update app.py

app.py

@@ -1,65 +1,65 @@
-import pickle
-import streamlit as st
-from streamlit_option_menu import option_menu
-
-#loading the saved data
-
-heart_disease_model = pickle.load(open("E:\jupyter notebook\heart disease prediction\heart_disease_model.sav",'rb'))
-
-st.title('Heart Disease Prediction using ML')
-
-col1, col2, col3 = st.columns(3)
-
-with col1:
-    age = st.text_input('Age')
-
-with col2:
-    sex = st.text_input('Sex')
-
-with col3:
-    cp = st.text_input('Chest Pain types')
-
-with col1:
-    trestbps = st.text_input('Resting Blood Pressure')
-
-with col2:
-    chol = st.text_input('Serum Cholestoral in mg/dl')
-
-with col3:
-    fbs = st.text_input('Fasting Blood Sugar > 120 mg/dl')
-
-with col1:
-    restecg = st.text_input('Resting Electrocardiographic results')
-
-with col2:
-    thalach = st.text_input('Maximum Heart Rate achieved')
-
-with col3:
-    exang = st.text_input('Exercise Induced Angina')
-
-with col1:
-    oldpeak = st.text_input('ST depression induced by exercise')
-
-with col2:
-    slope = st.text_input('Slope of the peak exercise ST segment')
-
-with col3:
-    ca = st.text_input('Major vessels colored by flourosopy')
-
-with col1:
-    thal = st.text_input('thal: 0 = normal; 1 = fixed defect; 2 = reversable defect')
-
-    # code for Prediction
-    heart_diagnosis = ''
-
-    # creating a button for Prediction
-
-    if st.button('Heart Disease Test Result'):
-        heart_prediction = heart_disease_model.predict([[
-            'age', 'sex',' cp', 'trestbps', 'chol', 'fbs', 'restecg', 'thalach', 'exang', 'oldpeak', 'slope', 'ca', 'thal']])
-        if (heart_prediction[0] == 1):
-            heart_diagnosis = 'The person is having heart disease'
-        else:
-            heart_diagnosis = 'The person does not have any heart disease'
-
-    st.success(heart_diagnosis)
+import pickle
+import streamlit as st
+from streamlit_option_menu import option_menu
+
+#loading the saved data
+
+heart_disease_model = pickle.load(open("heart_disease_model.sav",'rb'))
+
+st.title('Heart Disease Prediction using ML')
+
+col1, col2, col3 = st.columns(3)
+
+with col1:
+    age = st.text_input('Age')
+
+with col2:
+    sex = st.text_input('Sex')
+
+with col3:
+    cp = st.text_input('Chest Pain types')
+
+with col1:
+    trestbps = st.text_input('Resting Blood Pressure')
+
+with col2:
+    chol = st.text_input('Serum Cholestoral in mg/dl')
+
+with col3:
+    fbs = st.text_input('Fasting Blood Sugar > 120 mg/dl')
+
+with col1:
+    restecg = st.text_input('Resting Electrocardiographic results')
+
+with col2:
+    thalach = st.text_input('Maximum Heart Rate achieved')
+
+with col3:
+    exang = st.text_input('Exercise Induced Angina')
+
+with col1:
+    oldpeak = st.text_input('ST depression induced by exercise')
+
+with col2:
+    slope = st.text_input('Slope of the peak exercise ST segment')
+
+with col3:
+    ca = st.text_input('Major vessels colored by flourosopy')
+
+with col1:
+    thal = st.text_input('thal: 0 = normal; 1 = fixed defect; 2 = reversable defect')
+
+    # code for Prediction
+    heart_diagnosis = ''
+
+    # creating a button for Prediction
+
+    if st.button('Heart Disease Test Result'):
+        heart_prediction = heart_disease_model.predict([[
+            'age', 'sex',' cp', 'trestbps', 'chol', 'fbs', 'restecg', 'thalach', 'exang', 'oldpeak', 'slope', 'ca', 'thal']])
+        if (heart_prediction[0] == 1):
+            heart_diagnosis = 'The person is having heart disease'
+        else:
+            heart_diagnosis = 'The person does not have any heart disease'
+
+    st.success(heart_diagnosis)