Update app.py

app.py

@@ -278,7 +278,7 @@ def analyze_competitors(row, co, country_code):
     
     # Create DataFrame
     results_df = pd.DataFrame(results)
-    results_df['Position'] = results_df['Position'].astype(int)
+    results_df['Position'] = results_df['Position'].astype(int)  # Ensure Position is integer
     
     # Mark our URL
     results_df['URL'] = results_df.apply(
@@ -663,7 +663,7 @@ def show_tabular_data(df, co, country_code):
         cols[3].write(row.clicks)
         cols[4].write(row.impressions)
         cols[5].write(f"{row.ctr:.2%}")
-        cols[6].write(f"{row.position:.1f}")
+        cols[6].write(f"{int(row.position)}")  # Round Position to integer
         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
@@ -689,7 +689,7 @@ def show_tabular_data(df, 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
+                    results_df.loc[our_url_mask, 'Position'] = row.position  # Already integer
                     
                     # Ensure our URL's score matches the main table
                     results_df.loc[our_url_mask, 'Score'] = row.relevancy_score
@@ -703,7 +703,7 @@ def show_tabular_data(df, co, country_code):
                     # 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
+                    # Display the styled DataFrame with Position as integer
                     st.markdown(styled_df.to_html(), unsafe_allow_html=True)
                     
                     # Extract our result for additional insights