Update app.py

app.py

@@ -107,6 +107,7 @@ def process_gsc_data(df):
     result['relevancy_score'] = None  # Initialize relevancy_score as None
     return result
 
+
 # -------------
 # Google Authentication Functions
 # -------------
@@ -298,7 +299,7 @@ def show_paginated_dataframe(report, rows_per_page=20, model_type='english'):
     
     def format_relevancy_score(x):
         if x is None:
-            return "Not calculated"
+            return "Calculate"
         try:
             return f"{float(x):.2f}"
         except ValueError:
@@ -312,10 +313,10 @@ def show_paginated_dataframe(report, rows_per_page=20, model_type='english'):
     
     report['clickable_url'] = report['page'].apply(make_clickable)
     
-    columns = ['clickable_url', 'query', 'impressions', 'clicks', 'ctr', 'position', 'relevancy_score', 'action']
-    report = report[columns[:-1]]  # Exclude 'action' from the DataFrame
+    columns = ['clickable_url', 'query', 'impressions', 'clicks', 'ctr', 'position', 'relevancy_score']
+    report = report[columns]
 
-    sort_column = st.selectbox("Sort by:", columns[1:-1], index=columns[1:-1].index('impressions'))
+    sort_column = st.selectbox("Sort by:", columns[1:], index=columns[1:].index('impressions'))
     sort_order = st.radio("Sort order:", ("Descending", "Ascending"))
     
     ascending = sort_order == "Ascending"
@@ -327,7 +328,7 @@ def show_paginated_dataframe(report, rows_per_page=20, model_type='english'):
             return 0
     
     report['ctr_numeric'] = report['ctr'].apply(safe_float_convert)
-    report['relevancy_score_numeric'] = report['relevancy_score'].apply(lambda x: safe_float_convert(x) if x != "Not calculated" else -1)
+    report['relevancy_score_numeric'] = report['relevancy_score'].apply(lambda x: safe_float_convert(x) if x != "Calculate" else -1)
     
     sort_column_numeric = sort_column + '_numeric' if sort_column in ['ctr', 'relevancy_score'] else sort_column
     report = report.sort_values(by=sort_column_numeric, ascending=ascending)
@@ -360,9 +361,8 @@ def show_paginated_dataframe(report, rows_per_page=20, model_type='english'):
     def update_dataframe():
         df_html = report.iloc[start_idx:end_idx].to_html(escape=False, index=False)
         df_html = df_html.replace('</table>', ''.join([
-            '<th>Action</th></tr>',
-            *[f'<tr><td colspan="7"></td><td><button onclick="calculate_relevancy({i})">Calculate Relevancy</button></td></tr>'
-              for i in range(start_idx, min(end_idx, len(report)))]
+            *[f'<script>document.getElementsByTagName("table")[0].rows[{i+1}].cells[6].onclick = function() {{ calculate_relevancy({start_idx + i}) }}</script>'
+              for i in range(min(rows_per_page, len(report) - start_idx))]
         ]) + '</table>')
         dataframe_placeholder.markdown(df_html, unsafe_allow_html=True)
     
@@ -379,7 +379,7 @@ def show_paginated_dataframe(report, rows_per_page=20, model_type='english'):
     """, unsafe_allow_html=True)
     
     # Handle relevancy calculation
-    if st.session_state.get('calculate_relevancy'):
+    if st.session_state.get('calculate_relevancy') is not None:
         row_index = st.session_state.calculate_relevancy
         page_content = fetch_content(report.iloc[row_index]['page'])
         query = report.iloc[row_index]['query']
@@ -389,6 +389,7 @@ def show_paginated_dataframe(report, rows_per_page=20, model_type='english'):
         update_dataframe()  # Update the dataframe display
 
     return report
+
 # -------------
 # Main Streamlit App Function
 # -------------
@@ -439,7 +440,7 @@ def main():
                     st.session_state.report_data = fetch_gsc_data(webproperty, search_type, start_date, end_date, selected_dimensions)
 
             if st.session_state.report_data is not None and not st.session_state.report_data.empty:
-                st.write("Data fetched successfully. Click the 'Calculate Relevancy' button in each row to calculate its relevancy score.")
+                st.write("Data fetched successfully. Click 'Calculate' in the Relevancy Score column to calculate the score for each row.")
                 st.session_state.report_data = show_paginated_dataframe(st.session_state.report_data, model_type=model_type)
                 download_csv_link(st.session_state.report_data)
             elif st.session_state.report_data is not None: