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import joblib
import pandas as pd
import streamlit as st
dist_dict = {'0-1 Miles' : 1,
'1-2 Miles' : 2,
'2-5 Miles' : 3,
'5-10 Miles' : 4,
'10+ Miles' : 5}
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_Home_Owner = unique_values["Home Owner"]
unique_Region = unique_values["Region"]
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)
Home_Owner = st.selectbox("Home Owner", options=unique_Home_Owner)
Region = st.selectbox("Region", options=unique_Region)
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],
"Home Owner": [Home_Owner],
"Region" : [Region],
"Commute Distance": [dist_dict[Commute_Distance]],
"Age": [Age]}))
# Show prediction
if result == [1]:
i = 'Yes'
else :
i = 'No'
st.success(f'Purchased Bike ={i}')
# Run main()
if __name__ == "__main__":
main() |