import joblib
import pandas as pd
import streamlit as st

EDU_DICT = {'Bachelorsl': 1,
            'Some-college': 2,
            '11th': 3,
            'HS-grad': 4,
            'Prof-school': 5,
            'Assoc-acdm': 6,
            'Assoc-voc': 7,
            '9th': 8,
            '7th-8th': 9, 
            '12th': 10,
            'Masters': 11,
            '1st-4th': 12,
            '10th': 13,
            'Doctorate': 14,
            '5th-6th': 15,
            'Preschool': 16
            }

model = joblib.load('model.joblib')
unique_values = joblib.load('unique_values.joblib')
unique_class =  unique_values["workclass"]
unique_education =  unique_values["education"]
unique_marital =  unique_values["marital-status"]
unique_occupation =  unique_values["occupation"]
unique_relationship =  unique_values["relationship"]
unique_race =  unique_values["race"]
unique_sex = unique_values["sex"]
unique_country =  unique_values["native-country"]
 
 
def main():
    st.title("Adult Income")

    with st.form("questionaire"):
        age = st.slider("Age" , min_value=17 , max_value=90)
        workclass = st.selectbox("Workclass" , options=unique_class)
        fnlwgt = st.slider("Fnlwgt" , min_value=12285 , max_value=1484705)
        education = st.selectbox("Education" , options=unique_education)
        education_num = st.slider("Education-num" , min_value=1 , max_value=16)
        marital_status = st.selectbox("Marital-status" , options=unique_marital)
        occupation = st.selectbox("Occupation" , options=unique_occupation)
        relationship = st.selectbox("Relationship" , options=unique_relationship)
        race = st.selectbox("Race" , options=unique_race)
        sex = st.selectbox("Sex" , options=unique_sex) 
        capital_gain = st.slider("Capital-gain" , min_value=0 , max_value=99999)
        capital_loss = st.slider("Capital-loss" , min_value=0 , max_value=4356)
        hours_per_week = st.slider("Hours-per-week" , min_value=1 , max_value=100)
        native_country = st.selectbox("Native-country" , options=unique_country)

        # clicked==True only when the button is clicked
        clicked = st.form_submit_button("Predict income")
        if clicked:
            result=model.predict(pd.DataFrame({"age": [age],
                                               "workclass": [workclass],
                                               "fnlwgt": [fnlwgt],
                                               "education": [EDU_DICT[education]],
                                               "education_num": [education_num],
                                               "marital_status": [marital_status],
                                               "occupation": [occupation],
                                               "relationship": [relationship],
                                               "race": [race],
                                               "sex": [sex],
                                               "capital-gain": [capital_gain],
                                               "capital-loss": [capital_loss],
                                               "hours-per-week": [hours_per_week],
                                               "native-country": [native_country]}))
            # Show prediction
            result = '>50k' if result[0] == 1 else '<=50k'
            st.success("Your predicted income is "+result)
            
            
# Run main()
if __name__ == "__main__" :
    main()