Upload app.py

app.py

@@ -90,7 +90,7 @@ def update_prediction(input_data):
 def get_input_data():
     """
     Generate input layout and get input values.
-        
+
     -return: DataFrame with input data.
     """
     session.input_data = pd.DataFrame()
@@ -103,7 +103,7 @@ def get_input_data():
             session.input_data['age'] = st.slider(
                 'Age', 18, 75, on_change=update_prediction(session.input_data))
         with col_sex:
-            session.input_data['sex'] = st.radio(
+            session.input_data['gender'] = st.radio(
                 'Sex', ['Female', 'Male'],
                 on_change=update_prediction(session.input_data))
 
@@ -129,8 +129,41 @@ def get_input_data():
                 'Diastolic blood pressure', 50, 120,
                 on_change=update_prediction(session.input_data))
 
+        # Row 4
+        col_chole, col_gluc = st.columns(2)
+        with col_chole:
+            session.input_data['cholesterol'] = st.radio(
+                'Cholesterol', ['Normal', 'Above normal', 'Well above normal'],
+                on_change=update_prediction(session.input_data))
+        with col_gluc:
+            session.input_data['gluc'] = st.radio(
+                'Glucose', ['Normal', 'Above normal', 'Well above normal'],
+                on_change=update_prediction(session.input_data))
+
+        # Row 5
+        col_alco, col_smk = st.columns(2)
+        with col_alco:
+            session.input_data['alco'] = st.radio(
+                'Alcohol intake', ['Yes', 'No'],
+                on_change=update_prediction(session.input_data))
+        with col_smk:
+            session.input_data['smoke'] = st.radio(
+                'Smoking', ['Yes', 'No'],
+                on_change=update_prediction(session.input_data))
+
+        # Row 6
+        session.input_data['active'] = st.radio(
+            'Physical activity', ['Yes', 'No'],
+            on_change=update_prediction(session.input_data))
+
         st.write("")
 
+    # Compute extra features
+    session.input_data["bmi"] = session.input_data["weight"] \
+        / (session.input_data["height"]/100)**2
+    session.input_data["bad_habits"] = session.input_data["smoke"] \
+        & session.input_data["alco"]
+
     return session.input_data
 
 
@@ -138,9 +171,9 @@ def generate_prediction(input_data):
     """
     Generate prediction of cardiovascular disease probability based on input
     data.
-    
+
     -param input_data: DataFrame with input data
-    
+
     -return: prediction of cardiovascular disease probability
     """
     return MODEL.predict(input_data)