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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") |