code: def load_spam(data_home=None, return_dataset=False):
      """
      Loads the email spam dataset that is weill suited to binary classification
      and threshold tasks. The dataset contains 4600 instances with 57 integer and
      real valued attributes and a discrete target.
  
      The Yellowbrick datasets are hosted online and when requested, the dataset
      is downloaded to your local computer for use. Note that if the dataset
      hasn't been downloaded before, an Internet connection is required. However,
      if the data is cached locally, no data will be downloaded. Yellowbrick
      checks the known signature of the dataset with the data downloaded to
      ensure the download completes successfully.
  
      Datasets are stored alongside the code, but the location can be specified
      with the ``data_home`` parameter or the ``$YELLOWBRICK_DATA`` envvar.
  
      Parameters
      ----------
      data_home : str, optional
          The path on disk where data is stored. If not passed in, it is looked
          up from ``$YELLOWBRICK_DATA`` or the default returned by ``get_data_home``.
  
      return_dataset : bool, default=False
          Return the raw dataset object instead of X and y numpy arrays to
          get access to alternative targets, extra features, content and meta.
  
      Returns
      -------
      X : array-like with shape (n_instances, n_features) if return_dataset=False
          A pandas DataFrame or numpy array describing the instance features.
  
      y : array-like with shape (n_instances,) if return_dataset=False
          A pandas Series or numpy array describing the target vector.
  
      dataset : Dataset instance if return_dataset=True
          The Yellowbrick Dataset object provides an interface to accessing the
          data in a variety of formats as well as associated metadata and content.
      """
      return _load_dataset("spam", data_home, return_dataset)
  
file_path: yellowbrick/yellowbrick/datasets/loaders.py
imports: import os
  import json
  from .base import Dataset, Corpus
label_desc: Use image node_id 11 for calling a global function with example usage: load_spam(data_home, return_dataset) and returns: _load_dataset