import datasets from enum import Enum from dataclasses import dataclass from typing import List import pandas as pd logger = datasets.logging.get_logger(__name__) _CITATION = """\ @dataset{gyodi_kristof_2021_4446043, author = {Gyódi, Kristóf and Nawaro, Łukasz}, title = {{Determinants of Airbnb prices in European cities: A spatial econometrics approach (Supplementary Material)}}, month = jan, year = 2021, note = {{This research was supported by National Science Centre, Poland: Project number 2017/27/N/HS4/00951}}, publisher = {Zenodo}, doi = {10.5281/zenodo.4446043}, url = {https://doi.org/10.5281/zenodo.4446043} }""" _DESCRIPTION = """ """ _CITIES = [ "Amsterdam", "Athens", "Barcelona", "Berlin", "Budapest", "Lisbon", "London", "Paris", "Rome", "Vienna" ] _BASE_URL = "https://zenodo.org/record/4446043/files/" _URL_TEMPLATE = _BASE_URL + "{city}_{day_type}.csv" class DayType(str, Enum): WEEKDAYS = "weekdays" WEEKENDS = "weekends" @dataclass class AirbnbFile: """A file from the Airbnb dataset.""" city: str day_type: DayType @property def url(self) -> str: return _URL_TEMPLATE.format(city=self.city.lower(), day_type=self.day_type.value) class AirbnbConfig(datasets.BuilderConfig): """BuilderConfig for Airbnb.""" def __init__(self, files: List[AirbnbFile], **kwargs): """BuilderConfig for Airbnb. Args: **kwargs: keyword arguments forwarded to super. """ super(AirbnbConfig, self).__init__(**kwargs) self.files = files _WEEKDAY_FILES = [AirbnbFile(city=city, day_type=DayType.WEEKDAYS) for city in _CITIES] _WEEKEND_FILES = [AirbnbFile(city=city, day_type=DayType.WEEKENDS) for city in _CITIES] class Airbnb(datasets.GeneratorBasedBuilder): """""" BUILDER_CONFIGS = [ AirbnbConfig( name=DayType.WEEKDAYS.value, files=_WEEKDAY_FILES, ), AirbnbConfig( name=DayType.WEEKENDS.value, files=_WEEKEND_FILES, ), AirbnbConfig( name="all", files=_WEEKDAY_FILES + _WEEKEND_FILES, ), ] def _info(self): features = datasets.Features( { "_id": datasets.Value("string"), "city": datasets.Value("string"), "realSum": datasets.Value(dtype="float64"), "room_type": datasets.Value(dtype="string"), "room_shared": datasets.Value(dtype="bool"), "room_private": datasets.Value(dtype="bool"), "person_capacity": datasets.Value(dtype="float64"), "host_is_superhost": datasets.Value(dtype="bool"), "multi": datasets.Value(dtype="int64"), "biz": datasets.Value(dtype="int64"), "cleanliness_rating": datasets.Value(dtype="float64"), "guest_satisfaction_overall": datasets.Value(dtype="float64"), "bedrooms": datasets.Value(dtype="int64"), "dist": datasets.Value(dtype="float64"), "metro_dist": datasets.Value(dtype="float64"), "attr_index": datasets.Value(dtype="float64"), "attr_index_norm": datasets.Value(dtype="float64"), "rest_index": datasets.Value(dtype="float64"), "rest_index_norm": datasets.Value(dtype="float64"), "lng": datasets.Value(dtype="float64"), "lat": datasets.Value(dtype="float64") }) if self.config.name == "all": features["day_type"] = datasets.Value(dtype="string") return datasets.DatasetInfo( description=_DESCRIPTION, features=features, supervised_keys=None, homepage="https://zenodo.org/record/4446043#.ZEV8d-zMI-R", citation=_CITATION ) def _split_generators(self, dl_manager): config_files: List[AirbnbFile] = self.config.files urls = [file.url for file in config_files] downloaded_files = dl_manager.download_and_extract(urls) return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"paths": downloaded_files}) ] def _generate_examples(self, paths: List[str]): _id = 0 config_files: List[AirbnbFile] = self.config.files include_day_type = self.config.name == "all" for file, path in zip(config_files, paths): logger.info("generating examples from = %s", path) df = pd.read_csv(path, index_col=0, header=0) for row in df.itertuples(): city = file.city data = { "_id": _id, "city": city, "realSum": row.realSum, "room_type": row.room_type, "room_shared": row.room_shared, "room_private": row.room_private, "person_capacity": row.person_capacity, "host_is_superhost": row.host_is_superhost, "multi": row.multi, "biz": row.biz, "cleanliness_rating": row.cleanliness_rating, "guest_satisfaction_overall": row.guest_satisfaction_overall, "bedrooms": row.bedrooms, "dist": row.dist, "metro_dist": row.metro_dist, "attr_index": row.attr_index, "attr_index_norm": row.attr_index_norm, "rest_index": row.rest_index, "rest_index_norm": row.rest_index_norm, "lng": row.lng, "lat": row.lat } if include_day_type: data["day_type"] = file.day_type.value yield _id, data _id += 1