Update app.py

app.py

@@ -55,10 +55,13 @@ def check_model_drift():
     p_pos_label_training_data = 0.03475
     training_data_size = 8000
     
-    p_0 = sample_df.prediction.value_counts()[0]
-    p_1 = sample_df.prediction.value_counts()[1]
+    n_0 = sample_df.prediction.value_counts()[0]
+    try:
+        n_1 = sample_df.prediction.value_counts()[1]
+    except Exception as e:
+        n_1 = 0
 
-    p_pos_label_sample_logs = p_1/(p_0+p_1)
+    p_pos_label_sample_logs = n_1/(n_0+n_1)
     
     variance = (p_pos_label_training_data * (1-p_pos_label_training_data))/training_data_size
     p_diff = abs(p_pos_label_training_data - p_pos_label_sample_logs)