Update app.py

app.py

@@ -1,83 +1,94 @@
-import streamlit as st 
-import joblib
-import numpy as np
-html_temp = """
-    <div style="background-color:black;padding:10px">
-    <h2 style="color:white;text-align:center;">Banking Churn Model App </h2>
-    </div>
-    """
-st.markdown(html_temp, unsafe_allow_html=True)
-
-st.write("Enter the customer details:")
-
-# model
-
-bank_model=joblib.load("bank_churn_svc_model.joblib")
-
-# Input variables
-
-col1, col2 = st.columns(2)
-with col1:
-    ## CreditScore
-    credit_score=st.slider("Slide the Credit Score Value:",min_value=350,max_value=850)
-    
-with col2:
-    ## Geography
-    option_geo=["France","Spain","Germany"]
-    geo=st.selectbox("Select The Geography: ",options=option_geo)
-    geography_value=option_geo.index(geo)
-    
-col1, col2 = st.columns(2)
-with col1:
-    ## gender
-    option_gen=["Female "," Male"]
-    gen=st.selectbox("Select the Gender",option_gen) 
-    gender_value=option_gen.index(gen)
-with col2:
-    ## Age
-    age=st.number_input("Enter your AGE:",max_value=92,min_value=18)
-
-col1,col2=st.columns(2)
-with col1:
-    ## Tenure
-    tenure=st.slider("Slide the Tenure of the Loan:",min_value=0,max_value=10)
-    
-with col2:
-    ## Balance
-    balance=st.slider("Slide The Balance Of the your Account:",min_value=0.0,max_value=250898.09)
-    
-col1,col2=st.columns(2)
-
-with col1:
-    ## IsActiveMember
-    active_holder= st.radio("Are you Active Account Holder:", ["YES", "NO"])
-    if active_holder=="YES":
-        active_holder_value=1
-    else:
-        active_holder_value=0
-        
-with col2:
-    ## EstimatedSalary
-    e_salary=st.slider("Silde the Salary :",max_value=199992,min_value=11)
-    
-
-
-if st.button("Submit"):
-    
-    # Scaler the values
-    
-    credit_score=np.round(((credit_score-650.528800)/96.653299),3)
-    age=np.round(((age-38.921800)/10.487806),3)
-    tenure=np.round(((tenure-5.012800)/2.8921740),3)
-    balance=np.round(((balance-76485.889288)/62397.405202),3)
-    e_salary=np.round(((e_salary-100090.239881)/57510.492818),3)
-    
-    
-    output = bank_model.predict([[credit_score, geography_value, gender_value, age, tenure, balance,  e_salary,  active_holder_value]])
-
-    
-    if output ==0:
-        st.write("The Customer is Interseted in our Bank")
-    else:
-        st.write("The Customer is Not Interseted in our Bank")
+import streamlit as st 
+import joblib
+import numpy as np
+html_temp = """
+    <div style="background-color:black;padding:10px">
+    <h2 style="color:white;text-align:center;">Banking Churn Model App </h2>
+    </div>
+    """
+st.markdown(html_temp, unsafe_allow_html=True)
+st.markdown(f"""
+    <style>
+        /* Set the background image for the entire app */
+        .stApp {{
+            background-color#abf62d;
+            background-size: 100px;
+            background-repeat:no;
+            background-attachment: auto;
+            background-position:full;
+        }}
+    </style>
+    """, unsafe_allow_html=True)
+st.write("Enter the customer details:")
+
+# model
+
+bank_model=joblib.load("bank_churn_svc_model.joblib")
+
+# Input variables
+
+col1, col2 = st.columns(2)
+with col1:
+    ## CreditScore
+    credit_score=st.slider("Slide the Credit Score Value:",min_value=350,max_value=850)
+    
+with col2:
+    ## Geography
+    option_geo=["France","Spain","Germany"]
+    geo=st.selectbox("Select The Geography: ",options=option_geo)
+    geography_value=option_geo.index(geo)
+    
+col1, col2 = st.columns(2)
+with col1:
+    ## gender
+    option_gen=["Female "," Male"]
+    gen=st.selectbox("Select the Gender",option_gen) 
+    gender_value=option_gen.index(gen)
+with col2:
+    ## Age
+    age=st.number_input("Enter your AGE:",max_value=92,min_value=18)
+
+col1,col2=st.columns(2)
+with col1:
+    ## Tenure
+    tenure=st.slider("Slide the Tenure of the Loan:",min_value=0,max_value=10)
+    
+with col2:
+    ## Balance
+    balance=st.slider("Slide The Balance Of the your Account:",min_value=0.0,max_value=250898.09)
+    
+col1,col2=st.columns(2)
+
+with col1:
+    ## IsActiveMember
+    active_holder= st.radio("Are you Active Account Holder:", ["YES", "NO"])
+    if active_holder=="YES":
+        active_holder_value=1
+    else:
+        active_holder_value=0
+        
+with col2:
+    ## EstimatedSalary
+    e_salary=st.slider("Silde the Salary :",max_value=199992,min_value=11)
+    
+
+
+if st.button("Submit"):
+    
+    # Scaler the values
+    
+    credit_score=np.round(((credit_score-650.528800)/96.653299),3)
+    age=np.round(((age-38.921800)/10.487806),3)
+    tenure=np.round(((tenure-5.012800)/2.8921740),3)
+    balance=np.round(((balance-76485.889288)/62397.405202),3)
+    e_salary=np.round(((e_salary-100090.239881)/57510.492818),3)
+    
+    
+    output = bank_model.predict([[credit_score, geography_value, gender_value, age, tenure, balance,  e_salary,  active_holder_value]])
+
+    
+    if output ==0:
+        st.write("The Customer is Interseted in our Bank")
+    else:
+        st.write("The Customer is Not Interseted in our Bank")