {total_results} in terms of relevancy score.")
-                    st.write(f"Our relevancy score: {our_score:.4f}")
+                    # Sort the results by Position in ascending order
+                    results_df = results_df.sort_values('Position', ascending=True).reset_index(drop=True)
                     
-                    if our_rank == 1:
-                        st.success("Your page has the highest relevancy score!")
-                    elif our_rank <= 3:
-                        st.info("Your page is among the top 3 most relevant results.")
-                    elif our_rank > total_results / 2:
-                        st.warning("Your page's relevancy score is in the lower half of the results. Consider optimizing your content.")
-                else:
-                    st.error(f"Our page '{row.page}' is not in the results. This indicates an error in fetching or processing the page.")
-
-            # "Compare" button placed below the competitors table
-            st.markdown(
-                """
-                <style>
-                .stButton > button {
-                    background-color: #008CBA;
-                    color: white;
-                }
-                </style>
-                """,
-                unsafe_allow_html=True
-            )
-            if st.button("Compare Your Relevancy Score to the Page In First Place", key=f"compare_{i}"):
-                compare_with_top_result(row._asdict(), co, country_code)
+                    # Update the Position for our URL
+                    our_url_mask = results_df['URL'].str.contains('Our URL')
+                    results_df.loc[our_url_mask, 'Position'] = row.position
+                    
+                    # Create a custom style function to highlight only our URL's row
+                    def highlight_our_url(row):
+                        if 'Our URL' in row['URL']:
+                            return ['background-color: lightgreen'] * len(row)
+                        return [''] * len(row)
+                    
+                    # Apply the custom style and hide the index
+                    styled_df = results_df.style.apply(highlight_our_url, axis=1).hide(axis="index")
+                    
+                    # Display the styled DataFrame
+                    st.markdown(styled_df.to_html(), unsafe_allow_html=True)
+                    
+                    # Extract our result for additional insights
+                    our_result = results_df[results_df['URL'].str.contains('Our URL')]
+                    
+                    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 terms of relevancy score.")
+                        st.write(f"Our relevancy score: {our_score:.4f}")
+                        
+                        if our_rank == 1:
+                            st.success("Your page has the highest relevancy score!")
+                        elif our_rank <= 3:
+                            st.info("Your page is among the top 3 most relevant results.")
+                        elif our_rank > total_results / 2:
+                            st.warning("Your page's relevancy score is in the lower half of the results. Consider optimizing your content.")
+                    else:
+                        st.error(f"Our page '{row.page}' is not in the results. This indicates an error in fetching or processing the page.")
+
+                    # Add "Compare" button at the bottom of the competitors table
+                    st.markdown(
+                        """
+                        <style>
+                        .stButton > button {
+                            background-color: #008CBA;
+                            color: white;
+                        }
+                        </style>
+                        """,
+                        unsafe_allow_html=True
+                    )
+                    if st.button("Compare Your Relevancy Score to the Page In First Place", key=f"compare_{i}"):
+                        compare_with_top_result(row._asdict(), co, country_code)
+        else:
+            cols[8].write("N/A")
 
     return df  # Return the updated dataframe