class_docstr: Data from the Kaggle Recruit Restaurants challenge.
  
  The goal is to predict the number of visitors in each of 829 Japanese restaurants over a priod
  of roughly 16 weeks. The data is ordered by date and then by restaurant ID.
  
  References
  ----------
  [^1]: [Recruit Restaurant Visitor Forecasting](https://www.kaggle.com/c/recruit-restaurant-visitor-forecasting)
code: def _iter(self):
      return stream.iter_csv(
          self.path,
          target="visitors",
          converters={
              "latitude": float,
              "longitude": float,
              "visitors": int,
              "is_holiday": ast.literal_eval,
          },
          parse_dates={"date": "%Y-%m-%d"},
      )
  
file_path: river/river/datasets/restaurants.py
imports: from __future__ import annotations
  import ast
  from river import stream
  from .None import base
label_desc: Use image node_id 2 for calling the Restaurants obj's underlying member method code with example usage: obj._iter() and returns: stream