text: import os
  from datetime import datetime
  
  import pandas as pd
  
  from srdatasets.datasets.dataset import Dataset
  from srdatasets.datasets.utils import download_url, extract
  
  
  class FourSquare(Dataset):
  
      __url__ = "http://www-public.imtbs-tsp.eu/~zhang_da/pub/dataset_tsmc2014.zip"
  
      __corefile__ = {
          "NYC": os.path.join("dataset_tsmc2014", "dataset_TSMC2014_NYC.txt"),
          "Tokyo": os.path.join("dataset_tsmc2014", "dataset_TSMC2014_TKY.txt"),
      }
  
      def download(self):
          download_url(self.__url__, self.rawpath)
          extract(self.rawpath, self.rootdir)
  
      def transform(self, city):
          """ city: `NYC` or `Tokyo`
          """
          df = pd.read_csv(
              self.rootdir.joinpath(self.__corefile__[city]),
              sep="\t",
              header=None,
              names=[
                  "user_id",
                  "venue_id",
                  "venue_category_id",
                  "venue_category_name",
                  "latitude",
                  "longtitude",
                  "timezone_offset",
                  "utc_time",
              ],
              usecols=[0, 1, 7],
              converters={
                  "utc_time": lambda x: int(
                      datetime.strptime(x, "%a %b %d %H:%M:%S %z %Y").timestamp()
                  )
              },
          )
          df = df.rename(columns={"venue_id": "item_id", "utc_time": "timestamp"})
          return df
  