Update app.py

app.py

@@ -633,6 +633,16 @@ def analyze_excel_single(file_path):
         if trustbuilder_present:
             # Create dataframe for trust builder
             results_df_builder = pd.read_csv(csv_output_path_trustbuilder)
+            bucket_colors = {
+                "Stability": "lightblue",
+                "Development": "lightgreen",
+                "Relationship": "lavender",
+                "Benefit": "lightyellow",
+                "Vision": "orange",
+                "Competence": "lightcoral",
+            }
+
+
             combined_data = {
                 "Message": results_df_builder["Message"],
                 "Stability": results_df_builder["Stability"].round(0).astype(int),
@@ -645,8 +655,12 @@ def analyze_excel_single(file_path):
 
             df_builder = pd.DataFrame(combined_data)
 
-            # Create consolidated table
-            # List of bucket columns
+
+
+            # Prepare lists to collect data
+            buckets = []
+            messages = []
+            percentages = []
             bucket_columns = [
                 "Stability",
                 "Development",
@@ -656,11 +670,6 @@ def analyze_excel_single(file_path):
                 "Competence",
             ]
 
-            # Prepare lists to collect data
-            buckets = []
-            messages = []
-            percentages = []
-
             # Iterate through each bucket column
             for bucket in bucket_columns:
                 for index, value in results_df_builder[bucket].items():
@@ -675,8 +684,11 @@ def analyze_excel_single(file_path):
                 "TrustBuilders®": messages,
                 "%": percentages,
             }
+            df_builder_pivot = pd.DataFrame(builder_consolidated).style.applymap(
+                lambda _: f"background-color: {bucket_colors.get(_, '')}", 
+                subset=list(bucket_colors.keys())
+            )
 
-            df_builder_pivot = pd.DataFrame(builder_consolidated)
 
             # Define the order of the Trust Bucket® categories
             trust_driver_order = [
@@ -708,12 +720,6 @@ def analyze_excel_single(file_path):
             )
             
 
-            #df_builder_pivot = df_builder_pivot.sort_values(
-            #    by=["%"], ascending=[False]
-            #)
-            #df_builder_pivot = df_builder_pivot.head(4)
-
-
         # After processing, ensure to delete the temporary files and directory
         os.remove(csv_output_path_trust)
         if nps_present:
@@ -723,7 +729,7 @@ def analyze_excel_single(file_path):
         if consideration_present:
             os.remove(csv_output_path_consideration)
         if satisfaction_present:
-            os.remove(csv_output_pa
+            os.remove(csv_output_path_satisfaction)
         if trustbuilder_present:
             os.remove(csv_output_path_trustbuilder)
         os.remove(text_output_path)