Upload app.py

app.py

@@ -0,0 +1,45 @@
+import joblib
+import pandas as pd
+import streamlist as st
+
+
+model = joblib.load('model.joblib')
+unique_values = joblib.load('unique_values.joblib')
+    
+unique_Marital_Status =  unique_values["Marital Status"]
+unique_Gender =  unique_values["Gender"]
+unique_Occupation =  unique_values["Occupation"]
+unique_Home_Owner =  unique_values["Home Owner"]
+unique_Region =  unique_values["Region"]
+unique_Education =  unique_values["Education"]
+unique_Commute_Distance =  unique_values["Commute Distance"]
+
+
+def main():
+    st.title("Bike buyer")
+
+    with st.form("questionaire"):
+        Marital_Status = st.selectbox("Marital Status", options=unique_Marital_Status)
+        Gender = st.selectbox("Gender", options=unique_Gender)
+        Education = st.selectbox("Education", options=unique_Education)
+        Occupation = st.selectbox("Occupation", options=unique_Occupation)
+        Home_Owner = st.selectbox("Home Owner", options=unique_Home_Owner)
+        Commute_Distance = st.selectbox("Commute Distance", options=unique_Commute_Distance)
+        Age = st.slider("Age", min_value=0, max_value=100)
+
+
+        # clicked==True only when the button is clicked
+        clicked = st.form_submit_button("Predict bike buyer")
+        if clicked:
+            result=model.predict(pd.DataFrame({"Marital Status": [Marital_Status],
+                                               "Gender": [Gender],
+                                               "Education": [Education],
+                                               "Occupation": [Occupation],
+                                               "Home Owner": [Home_Owner],
+                                               "Commute Distance": [Commute_Distance],
+                                               "Age": [Age]}))
+            # Show prediction
+            st.success("Purchased Bike", result)
+# Run main()
+if __name__ == "__main__":
+    main()