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import joblib |
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import pandas as pd |
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import streamlit as st |
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EDU_DICT = {'18-24': 1, |
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'25-29': 2, |
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'30-34': 3, |
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'35-39': 4, |
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'40-44': 5, |
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'45-49': 6, |
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'50-54': 7, |
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'55-59': 8, |
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'60-64': 9, |
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'65-69': 10, |
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'70-74': 11, |
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'75-79': 12, |
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'80+': 13 |
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} |
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model = joblib.load('model_n.joblib') |
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unique_values = joblib.load('unique_values_n.joblib') |
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unique_Checkup = unique_values["Checkup"] |
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unique_Exercise = unique_values["Exercise"] |
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unique_Heart_Disease = unique_values["Heart_Disease"] |
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unique_Skin_Cancer = unique_values["Skin_Cancer"] |
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unique_Other_Cancer = unique_values["Other_Cancer"] |
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unique_Depression = unique_values["Depression"] |
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unique_Diabetes = unique_values["Diabetes"] |
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unique_Arthritis = unique_values["Arthritis"] |
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unique_Sex = unique_values["Sex"] |
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unique_Age_Category = unique_values["Age_Category"] |
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unique_Smoking_History = unique_values["Smoking_History"] |
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def main(): |
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st.title("General Health analysis") |
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with st.form("questionaire"): |
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Checkup = st.selectbox("Checkup", unique_Checkup) |
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Exercise = st.selectbox("Exercise", unique_Exercise) |
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Heart_Disease = st.selectbox("Heart Disease", unique_Heart_Disease) |
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Skin_Cancer = st.selectbox("Skin Cancer", unique_Skin_Cancer) |
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Other_Cancer = st.selectbox("Other Cancer", unique_Other_Cancer) |
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Depression = st.selectbox("Depression", unique_Depression) |
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Diabetes = st.selectbox("Diabetes", unique_Diabetes) |
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Arthritis = st.selectbox("Arthritis", unique_Arthritis) |
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Sex = st.selectbox("Sex", unique_Sex) |
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Age_Category = st.selectbox("Age Category", unique_Age_Category) |
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BMI = st.slider("BMI", min_value=1, max_value=50) |
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Smoking_History = st.selectbox("Smoking History", unique_Smoking_History) |
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Alcohol_Consumption = st.slider("Alcohol Consumption", min_value=0, max_value=100) |
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Fruit_Consumption = st.slider("Fruit Consumption", min_value=0, max_value=100) |
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Green_Vegetables_Consumption = st.slider("Green Vegetables Consumption", min_value=0, max_value=100) |
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FriedPotato_Consumption = st.slider("Fried Potato Consumption", min_value=0, max_value=100) |
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Weight_kg = st.slider("Weight_(kg)", min_value=30, max_value=150) |
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Height_cm = st.slider("Height_(cm)", min_value=100, max_value=200) |
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clicked = st.form_submit_button("Predict General Health") |
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if clicked: |
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result=model.predict(pd.DataFrame({"Checkup": [Checkup], |
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"Exercise": [Exercise], |
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"Heart_Disease": [Heart_Disease], |
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"Skin_Cancer": [Skin_Cancer], |
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"Other_Cancer": [Other_Cancer], |
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"Depression": [Depression], |
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"Diabetes": [Diabetes], |
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"Arthritis": [Arthritis], |
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"Sex": [Sex], |
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"Age_Category": [EDU_DICT[Age_Category]], |
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"BMI": [BMI], |
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"Smoking_History": [Smoking_History], |
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"Alcohol_Consumption": [Alcohol_Consumption], |
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"Fruit_Consumption": [Fruit_Consumption], |
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"Green_Vegetables_Consumption": [Green_Vegetables_Consumption], |
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"FriedPotato_Consumption": [FriedPotato_Consumption], |
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"Weight_kg": [Weight_kg], |
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"Height_cm": [Height_cm]})) |
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result = 'Very Good' if result[0] == 1 else 'Poor' |
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st.success('The predicted General Health is {}'.format(result)) |
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if __name__=='__main__': |
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main() |
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