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app.py

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+# -*- coding: utf-8 -*-
+"""app.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1NiGtTsWgQO-_sqya-2Qexup3M8BcmfYI
+"""
+
+import joblib
+import pandas as pd
+import streamlit as st
+
+AgeCategory_new = {'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 or older':13}
+
+model = joblib.load('model.joblib')
+unique_values = joblib.load('unique_values.joblib')
+
+unique_Smoking =  unique_values["Smoking"]
+unique_AlcoholDrinking =  unique_values["AlcoholDrinking"]
+unique_Stroke =  unique_values["Stroke"]
+unique_DiffWalking =  unique_values["DiffWalking"]
+unique_Sex =  unique_values["Sex"]
+unique_race = unique_values["race"]
+unique_Diabetic =  unique_values["Diabetic"]
+unique_PhysicalActivity =  unique_values["PhysicalActivity"]
+unique_GenHealth =  unique_values["GenHealth"]
+unique_Asthma =  unique_values["Asthma"]
+unique_KidneyDisease =  unique_values["KidneyDisease"]
+unique_SkinCancer =  unique_values["SkinCancer"]
+unique_AgeCategory =  unique_values["AgeCategory"]
+
+def main():
+    st.title("Personal Key Indicators of Heart Disease")
+
+    with st.form("questionaire"):
+        BMI = st.slider("BMI", min_value=10, max_value=100)
+        Smoking = st.selectbox("Smoking", unique_Smoking)
+        AlcoholDrinking = ("AlcoholDrinking", unique_AlcoholDrinking)
+        Stroke = ("Stroke", unique_Stroke)
+        PhysicalHealth = st.slider("PhysicalHealth", min_value=0, max_value=50)
+        MentalHealth = st.slider("MentalHealth", min_value=0, max_value=50)
+        DiffWalking = ("DiffWalking", unique_DiffWalking)
+        Sex = ("Sex", unique_Sex)
+        AgeCategory = ("AgeCategory_new", unique_AgeCategory)
+        Race = ("Race", unique_Race)
+        Diabetic = ("Diabetic", unique_Diabetic)
+        PhysicalActivity = ("PhysicalActivity", unique_PhysicalActivity)
+        GenHealth = ("GenHealth", unique_GenHealth)
+        SleepTime = st.slider("SleepTime", min_value=0, max_value=24)
+        Asthma = ("Asthma", unique_Asthma)
+        KidneyDisease = ("KidneyDisease", unique_KidneyDisease)
+        SkinCancer = ("SkinCancer", unique_SkinCancer)
+
+        clicked = st.form_submit_button("Predict HeartDisease")
+        if clicked:
+            result=model.predict(pd.DataFrame({"BMI": [BMI],
+                                               "Smoking": [Smoking],
+                                               "AlcoholDrinking": [AlcoholDrinking],
+                                               "Stroke": [Stroke],
+                                               "PhysicalHealth": [PhysicalHealth],
+                                               "MentalHealth": [MentalHealth],
+                                               "DiffWalking": [DiffWalking],
+                                               "sex": [sex],
+                                               "AgeCategory_new": [AgeCategory_new[AgeCategory]],
+                                               "race": [race],
+                                               "Diabetic": [Diabetic],
+                                               "PhysicalActivity": [PhysicalActivity],
+                                               "GenHealth": [GenHealth],
+                                               "SleepTime": [SleepTime],
+                                               "Asthma": [Asthma],
+                                               "KidneyDisease": [KidneyDisease],
+                                               "SkinCancer": [SkinCancer]}))
+            result = 'Yes' if result[0] == 1 else 'No'
+            st.success('The predicted HeartDisease is {}'.format(result))
+
+if __name__=='__main__':
+    main()

model.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3c33bab3a333ca2956756983f530d1ec727da8d6f285f9b1f8ffb92939dd559e
+size 400322

requirements.txt

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+joblib
+pandas
+scikit-learn==1.2.2
+xgboost==1.7.6
+altair<5

unique_values.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f88a8401450d235f5b3db981bed97ba6fbebedb3f88bb4d700cb1b49332e5a3c
+size 3731