code: def select_field(X, cols=None, single_dimension=False):
      """
      Select columns from a pandas DataFrame
  
      Args:
          X (pandas DataFrame): input data
          cols (array-like): list of columns to select
          single_dimension (bool): reduce data to
              one dimension if only one column
              is requested
      Returns:
          X (numpy array)
      """
      if cols is None:
          return X.values
      if len(cols) > 1:
          return X[cols].values
      if len(cols) == 1:
          if single_dimension:
              return X[cols[0]].values
          else:
              return X[cols].values
  
imports: import warnings
  import pandas
  import numpy
  from scipy import sparse
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.preprocessing import MultiLabelBinarizer, FunctionTransformer, LabelEncoder, normalize
  from sklearn.feature_extraction.text import HashingVectorizer
  from sklearn import feature_selection
label_desc: Use image node_id 1 for calling a global function with example usage: select_field(X, cols, single_dimension) and returns: X, X, X, X