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# -*- coding: utf-8 -*-
"""Lab07_Deployment_on_HuggingFace_Spaces_backend.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/18LL9Kki70qRHvNJQFYMtTe4TwJRJ97x9
"""
import joblib
import pandas as pd
import streamlit as st
EDU_DICT = {"bachelor's degree": 1,
'some college': 2,
"master's degree": 3,
"associate's degree": 4,
'high school': 5,
'some high school': 6,
}
model = joblib.load('model.joblib')
unique_values = joblib.load('unique_values.joblib')
unique_gender = unique_values["gender"]
unique_race_ethnicity = unique_values["race/ethnicity"]
unique_level_of_education = unique_values["parental level of education"]
unique_lunch = unique_values["lunch"]
def main():
st.title("Students Performance Analysis")
with st.form("questionaire"):
gender = st.selectbox("gender", unique_gender)
race_ethnicity = st.selectbox("race/ethnicity", unique_race_ethnicity)
level_of_education = st.selectbox("parental level of education", unique_level_of_education)
lunch = st.selectbox("lunch", unique_lunch)
math_score = st.slider("math score", min_value=0, max_value=100)
reading_score = st.slider("reading score", min_value=17, max_value=100)
writing_score = st.slider("writing score", min_value=10, max_value=100)
clicked = st.form_submit_button("Predict Students Performance")
if clicked:
result= model.predict(pd.DataFrame({"gender": [gender],
"race/ethnicity": [race_ethnicity],
"parental level of education": [EDU_DICT[level_of_education]],
"lunch": [lunch],
"math score": [math_score],
"reading score": [reading_score],
"writing score": [writing_score]
}))
result = 'completed' if result[0] == 1 else 'none'
st.success('The predicted students performance is {}'.format(result))
if __name__=='__main__':
main() |