|
from dateutil.parser import parse |
|
import geopy.distance |
|
import json |
|
from datetime import datetime |
|
|
|
RPI_dict = {'2Q2022': 163.9, '1Q2022': 159.5, '4Q2021': 155.7, '3Q2021': 150.6, '2Q2021': 146.4, '1Q2021': 142.2, '4Q2020': 138.1, '3Q2020': 133.9, '2Q2020': 131.9, '1Q2020': 131.5, '4Q2019': 131.5, '3Q2019': 130.9, '2Q2019': 130.8, '1Q2019': 131, '4Q2018': 131.4, '3Q2018': 131.6, '2Q2018': 131.7, '1Q2018': 131.6, '4Q2017': 132.6, '3Q2017': 132.8, '2Q2017': 133.7, '1Q2017': 133.9} |
|
|
|
def is_date(string, fuzzy=False): |
|
""" |
|
Return whether the string can be interpreted as a date. |
|
|
|
:param string: str, string to check for date |
|
:param fuzzy: bool, ignore unknown tokens in string if True |
|
""" |
|
try: |
|
parse(string, fuzzy=fuzzy) |
|
return True |
|
|
|
except ValueError: |
|
return False |
|
|
|
def distance_to_mrt(lat, long, location): |
|
coord_mrt = tuple(location) |
|
coord_house = (lat, long) |
|
distance_km = geopy.distance.distance(coord_mrt, coord_house).km |
|
|
|
return distance_km |
|
|
|
|
|
def nearest_mrt(lat, long, mrt_name, mrt_loc): |
|
count = 0 |
|
distance_km = 100 |
|
for mrt in mrt_name: |
|
distance_cal = distance_to_mrt(lat, long, mrt_loc[count]) |
|
if distance_cal < distance_km: |
|
nearest_mr = mrt |
|
distance_km = distance_cal |
|
count += 1 |
|
return distance_km, nearest_mr |
|
|
|
def price_adj(price, qrtr_transaction): |
|
RPI = float(RPI_dict[qrtr_transaction]) |
|
resale_price_adj = price*(133.9/RPI) |
|
return resale_price_adj |
|
|
