Update app.py

app.py

@@ -117,9 +117,9 @@ def check_data_drift():
         mean_diff = abs(mean_feature_training_data - mean_feature_sample_logs)
 
         if mean_diff > 2 * std_feature_training_data:
-            data_drift_status[feature] = "Data Drift Detected! Check Logs!"
+            data_drift_status[feature] = ["Data Drift Detected! Check Logs!"]
         else:
-            data_drift_status[feature] = "No Data Drift!"
+            data_drift_status[feature] = ["No Data Drift!"]
 
     # Categorical feature Type
 
@@ -129,9 +129,9 @@ def check_data_drift():
     psi_value = psi(live_proportions, training_proportions)
 
     if psi_value > 0.1:
-        data_drift_status['Type'] = "Data Drift Detected! Check Logs!"
+        data_drift_status['Type'] = ["Data Drift Detected! Check Logs!"]
     else:
-        data_drift_status['Type'] = "No Data Drift!"
+        data_drift_status['Type'] = ["No Data Drift!"]
 
     return pd.DataFrame.from_dict(data_drift_status)