Upload app.py

app.py

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+import streamlit as st
+import pandas as pd
+import joblib
+
+model = joblib.load('model.pkl')
+st.title("🤯 Student Result Predictor")
+
+# take the input 
+gender = st.selectbox('Gender', ['Female','Male'])
+ethinic = st.selectbox('ethinic',['Group A','Group B','Group C','Group D', 'Group E'])
+parent_education = st.selectbox('parent education',["bachelor's degree","Associate's Degree","some college","high school","master's degree","some high school"])
+lunch = st.selectbox('Lunch', ['standard', 'free/reduced'])
+test_preparation = st.selectbox('Test Preparation', ['Completed','None'])
+math_score = st.number_input('Math Score',0, 100)
+Reading_score = st.number_input('Reading Score',0, 100)
+Writing_score = st.number_input('Writing Score',0, 100)
+
+# ethinic case
+group_A = group_B = group_C = group_D = group_E = 0
+if ethinic == 'Group B':
+    group_B = 1
+elif ethinic == 'Group C':
+    group_C = 1
+elif ethinic == 'Group D':
+    group_D = 1
+else:
+    group_E = 1
+
+# parent education case,
+associate = bachelor = highschool = master = some_college = some_school = 0
+if parent_education == "bachelor's degree":
+    bachelor = 1
+elif parent_education == "some college":
+    some_college = 1
+elif parent_education == "high school":
+    highschool = 1
+elif parent_education == "master's degree":
+    master = 1
+elif parent_education == "associate's degree":
+    associate = 1
+else:
+    some_school = 1
+
+# gender case
+if gender == 'male':
+    gender = 1
+else:
+    gender = 0
+
+# lunch case
+if lunch == 'standard':
+    lunch = 1
+else:
+    lunch = 0
+
+# test Preparation
+if test_preparation == 'None':
+    test_preparation = 1
+else:
+    test_preparation = 0
+
+
+input_data = pd.DataFrame({
+    'math score':[math_score],
+    'reading score':[Reading_score],
+    'writing score':[Writing_score],
+    'group_A':[group_A],
+    'group_B':[group_B],
+    'group_C':[group_C],
+    'group_D':[group_D],
+    'group_E':[group_E],
+    'associate':[associate],
+    'bachelor':[bachelor],
+    'high_school':[highschool],
+    'master':[master],
+    'some_college':[some_college],
+    'some_school':[some_school],
+    'gender':[gender],
+    'lunch_standard':[lunch],
+    'preparation':[test_preparation]
+})
+
+
+# predict output
+if st.button("Predict"):
+    prediction = model.predict(input_data)[0]
+    st.success("🥳 Pass" if prediction == 1 else "⛔ Fail,Try Hard")