Update app.py

app.py

@@ -14,9 +14,9 @@ import pickle
 def predict(age, workclass, education, marital_status, occupation, relationship, race, gender, capital_gain, capital_loss, hours_per_week, native_country):
     features = [age, workclass, education, marital_status, occupation, relationship, race, gender, capital_gain, capital_loss, hours_per_week, native_country]
     columns = {
-    "age": age, "workclass":workclass, "educational-num":education, "marital-status":marital_status, "occupation":occupation, 
-    "relationship":relationship, "race":race, "gender":gender, "capital-gain":capital_gain, "capital-loss":capital_loss, 
-    "hours-per-week":hours_per_week, "native-country":native_country}
+    "age": [age], "workclass":[workclass], "educational-num":[education], "marital-status":[marital_status], "occupation":[occupation], 
+    "relationship":[relationship], "race":[race], "gender":[gender], "capital-gain":[capital_gain], "capital-loss":[capital_loss], 
+    "hours-per-week":[hours_per_week], "native-country":[native_country]}
     df = pd.DataFrame(data=columns)
     fixed_features = cleaning_features(df)
     # prediction = model.predict(features)