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app.py

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+import streamlit as st
+import pandas as pd
+import joblib
+
+address_list = ['Abazar',
+ 'Abbasabad',
+ 'Absard',
+ 'Abuzar',
+ 'Afsarieh',
+ 'Ahang',
+ 'Air force',
+ 'Ajudaniye',
+ 'Alborz Complex',
+ 'Aliabad South',
+ 'Amir Bahador',
+ 'Amirabad',
+ 'Amirieh',
+ 'Andisheh',
+ 'Aqdasieh',
+ 'Araj',
+ 'Argentina',
+ 'Atabak',
+ 'Azadshahr',
+ 'Azarbaijan',
+ 'Azari',
+ 'Baghestan',
+ 'Bahar',
+ 'Baqershahr',
+ 'Beryanak',
+ 'Boloorsazi',
+ 'Central Janatabad',
+ 'Chahardangeh',
+ 'Chardangeh',
+ 'Chardivari',
+ 'Chidz',
+ 'Damavand',
+ 'Darabad',
+ 'Darakeh',
+ 'Darband',
+ 'Daryan No',
+ 'Dehkade Olampic',
+ 'Dezashib',
+ 'Dolatabad',
+ 'Dorous',
+ 'East Ferdows Boulevard',
+ 'East Pars',
+ 'Ekbatan',
+ 'Ekhtiarieh',
+ 'Elahieh',
+ 'Elm-o-Sanat',
+ 'Enghelab',
+ 'Eram',
+ 'Eskandari',
+ 'Fallah',
+ 'Farmanieh',
+ 'Fatemi',
+ 'Feiz Garden',
+ 'Firoozkooh',
+ 'Firoozkooh Kuhsar',
+ 'Gandhi',
+ 'Garden of Saba',
+ 'Gheitarieh',
+ 'Ghiyamdasht',
+ 'Ghoba',
+ 'Gholhak',
+ 'Gisha',
+ 'Golestan',
+ 'Haft Tir',
+ 'Hakimiyeh',
+ 'Hashemi',
+ 'Hassan Abad',
+ 'Hekmat',
+ 'Heravi',
+ 'Heshmatieh',
+ 'Hor Square',
+ 'Islamshahr',
+ 'Islamshahr Elahieh',
+ 'Javadiyeh',
+ 'Jeyhoon',
+ 'Jordan',
+ 'Kahrizak',
+ 'Kamranieh',
+ 'Karimkhan',
+ 'Karoon',
+ 'Kazemabad',
+ 'Keshavarz Boulevard',
+ 'Khademabad Garden',
+ 'Khavaran',
+ 'Komeil',
+ 'Koohsar',
+ 'Kook',
+ 'Lavasan',
+ 'Lavizan',
+ 'Mahallati',
+ 'Mahmoudieh',
+ 'Majidieh',
+ 'Malard',
+ 'Marzdaran',
+ 'Mehrabad',
+ 'Mehrabad River River',
+ 'Mehran',
+ 'Mirdamad',
+ 'Mirza Shirazi',
+ 'Moniriyeh',
+ 'Narmak',
+ 'Nasim Shahr',
+ 'Nawab',
+ 'Naziabad',
+ 'Nezamabad',
+ 'Niavaran',
+ 'North Program Organization',
+ 'Northern Chitgar',
+ 'Northern Janatabad',
+ 'Northern Suhrawardi',
+ 'Northren Jamalzadeh',
+ 'Ostad Moein',
+ 'Ozgol',
+ 'Pakdasht',
+ 'Pakdasht KhatunAbad',
+ 'Parand',
+ 'Parastar',
+ 'Pardis',
+ 'Pasdaran',
+ 'Persian Gulf Martyrs Lake',
+ 'Pirouzi',
+ 'Pishva',
+ 'Punak',
+ 'Qalandari',
+ 'Qarchak',
+ 'Qasr-od-Dasht',
+ 'Qazvin Imamzadeh Hassan',
+ 'Railway',
+ 'Ray',
+ 'Ray - Montazeri',
+ 'Ray - Pilgosh',
+ 'Razi',
+ 'Republic',
+ 'Robat Karim',
+ 'Rudhen',
+ 'Saadat Abad',
+ 'SabaShahr',
+ 'Sabalan',
+ 'Sadeghieh',
+ 'Safadasht',
+ 'Salehabad',
+ 'Salsabil',
+ 'Sattarkhan',
+ 'Seyed Khandan',
+ 'Shadabad',
+ 'Shahedshahr',
+ 'Shahr-e-Ziba',
+ 'ShahrAra',
+ 'Shahrake Apadana',
+ 'Shahrake Azadi',
+ 'Shahrake Gharb',
+ 'Shahrake Madaen',
+ 'Shahrake Qods',
+ 'Shahrake Quds',
+ 'Shahrake Shahid Bagheri',
+ 'Shahrakeh Naft',
+ 'Shahran',
+ 'Shahryar',
+ 'Shams Abad',
+ 'Shoosh',
+ 'Si Metri Ji',
+ 'Sohanak',
+ 'Southern Chitgar',
+ 'Southern Janatabad',
+ 'Southern Program Organization',
+ 'Southern Suhrawardi',
+ 'Tajrish',
+ 'Tarasht',
+ 'Taslihat',
+ 'Tehran Now',
+ 'Tehransar',
+ 'Telecommunication',
+ 'Tenant',
+ 'Thirteen November',
+ 'Vahidieh',
+ 'Vahidiyeh',
+ 'Valiasr',
+ 'Vanak',
+ 'Varamin - Beheshti',
+ 'Velenjak',
+ 'Villa',
+ 'Water Organization',
+ 'Waterfall',
+ 'West Ferdows Boulevard',
+ 'West Pars',
+ 'Yaftabad',
+ 'Yakhchiabad',
+ 'Yousef Abad',
+ 'Zafar',
+ 'Zaferanieh',
+ 'Zargandeh',
+ 'Zibadasht']
+
+model = joblib.load('house_model.joblib')
+st.title('Tehran House Price in 1400 :house_buildings:')
+area = st.number_input('Input House Area', 45,1000)
+room = st.slider("Choose Room",0,10)
+parking = st.selectbox("Parking", options=[0, 1], format_func=lambda x: "Yes" if x else "No")
+warehouse = st.selectbox("Warehouse", options=[0, 1], format_func=lambda x: "Yes" if x else "No")
+elevator = st.selectbox("Elevator", options=[0, 1], format_func=lambda x: "Yes" if x else "No")
+address = st.selectbox("Select Address", address_list)
+
+if st.button("Predict Price"):
+    user_data = pd.DataFrame({
+        'Area': [area],
+        'Room': [room],
+        'Parking': [parking],
+        'Warehouse': [warehouse],
+        'Elevator': [elevator]
+    })
+
+    for col in address_list:
+        user_data[col] = 0
+    user_data[address] = 1
+
+    prediction = model.predict(user_data)[0]
+
+    st.write(f"### Predicted Price: {prediction:,.0f} TMN")

house_model.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2ffd609778307fa6858b78db2fd44f8af0fd869c2684992954bd823572a2fcc7
+size 5918

requirements.txt

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+joblib==1.3.2