app.py

import streamlit as st
 
import numpy as np
import pandas as pd
import joblib

model = joblib.load('divar.sav')
st.title('what is the price of your house??')
Area = st.number_input("Input Area", 0,10000)
Room = st.selectbox("Room? ", [1,2,3,4,5,6,7,8,9,10])
Parking = st.selectbox("Parking??", ['1','0'])
Warehouse = st.selectbox("Warehouse??", ['1','0'])
Elevator = st.selectbox("Elevator??", ['1','0'])
address1 = st.text_input("Adress??",'Abazar' )
features=pd.read_csv('featues.csv')
address=pd.read_csv('address.csv')
new_row = {'Area': Area , 'Room': Room, 'Parking': Parking,'Warehouse':Warehouse,'Elevator':Elevator}
features.loc[len(features)] = new_row
address[address1]=True
merged = pd.concat([features, address],axis=1)
#final_df = merged.style.hide()
merged.to_csv('merged.csv',index=False)
test = pd.read_csv('merged.csv')
def predict():
    prediction = model.predict(test)
    final=prediction/1000000000
    st.success('The price of your house is: ' + str(final) + ' Billion tomans')
trigger = st.button('Predict', on_click=predict)