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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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Blood_DICT = {'126/83':1, |
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'125/80': 2, |
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'140/90': 3, |
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'120/80': 4, |
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'132/87': 5, |
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'130/86': 6, |
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'117/76': 7, |
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'118/76': 8, |
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'128/85': 9, |
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'131/86': 10, |
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'128/84': 11, |
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'115/75': 12, |
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'135/88': 13, |
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'129/84': 14, |
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'130/85': 15, |
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'115/78': 16, |
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'119/77': 17, |
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'121/79': 18, |
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'125/82': 19, |
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'135/90': 20, |
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'122/80': 21, |
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'142/92': 22, |
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'140/95': 23, |
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'139/91': 24, |
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'118/75': 25, |
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} |
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Gender_DICT = {'Male':1, |
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'Female': 2,} |
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Occupation_DICT = {'Software Engineer':1, |
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'Doctor': 2, |
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'Sales Representative': 3, |
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'Teacher': 4, |
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'Nurse': 5, |
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'Engineer': 6, |
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'Accountant': 7, |
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'Scientist': 8, |
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'Lawyer': 9, |
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'Salesperson': 10, |
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'Manager': 11,} |
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BMI_DICT = {'Overweight':1, |
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'Normal': 2, |
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'Obese': 3, |
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'Normal Weight': 4,} |
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model = joblib.load('rf_n3.joblib') |
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unique_values = joblib.load('unique_values_n3.joblib') |
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unique_Gender = unique_values["Gender"] |
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unique_occupation = unique_values["Occupation"] |
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unique_ฺBMI = unique_values["BMI Category"] |
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unique_Blood = unique_values["Blood Pressure"] |
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def main(): |
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st.title("Sleeping Health") |
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with st.form("questionaire"): |
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Gender = st.selectbox("Gender", unique_Gender) |
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age = st.slider("Age", min_value=27, max_value=59) |
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occupation = st.selectbox("Occupation", unique_occupation) |
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Sleep_Duration = st.slider("Sleep Duration", min_value=5.8, max_value=8.5) |
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Quality_of_Sleep = st.slider("Quality of Sleep", min_value=1, max_value=10) |
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Physical_Activity_Level = st.slider("Physical Activity Level", min_value=30, max_value=90) |
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Stress_Level= st.slider("Stress Level", min_value=1, max_value=10) |
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BMI_Category = st.selectbox("BMI Category", unique_ฺBMI) |
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Blood_Pressure = st.selectbox("Blood Pressure", unique_Blood) |
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Heart_Rate = st.slider("Heart Rate", min_value=65, max_value=86) |
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Daily_Steps = st.slider("Daily Steps", min_value=3000, max_value=10000) |
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clicked_sleep = st.form_submit_button("Predict Sleep Health") |
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if clicked_sleep: |
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result = model.predict(pd.DataFrame({"Gender": [Gender_DICT[Gender]], |
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"Age": [age], |
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"Occupation": [Occupation_DICT[occupation]], |
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"Sleep Duration": [Sleep_Duration], |
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"Quality of Sleep": [Quality_of_Sleep], |
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"Physical Activity Level": [Physical_Activity_Level], |
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"Stress Level": [Stress_Level], |
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"BMI Category": [BMI_DICT[BMI_Category]], |
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"Blood Pressure": [Blood_DICT[Blood_Pressure]], |
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"Heart Rate": [Heart_Rate], |
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"Daily Steps": [Daily_Steps] |
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})) |
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if result[0] == 1: |
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result_message = "None" |
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elif result[0] == 2: |
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result_message = "Sleep Apnea" |
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elif result[0] == 3: |
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result_message = "Insomnia" |
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else: |
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result_message = None |
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if result_message is not None: |
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st.success(result_message) |
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if __name__=='__main__': |
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main() |
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