code: def indexable(*iterables):
      """Make arrays indexable for cross-validation.
      Checks consistent length, passes through None, and ensures that everything
      can be indexed by converting sparse matrices to csr and converting
      non-interable objects to arrays.
      Parameters
      ----------
      *iterables : lists, dataframes, arrays, sparse matrices
          List of objects to ensure sliceability.
      """
      result = []
      for X in iterables:
          if sp.issparse(X):
              result.append(X.tocsr())
          elif hasattr(X, "__getitem__") or hasattr(X, "iloc"):
              result.append(X)
          elif X is None:
              result.append(X)
          else:
              result.append(np.array(X))
      check_consistent_length(*result)
      return result
  
imports: import warnings
  import numbers
  import numpy
  import scipy.sparse
  from ..None import six
  from ...utils.exceptions import NotFittedError, NonBLASDotWarning, DataConversionWarning
label_desc: Use image node_id 8 for calling a global function with example usage: indexable() and returns: result