app.py

import streamlit as st 
import joblib
import pandas as pd
#st.title('Placement Prediction app')
# st.markdown("""
# <style>
# .title {
# font-size: 50px;
# font-weight: bold;
# color: #4CAF50;
# text-align: center;
# font-family: 'Courier New', Courier, monospace;
# }
# </style>
# """, unsafe_allow_html=True)


# st.title('Placement Prediction App')
# st.subheader('Predicting student placement outcomes using machine learning')
# st.markdown('This app uses historical data to predict whether a student will be placed in a company based on their profile.')

try:
 model = joblib.load('model_campus')
 st.success("Model loaded successfully!")
except Exception as e:
 st.error(f"Error loading model: {e}")
 st.stop()
# model = joblib.load(open('/Users/nishthapandey/Desktop/PlacementPrediction/model_campus_placement_rf.joblib','rb'))

def predict_placement(data):
 # Preprocess the data
 new_data = pd.DataFrame(data, index[0])

 # Make prediction
 prediction = model.predict(new_data)[0]
 prob = model.predict_proba(new_data)[0][1]

 return prediction, prob

def main():
 st.header('Placement Prediciton App')

 gender = st.radio('Gender', ['Male', 'Female'])
 ssc_p = st.number_input('Secondary School Percentage', min_value=0.0, max_value=100.0, value=50.0, step=0.1)
 ssc_b = st.radio('Board of Education (SSC)', ['Central', 'Others'])
 hsc_p = st.number_input('Higher Secondary Percentage', min_value=0.0, max_value=100.0, value=50.0, step=0.1)
 hsc_b = st.radio('Board of Education (HSC)', ['Central', 'Others'])
 degree_p = st.number_input('UG Percentage', min_value=0.0, max_value=100.0, value=50.0, step=0.1)
 branch = st.selectbox('Branch of Study', ['CSE', 'ECE/EN', 'Others'])
 workex = st.radio('Work Experience', ['Yes', 'No'])
 certifications = st.number_input('Number of Certifications', min_value=0, max_value=10, value=0)
 etest_p = st.number_input('Employability Percentage', min_value=0.0, max_value=100.0, value=50.0, step=0.1)
 backlogs = st.number_input('Number of Backlogs', min_value=0, max_value=10, value=0)
 
 if st.button('predict'):
 new_data = {
 'gender': 0 if gender == "Male" else 1,
 'ssc_p': ssc_p,
 'ssc_b': 1 if ssc_b == "Central" else 0,
 'hsc_p': hsc_p,
 'hsc_b': 1 if hsc_b == "Central" else 0,
 'degree_p': degree_p,
 'Branch': 2 if branch == "ECE/EN" else 1 if branch == "CSE" else 0,
 'Workex': 1 if workex == "Yes" else 0,
 'Certifications': certifications,
 'etest_p': etest_p,
 'Backlogs': backlogs,
 }

 prediction, probability = predict_placement(new_data)
 st.write(f'Percentage of getting placed: {probability*100:.2f}%')


if __name__=='__main__':
 main()