Update app.py

app.py

@@ -14,7 +14,7 @@ st.title("Customer Churn Prediction App")
 st.write("This tool predicts customer churn risk based on their details. Enter the required information below.")
 
 # Collect user input based on dataset columns
-SeniorCitizen = st.selectbox("Is the customer a senior citizen?",[0, 1])
+SeniorCitizen = st.selectbox("Is the customer a senior citizen?",["Yes", "No"])
 Partner = st.selectbox("Does the customer have a partner?", ["Yes", "No"])
 Dependents = st.selectbox("Does the customer have dependents?", ["Yes", "No"])
 PhoneService = st.selectbox("Does the customer have phone service?", ["Yes", "No"])
@@ -27,10 +27,10 @@ TotalCharges = st.number_input("Total Charges", min_value=0.0, value=600.0)
 
 # Convert categorical inputs to match model training
 input_data = pd.DataFrame([{
-    'SeniorCitizen' : 1,
-    'Partner': 1 if Partner == "Yes" else 0,
-    'Dependents': 1 if Dependents == "Yes" else 0,
-    'PhoneService': 1 if PhoneService == "Yes" else 0,
+    'SeniorCitizen': 1 if SeniorCitizen == "Yes" else 0,
+    'Partner': Partner,
+    'Dependents': Dependents,
+    'PhoneService': PhoneService,
     'InternetService': InternetService,
     'Contract': Contract,
     'PaymentMethod': PaymentMethod,