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app.py

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+# -*- coding: utf-8 -*-
+"""Untitled15.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1LkYVMK8AOEpUsR_FhEmhaVir9hAQSBsg
+"""
+
+import joblib
+import pandas as pd
+import streamlit as st
+smoking_status = {'formerly smoked': 1,
+            'never smoked	': 2,
+            'smokes': 3,
+            'Unknown': 4,
+            }
+
+model = joblib.load('model.joblib')
+unique_values = joblib.load('unique_values.joblib')
+unique_gender = unique_values["gender"]
+unique_ever_married = unique_values["ever_married"]
+unique_work_type = unique_values["work_type"]
+unique_Residence_type = unique_values["Residence_type"]
+unique_smoking_status = unique_values["smoking_status"]
+
+
+def main():
+  st.title("Adult Income Analysis")
+  with st.form("questionaire"):
+      age = st.slider("age", min_value=0, max_value=100)
+      gender = st.selectbox("gender", unique_gender)
+      hypertension = st.slider("hypertension", min_value=0, max_value=1)
+      heart_disease = st.slider("heart_disease", min_value=0, max_value=1)
+      ever_married = st.selectbox("ever_married", unique_ever_married)
+      work_type = st.selectbox("work_type", unique_work_type)
+      Residence_type = st.selectbox("Residence_type", unique_Residence_type)
+      avg_glucose_level = st.slider("avg_glucose_level", min_value=0, max_value=300)
+      bmi = st.slider("bmi", min_value=0, max_value=100)
+      smoking_status = st.selectbox("smoking_status", unique_smoking_status)
+
+      clicked = st.form_submit_button("Predict stroke")
+      if clicked:
+        result=model.predict(pd.DataFrame({"age": [age],
+                                      "gender": [gender],
+                                      "hypertension": [hypertension],
+                                      "heart_disease": [heart_disease],
+                                      "ever_married": [ever_married],
+                                      "work_type": [work_type],
+                                      "Residence_type": [Residence_type],
+                                      "avg_glucose_level": [avg_glucose_level],
+                                      "bmi": [bmi],
+                                      "smoking_status":[smoking_status]}))
+        result = '1' if result[0] == 1 else '0'
+        st.success('The predicted stroke is {}'.format(result))
+if __name__=='__main__':
+  main()

model.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6074ed90c8d54cda47c2f4649c85593f868ca8f25e25fcd3cf3f8b9e1af01ea4
+size 76513

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:d50a7d378062a047249d0a3a123de19866e62dcf3d47aae7acbded938be46d45
+size 1425