Update app.py

app.py

@@ -8,14 +8,13 @@ from sklearn.preprocessing import StandardScaler
 from xgboost import XGBClassifier
 from sklearn.model_selection import train_test_split 
 from sklearn.preprocessing import LabelEncoder
-#from main import cross_sell
 
 
 
 st.title("Health Insurance Cross Sell Prediction")
 st.sidebar.header('Customer Data')
 
-df = pd.read_csv('health_insurance.csv')
+#df = pd.read_csv('health_insurance.csv')
 
 
 # DATA from user
@@ -50,9 +49,9 @@ def user_report():
       is_your_vechile_damaged=0
   else:
       is_your_vechile_damaged=1
-  annual_premium = st.sidebar.slider('Enter Annjual premium you pay', 2000,60000, 5000 )
+  annual_premium = st.sidebar.slider('Enter Annual premium you pay', 2000,60000, 5000 )
   policy_sales_channel= st.sidebar.number_input("Policy Sales Channel(Enter any number between 1 to 160)",step =1,min_value=1,max_value=160)
-  number_of_days_company = st.sidebar.number_input("Enter the number of days Associaed with company",step=1)
+  number_of_days_company = st.sidebar.number_input("Enter the number of days Associaed with company(Vintage)",step=1)
 
   user_report_data = {
       'Gender':gender,