final submission

eda.py

@@ -68,7 +68,7 @@ def run():
     # Magic Syntax
     st.write(
     ' On this page, the author will do a simple exploration.'
-    ' The dataset used is the Churn Custimer dataset.'
+    ' The dataset used is the Churn Customer dataset.'
     ' This dataset comes from Github Project Hacktiv8.')
 
     # Show DataFrame

prediction.py

@@ -13,7 +13,7 @@ model_ann = load_model('customer_churn.h5')
 
 def run():
     with st.form(key='Churn_Customer_Prediction'):
-        churn_risk_score = st.selectbox('Churn Risk', (0, 1), index=1)
+        user_id = st.text_input('User_ID', value='')
         age = st.number_input('Age', min_value=23, max_value=65, value=23)
         gender = st.selectbox('Gender', ('Male', 'Female'), index=1)
         days_since_last_login = st.number_input('Last Login', min_value=0, max_value=26, value=0)
@@ -50,6 +50,7 @@ def run():
         submitted = st.form_submit_button('Predict')
 
     data_inf = {
+    'user_id': user_id,
     'age': age,
     'gender': gender,
     'region_category': region_category,
@@ -69,8 +70,7 @@ def run():
     'offer_application_preference': offer_application_preference,
     'past_complaint': past_complaint,
     'complaint_status': complaint_status,
-    'feedback': feedback,
-    'churn_risk_score': churn_risk_score
+    'feedback': feedback
     }
 
     data_inf = pd.DataFrame([data_inf])