Update app.py

app.py

@@ -1,51 +1,47 @@
 import streamlit as st
 import pandas as pd
 
-def main():
-    st.title("Data Collection Form")
-
-    sex = st.radio("Sex", ["Female", "Male"])
-    age = st.number_input("Age", min_value=0)
-    hypertension = st.selectbox("Do you have hypertension?", [0, 1])
-    heart_disease = st.selectbox("Do you have heart disease?", [0, 1])
-    ever_married = st.selectbox("Have you ever been married?", [0, 1])
-    work_type = st.selectbox("What is your work type?", ["Never worked", "Children", "Government job", "Self-employed", "Private"])
-    residence_type = st.selectbox("What is your residence type?", ["Urban", "Rural"])
-    avg_glucose_level = st.number_input("Average Glucose Level", min_value=0.0)
-    bmi = st.number_input("BMI", min_value=0.0)
-    smoking_status = st.selectbox("What is your smoking status?", [0, 1])
-
-    submit_button = st.button("Submit")
-
-    if submit_button:
-        data = {
-            "sex": 1 if sex == "Male" else 0,
-            "age": age,
-            "hypertension": ["ever had", "never had"].index(hypertension),
-            "heart_disease": ["ever had", "never had"].index(heart_disease),
-            "ever_married": ["married","single"].index(ever_married),
-            "work_type": ["Never worked", "Children", "Government job", "Self-employed", "Private"].index(work_type),
-            "residence_type": ["Urban", "Rural"].index(residence_type),
-            "avg_glucose_level": avg_glucose_level,
-            "bmi": bmi,
-            "smoking_status": ["never smoked", "smokes"].index(smoking_status)
-        }
-
-        df = pd.DataFrame([data])
-        st.write("Submitted Data:")
-        st.write(df)
-
-        # Unpickle classifier
-        clf = joblib.load("stroke.pkl")
-
-        # Get prediction
-        prediction = clf.predict(df)[0]
-
-        # Output prediction
-        if prediction == 0:
-            st.text("No Stroke")
-        else:
-            st.text("Stroke")
-
-if __name__ == "__main__":
-    main()
+st.title("Data Collection Form")
+
+sex = st.radio("Sex", ["Female", "Male"])
+age = st.number_input("Age", min_value=0)
+hypertension = st.selectbox("Do you have hypertension?", [0, 1])
+heart_disease = st.selectbox("Do you have heart disease?", [0, 1])
+ever_married = st.selectbox("Have you ever been married?", [0, 1])
+work_type = st.selectbox("What is your work type?", ["Never worked", "Children", "Government job", "Self-employed", "Private"])
+residence_type = st.selectbox("What is your residence type?", ["Urban", "Rural"])
+avg_glucose_level = st.number_input("Average Glucose Level", min_value=0.0)
+bmi = st.number_input("BMI", min_value=0.0)
+smoking_status = st.selectbox("What is your smoking status?", [0, 1])
+
+submit_button = st.button("Submit")
+
+if submit_button:
+    data = {
+        "sex": 1 if sex == "Male" else 0,
+        "age": age,
+        "hypertension": ["ever had", "never had"].index(hypertension),
+        "heart_disease": ["ever had", "never had"].index(heart_disease),
+        "ever_married": ["married","single"].index(ever_married),
+        "work_type": ["Never worked", "Children", "Government job", "Self-employed", "Private"].index(work_type),
+        "residence_type": ["Urban", "Rural"].index(residence_type),
+        "avg_glucose_level": avg_glucose_level,
+        "bmi": bmi,
+        "smoking_status": ["never smoked", "smokes"].index(smoking_status)
+    }
+
+    df = pd.DataFrame([data])
+    st.write("Submitted Data:")
+    st.write(df)
+
+    # Unpickle classifier
+    clf = joblib.load("stroke.pkl")
+
+    # Get prediction
+    prediction = clf.predict(df)[0]
+
+    # Output prediction
+    if prediction == 0:
+        st.text("No Stroke")
+    else:
+        st.text("Stroke")