app.py

import streamlit as st
import pickle
import pandas as pd
import numpy as np
# import requests
data =pd.read_csv('clean_data.csv')
pipe=pickle.load(open("LinearModle_.pkl",'rb'))


location =st.selectbox('Select the location',data['location'].unique())
bhk =st.number_input("Enter the BHK ",step=1)
bath =st.number_input("Enter the number of Bathrooms",step=1)
sqft =st.number_input("Enter the the area of flat")


def predict():
    input= pd.DataFrame([[location,sqft,bath,bhk]],columns=['location','total_sqft','bath','bhk'])
    prediction = pipe.predict(input)[0] * 1e5 # Its converted into lakhs
    print(prediction)
    # print(type(location),type(bhk),type(bath),type(sqft))
    return np.abs(np.round(prediction,2))

if(st.button('Check_the_price')):
    st.write("The approximate price of this property is: ")
    st.write(predict()," In Indian Ruppee")