Changed column name for shortlist score and preview cols for shortlist

app.py

@@ -74,7 +74,7 @@ if uploaded_file is not None:
                 )
         
         scored_full = shortlist_applications(df, k=len(df))
-        threshold_score = scored_full["auto_shortlist_score"].quantile(quantile_map[mode])
+        threshold_score = scored_full["shortlist_score"].quantile(quantile_map[mode])
         auto_short = shortlist_applications(df, threshold=threshold_score)
 
         st.title("Filters")
@@ -114,9 +114,17 @@ if uploaded_file is not None:
         shortlistCounter_col.metric("Shorlist Length",  len(auto_short))
         mode_col.metric("Mode", mode)
 
-        freeform_col_index = auto_short.columns.get_loc(freeform_col)
-        st.dataframe(auto_short.iloc[:, freeform_col_index:], hide_index=True)
-
+        shorltist_cols_to_show = [
+                freeform_col,
+                'Usage',
+                'necessity_index',
+                'urgency_score',
+                'severity_score',
+                'vulnerability_score',
+                'shortlist_score'
+                ]
+
+        st.dataframe(auto_short.loc[:, shorltist_cols_to_show], hide_index=True)
 
         ## REVIEW APPLICATIONS 
 

functions/shortlist.py

@@ -60,13 +60,13 @@ def shortlist_applications(
         weights['usage'] * usage_score
     )
     df = df.copy()
-    df['auto_shortlist_score'] = combined
+    df['shortlist_score'] = combined
 
     # Select applications based on k or threshold
-    df_sorted = df.sort_values('auto_shortlist_score', ascending=False)
+    df_sorted = df.sort_values('shortlist_score', ascending=False)
     if k is not None:
         result = df_sorted.head(k)
     else:
-        result = df_sorted[df_sorted['auto_shortlist_score'] >= threshold]
+        result = df_sorted[df_sorted['shortlist_score'] >= threshold]
 
-    return result
+    return result