code: def has_ndarray_int_columns(features, X):
      """Checks if numeric feature columns exist in ndarray"""
      _, ncols = X.shape
      if not all(
          d.isdigit() for d in features if isinstance(d, str)
      ) or not isinstance(X, np.ndarray):
          return False
      ndarray_columns = np.arange(0, ncols)
      feature_cols = np.unique([int(d) for d in features])
      return all(np.in1d(feature_cols, ndarray_columns))
  
file_path: yellowbrick/yellowbrick/utils/helpers.py
imports: import re
  import inspect
  import sklearn
  import numpy
  from sklearn.pipeline import Pipeline
  from sklearn.utils.validation import check_is_fitted
  from yellowbrick.utils.types import is_estimator
  from yellowbrick.exceptions import YellowbrickTypeError
  from yellowbrick.contrib.wrapper import ContribEstimator
label_desc: Use image node_id 4 for calling a global function with example usage: has_ndarray_int_columns(features, X) and returns: all, False