class_docstr: Room occupancy data.
  
  Dataset on detecting room occupancy based on several variables. The dataset contains
  temperature, humidity, light, and CO2 variables.
  
  The data is sampled at every 16 observations to reduce the length of the series.
  
  References
  ----------
  Candanedo, Luis M., and Véronique Feldheim. "Accurate occupancy detection of an office room from light, temperature, humidity and CO2 measurements using statistical learning models." Energy and Buildings 112 (2016): 28-39.
code: def __iter__(self):
      return stream.iter_csv(
          self.path,
          target=["V1", "V2", "V3", "V4"],
          converters={
              "V1": float,
              "V2": float,
              "V3": float,
              "V4": float,
          },
          parse_dates={"time": "%Y-%m-%d %H:%M:%S"},
      )
  
imports: from __future__ import annotations
  from river import datasets, stream
  from .base import ChangePointFileDataset
label_desc: Use image node_id 2 for calling the Occupancy obj's underlying member method code with example usage: obj.__iter__() and returns: stream