Upload app.py

app.py

@@ -2,64 +2,44 @@ import joblib
 import pandas as pd
 import streamlit as st 
 
-EDU_DICT = {'Preschool': 1,
-            '1st-4th': 2,
-            '5th-6th': 3,
-            '7th-8th': 4,
-            '9th': 5,
-            '10th': 6,
-            '11th': 7,
-            '12th': 8,
-            'HS-grad': 9, 
-            'Some-college': 10,
-            'Assoc-voc': 11,
-            'Assoc-acdm': 12,
-            'Bachelors': 13,
-            'Masters': 14,
-            'Prof-school': 15,
-            'Doctorate': 16
-            }
+
 
 model = joblib.load('model.joblib')
 unique_values = joblib.load('unique_values.joblib')
     
-unique_class =  unique_values["workclass"]
-unique_education =  unique_values["education"]
-unique_marital_status =  unique_values["marital.status"]
-unique_relationship =  unique_values["relationship"]
-unique_occupation =  unique_values["occupation"]
-unique_sex =  unique_values["sex"]
-unique_race = unique_values["race"]
-unique_country =  unique_values["native.country"]
+unique_hypertension =  unique_values["hypertension"]
+unique_heart_disease =  unique_values["heart_disease"]
+unique_bmi =  unique_values["bmi"]
+unique_HbA1c_level =  unique_values["HbA1c_level"]
+unique_blood_glucose_level =  unique_values["blood_glucose_level"]
+unique_gender =  unique_values["gender"]
+unique_smoking_history = unique_values["smoking_history"]
 
 def main():
-    st.title("Adult Income Analysis")
+    st.title("diabetes prediction")
 
     with st.form("questionaire"):
         age = st.slider("Age", min_value=10, max_value=100)
-        workclass = st.selectbox("Workclass", unique_class)
-        education = st.selectbox("Education", unique_education)
-        Marital_Status = st.selectbox("Marital Status", unique_marital_status)
-        occupation = st.selectbox("Occupation", unique_occupation)
-        relationship = st.selectbox("Relationship", unique_relationship)
-        race = st.selectbox("Race", unique_race)
-        sex = st.selectbox("Sex", unique_sex)
-        hours_per_week = st.slider("Hours per week", min_value=1, max_value=100)
-        native_country = st.selectbox("Country", unique_country)
+        hypertension = st.selectbox("Hypertemsion", unique_hypertension)
+        heart_disease = st.selectbox("Heart_desease", unique_heart_disease)
+        bmi = st.selectbox("Bmi", unique_bmi)
+        HbA1c_level = st.selectbox("HbA1c_level", unique_HbA1c_level)
+        blood_glucose_level = st.selectbox("Blood_glucose_level", blood_glucose_level)
+        gender = st.selectbox("Gender", gender)
+        smoking_history = st.selectbox("Smoking_history", smoking_history)
+
 
-        clicked = st.form_submit_button("Predict income")
+        clicked = st.form_submit_button("Predict diabetes")
         if clicked:
             result=model.predict(pd.DataFrame({"age": [age],
-                                               "workclass": [workclass],
-                                               "education": [EDU_DICT[education]],
-                                               "marital.status": [Marital_Status],
-                                               "occupation": [occupation],
-                                               "relationship": [relationship],
-                                               "race": [race],
-                                               "sex": [sex],
-                                               "hours.per.week": [hours_per_week],
-                                               "native.country": [native_country]}))
-            result = '>50K' if result[0] == 1 else '<=50K'
+                                               "hypertension": [hypertension],
+                                               "heart_disease": [heart_disease],
+                                               "bmi": [bmi],
+                                               "HbA1c_level": [HbA1c_level],
+                                               "blood_glucose_level": [blood_glucose_level],
+                                               "gender": [gender],
+                                               "smoking_history": [smoking_history]}))
+            result = '0' if result[0] == 1 else '1'
             st.success('The predicted income is {}'.format(result))
 
 if __name__=='__main__':