Update app.py

app.py

@@ -448,6 +448,8 @@ def analyze_excel_single(file_path):
             if loyalty_missing_ratio > 0.8:
                 df.drop(columns=["Loyalty"], inplace=True)
                 loyalty_present = False
+        else:
+            print("not present")
 
         # Handling Consideration column
         consideration_present = "Consideration" in df.columns
@@ -456,6 +458,8 @@ def analyze_excel_single(file_path):
             if consideration_missing_ratio > 0.8:
                 df.drop(columns=["Consideration"], inplace=True)
                 consideration_present = False
+        else:
+            print("not present")
 
         # Handling Satisfaction column
         satisfaction_present = "Satisfaction" in df.columns
@@ -464,6 +468,8 @@ def analyze_excel_single(file_path):
             if satisfaction_missing_ratio > 0.8:
                 df.drop(columns=["Satisfaction"], inplace=True)
                 satisfaction_present = False
+        else: 
+            print("not present")
 
         # Step 2: Remove missing values and print data shape
         df.dropna(subset=required_columns, inplace=True)
@@ -728,27 +734,30 @@ def analyze_excel_single(file_path):
 
         if img_nps is None:
             # Load the placeholder image if NPS analysis was not performed
-            img_nps = Image.open("./images/nps_not_available.png")
-            img_nps = img_nps.resize((1000, 800), Image.Resampling.LANCZOS)
+            #img_nps = Image.open("./images/nps_not_available.png")
+            #img_nps = img_nps.resize((1000, 800), Image.Resampling.LANCZOS)
+            print("none")
 
         if img_loyalty is None:
             # Load the placeholder image if Loyalty analysis was not performed
-            img_loyalty = Image.open("./images/loyalty_not_available.png")
-            img_loyalty = img_loyalty.resize((1000, 800), Image.Resampling.LANCZOS)
+            #img_loyalty = Image.open("./images/loyalty_not_available.png")
+            #img_loyalty = img_loyalty.resize((1000, 800), Image.Resampling.LANCZOS)
+            print("none")
 
         if img_consideration is None:
             # Load the placeholder image if Consideration analysis was not performed
-            img_consideration = Image.open("./images/consideration_not_available.png")
-            img_consideration = img_consideration.resize(
-                (1000, 800), Image.Resampling.LANCZOS
-            )
+            #img_consideration = Image.open("./images/consideration_not_available.png")
+            #img_consideration = img_consideration.resize(
+            #    (1000, 800), Image.Resampling.LANCZOS
+            #)
+            print("none")
 
         if img_satisfaction is None:
             # Load the placeholder image if Satisfaction analysis was not performed
-            img_satisfaction = Image.open("./images/satisfaction_not_available.png")
-            img_satisfaction = img_satisfaction.resize(
-                (1000, 800), Image.Resampling.LANCZOS
-            )
+            #img_satisfaction = Image.open("./images/satisfaction_not_available.png")
+            #img_satisfaction = img_satisfaction.resize(
+            #    (1000, 800), Image.Resampling.LANCZOS
+            #)
 
         return (
             img_bucketfull,