code: def _transform_dbscan(
      self, df: pd.DataFrame, ydf, kind, verbose
  ) -> Tuple[
      Union[pd.DataFrame, None],
      pd.DataFrame,
      pd.DataFrame,
      pd.DataFrame,
  ]:
      res = self.bind()
      if hasattr(res, "_dbscan_params"):
          # Assume that we are transforming to last fit of dbscan
          cols = res._dbscan_params["cols"]
          umap = res._dbscan_params["fit_umap_embedding"]
          target = res._dbscan_params["target"]
  
          dbscan = (
              res._node_dbscan if kind == "nodes" else res._edge_dbscan
          )
          # print('DBSCAN TYPE IN TRANSFORM', type(dbscan))
  
          emb = None
          if umap and cols is None:
              emb, X, y = res.transform_umap(
                  df, ydf, kind=kind, return_graph=False
              )
          else:
              X, y = res.transform(
                  df, ydf, kind=kind, return_graph=False
              )
          XX = X
          if target:
              XX = y
          if cols is not None:
              XX = get_matrix_by_column_parts(XX, cols)
  
          if umap:
              X_ = emb
          else:
              X_ = XX
  
          if res.engine_dbscan == "cuml":
              print(
                  "Transform DBSCAN not yet supported for engine_dbscan=`cuml`, use engine=`umap_learn`, `pandas` or `sklearn` instead"
              )
              return emb, X, y, df
  
          X_, emb = make_safe_gpu_dataframes(X_, emb, "pandas")
  
          labels = dbscan_predict(X_, dbscan)  # type: ignore
          # print('after dbscan predict', type(labels))
          if umap and cols is None:
              df = df.assign(_dbscan=labels, x=emb.x, y=emb.y)  # type: ignore
          else:
              df = df.assign(_dbscan=labels)
  
          if verbose:
              print(
                  f"Transformed DBSCAN: {len(df[DBSCAN].unique())} clusters"
              )
  
          return emb, X, y, df  # type: ignore
      else:
          raise Exception(
              "No dbscan model found. Please run `g.dbscan()` first"
          )
  
imports: import logging
  import pandas
  import numpy
  from typing import Any, List, Union, TYPE_CHECKING, Tuple, Optional
  from typing_extensions import Literal
  from collections import Counter
  from graphistry.Plottable import Plottable
  from graphistry.constants import CUML, UMAP_LEARN, DBSCAN
  from graphistry.features import ModelDict
  from graphistry.feature_utils import get_matrix_by_column_parts
label_desc: Use image node_id 4 for calling the ClusterMixin obj's underlying member method code with example usage: obj._transform_dbscan(df, ydf, kind, verbose) and returns: emb,  X,  y,  df, emb,  X,  y,  df