PC Estate Price Prediction API

API Reference

The PC Estate Price Prediction API is organized around REST. It is an aplication for prediction of estate prices in Poços de Caldas, a city from Brazil.

The basic url is:

https://estate-predict-pc.herokuapp.com/api/predictor

The parameters need to predict are:

• type, (string): the type of the estate. Can be APARTMENT, HOME, CONDOMINIUM or RESIDENTIAL_ALLOTMENT_LAND

• area, (real): in the case of APARTMENT, HOME and CONDOMINIUM types, this parameter will be the contructed area. On the other hand, if the type is RESIDENTIAL_ALLOTMENT_LAND, it will be the allotment area.

• n_bathrooms, (integer): number of bathrooms.

• n_bedrooms, (integer): number of bedrooms.

• n_suites, (integer): how many of the bedrooms are suites.

• n_parking_spaces, (integer): number of parking spaces.

• neighborhood, (string): the estate neighborhood.

For more accurated results, you can pass the following optional features if you have:

• iptu, (integer): annual estate tax.

• condo_fee, (real): monthly condominum fee.

• units_on_floor, (integer): number of units on the floor (for appartments).

• n_floors, (integer): number of floors in the building (for appartments). ‘

• resale, (integer): it must be 0 if the estate is new. In the other hand, it must be 1.

• buildings, (integer): number of buildings in the estate.

List of Valid Neighborhoods

We can see in the box below a list with the neighborhoods of Poços de Caldas:

Example of Usage in Python

import requests
url = "https://estate-predict-pc.herokuapp.com/api/predictor"
headers = {'Content-type': 'application/json', 'Accept': 'text/plain'}
params = {
    "area": 170,
    "n_bathrooms": 2,
    "n_bedrooms": 3,
    "n_parking_spaces": 2,
    "n_suites": 0,
    "neighborhood": "Jardim Europa",
    "type": "HOME",
    "condo_fee": 250,
    "iptu": 450
}
r = requests.post(url, data=json.dumps(params), headers=headers)
r.json()

Eduardo

Data Scientist and Physicist

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