code: def data_df_from_bunch(data_bunch):
      try:
          feature_names = data_bunch.feature_names
      except AttributeError:
          feature_names = [
              "x%d" % i for i in range(data_bunch.data.shape[1])
          ]
      data = data_bunch.data
      if issparse(data):
          data = data.toarray()
      df = pd.DataFrame(data, columns=feature_names)
      try:
          df["target"] = data_bunch.target_names[data_bunch.target]
      except (TypeError, AttributeError):
          df["target"] = data_bunch.target
      return df
  
imports: import pandas
  from scipy.sparse import issparse
  from .preprocessing import clean
label_desc: Use image node_id 1 for calling a global function with example usage: data_df_from_bunch(data_bunch) and returns: df