Update app.py

app.py

@@ -2,65 +2,26 @@ 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')
+model = joblib.load('modelB.joblib')
+unique_values = joblib.load('unique_valuesB.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_gender =  unique_values["Gender"]
+
 
 def main():
-    st.title("Adult Income Analysis")
+    st.title("BMI Predict")
 
     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)
+        Gender = st.selectbox("Gender",unique_gender)
+        Height = st.slider("Height", min_value=140, max_value=199)
+        Weight = st.slider("Weight", min_value=50, max_value=160)
 
-        clicked = st.form_submit_button("Predict income")
+        clicked = st.form_submit_button("BMI")
         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'
-            st.success('The predicted income is {}'.format(result))
+            result=model.predict(pd.DataFrame({"Gender": [Gender],
+                                               "Height": [Height],
+                                               "Weight": [Weight]}))
+            st.success('The predicted BMI is {}'.format(result))
 
 if __name__=='__main__':
     main()