class_docstr: The `DictMapper` transformer maps the values of columns according to the input `mapper` dictionary, fall back to
  the `default` value if the key is not present in the dictionary.
  
  Parameters
  ----------
  mapper : dict[..., int]
      The dictionary containing the mapping of the values.
  default : int
      The value to fall back to if the value is not in the mapper.
  
  Attributes
  ----------
  n_features_in_ : int
      Number of features seen during `fit`.
  dim_ : int
      Deprecated, please use `n_features_in_` instead.
code: def dim_(self):
      warn(
          "Please use `n_features_in_` instead of `dim_`, `dim_` will be deprecated in future versions",
          DeprecationWarning,
      )
      return self.n_features_in_
  
file_path: scikit-lego/sklego/preprocessing/dictmapper.py
imports: from warnings import warn
  import numpy
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.utils import check_array
  from sklearn.utils.validation import check_is_fitted
label_desc: Use image node_id 4 for calling the DictMapper obj's underlying member method code with example usage: obj.dim_() and returns: self