class_docstr: Base class for bandit datasets.
  
  Parameters
  ----------
  n_features
      Number of features in the dataset.
  n_samples
      Number of samples in the dataset.
  n_classes
      Number of classes in the dataset, only applies to classification datasets.
  n_outputs
      Number of outputs the target is made of, only applies to multi-output datasets.
  sparse
      Whether the dataset is sparse or not.
code: def _repr_content(self):
      return {**super()._repr_content, "Arms": f"{len(self.arms):,d}"}
  
file_path: river/river/bandit/datasets/base.py
imports: from __future__ import annotations
  import abc
  from river import bandit, datasets
label_desc: Use image node_id 3 for calling the BanditDataset obj's underlying member method code with example usage: obj._repr_content() and returns: dict