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import joblib
import pandas as pd
import streamlit as st
EDU_DICT = {'18-24': 1,
'25-29': 2,
'30-34': 3,
'35-39': 4,
'40-44': 5,
'45-49': 6,
'50-54': 7,
'55-59': 8,
'60-64': 9,
'65-69': 10,
'70-74': 11,
'75-79': 12,
'80+': 13
}
model = joblib.load('model_n.joblib')
unique_values = joblib.load('unique_values_n.joblib')
#unique_General_Health = unique_values["General_Health"]
unique_Checkup = unique_values["Checkup"]
unique_Exercise = unique_values["Exercise"]
unique_Heart_Disease = unique_values["Heart_Disease"]
unique_Skin_Cancer = unique_values["Skin_Cancer"]
unique_Other_Cancer = unique_values["Other_Cancer"]
unique_Depression = unique_values["Depression"]
unique_Diabetes = unique_values["Diabetes"]
unique_Arthritis = unique_values["Arthritis"]
unique_Sex = unique_values["Sex"]
unique_Age_Category = unique_values["Age_Category"]
unique_Smoking_History = unique_values["Smoking_History"]
def main():
st.title("General Health analysis")
with st.form("questionaire"):
Checkup = st.selectbox("Checkup", unique_Checkup)
Exercise = st.selectbox("Exercise", unique_Exercise)
Heart_Disease = st.selectbox("Heart Disease", unique_Heart_Disease)
Skin_Cancer = st.selectbox("Skin Cancer", unique_Skin_Cancer)
Other_Cancer = st.selectbox("Other Cancer", unique_Other_Cancer)
Depression = st.selectbox("Depression", unique_Depression)
Diabetes = st.selectbox("Diabetes", unique_Diabetes)
Arthritis = st.selectbox("Arthritis", unique_Arthritis)
Sex = st.selectbox("Sex", unique_Sex)
Age_Category = st.selectbox("Age Category", unique_Age_Category)
BMI = st.slider("BMI", min_value=1, max_value=50)
Smoking_History = st.selectbox("Smoking History", unique_Smoking_History)
Alcohol_Consumption = st.slider("Alcohol Consumption", min_value=0, max_value=100)
Fruit_Consumption = st.slider("Fruit Consumption", min_value=0, max_value=100)
Green_Vegetables_Consumption = st.slider("Green Vegetables Consumption", min_value=0, max_value=100)
FriedPotato_Consumption = st.slider("Fried Potato Consumption", min_value=0, max_value=100)
Weight_ == st.slider("Weight_(kg)", min_value=100, max_value=200)
Height_ == st.slider("Height_(cm)", min_value=100, max_value=200)
clicked = st.form_submit_button("Predict General Health")
if clicked:
result=model.predict(pd.DataFrame({"Checkup": [Checkup],
"Exercise": [Exercise],
"Heart_Disease": [Heart_Disease],
"Skin_Cancer": [Skin_Cancer],
"Other_Cancer": [Other_Cancer],
"Depression": [Depression],
"Diabetes": [Diabetes],
"Arthritis": [Arthritis],
"Sex": [Sex],
"Age_Category": [EDU_DICT[Age_Category]],
"BMI": [BMI],
"Smoking_History": [Smoking_History],
"Alcohol_Consumption": [Alcohol_Consumption],
"Fruit_Consumption": [Fruit_Consumption],
"Green_Vegetables_Consumption": [Green_Vegetables_Consumption],
"FriedPotato_Consumption": [FriedPotato_Consumption],
"Weight_(kg)": [Weight_],
"Height_(cm)": [Height_]}))
result = 'Very Good' if result[0] == 1 else 'Poor'
st.success('The predicted General Health is {}'.format(result))
if __name__=='__main__':
main()
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