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import pandas as pd
# new_data = pd.DataFrame({
# 'gender':0,
# 'ssc_p':55.0,
# 'ssc_b':0,
# 'hsc_p':75.0,
# 'hsc_b':0,
# 'hsc_s':1,
# 'degree_p':65.0,
# 'degree_t':2,
# 'workex':0,
# 'etest_p':55.0,
# 'specialisation':1,
# 'mba_p':58.8,
# },index=[0])
import joblib
model = joblib.load('model_campus_placement')
# p=model.predict(new_data)
# prob=model.predict_proba(new_data)
# if p[0]==1:
# print('Placed')
# print(f"You will be placed with probability of {prob[0][1]:.2f}")
# else:
# print("Not-placed")
import streamlit as st
st.title('Campus-Placement-Prediction-Using-Machine-Learning')
gender=st.number_input('gender',value=0)
ssc_p=st.number_input('ssc_p',value=0)
ssc_b=st.number_input('ssc_b',value=0)
hsc_p=st.number_input('hsc_p',value=0)
hsc_b=st.number_input('hsc_b',value=0)
hsc_s=st.number_input('hsc_s',value=0)
degree_p=st.number_input('degree_p',value=0)
degree_t=st.number_input('degree_t',value=0)
workex=st.number_input('workex',value=0)
etest_p=st.number_input('etest_p',value=0)
specialisation=st.number_input('specialisation',value=0)
mba_p=st.number_input('mba_p',value=0)
if st.button('submit'):
new_data = pd.DataFrame({
'gender':gender,
'ssc_p':ssc_p,
'ssc_b':ssc_b,
'hsc_p':hsc_p,
'hsc_b':hsc_b,
'hsc_s':hsc_s,
'degree_p':degree_p,
'degree_t':degree_t,
'workex':workex,
'etest_p':etest_p,
'specialisation':specialisation,
'mba_p':mba_p,
},index=[0])
p=model.predict(new_data)
prob=model.predict_proba(new_data)
if p[0]==1:
# print('Placed')
st.write('Placed')
# print(f"You will be placed with probability of {prob[0][1]:.2f}")
st.write(f"You will be placed with probability of {prob[0][1]:.2f}")
else:
# print("Not-placed")
st.write('Not-placed')
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