class_docstr: Return the role and logical type of each column.
  
  Parameters
  ----------
  n_top_columns : int , optional
      amount of columns to show ordered by feature importance (date, index, label are first)
code: def __init__(self, n_top_columns: int = 10, **kwargs):
      super().__init__(**kwargs)
      self.n_top_columns = n_top_columns
  
file_path: deepchecks/deepchecks/tabular/checks/data_integrity/columns_info.py
imports: import pandas
  from deepchecks.core import CheckResult
  from deepchecks.tabular import Context, SingleDatasetCheck
  from deepchecks.tabular.utils.feature_importance import N_TOP_MESSAGE, column_importance_sorter_dict
label_desc: Use image node_id 1 to create a new ColumnsInfo object from inherited base classes: SingleDatasetCheck with example: obj = ColumnsInfo(n_top_columns)