code: def _fit(self, model, variable):
      if variable.variable not in model.variables:
          raise Exception("Variable is not a column of explainer")
      is_numeric = is_numeric_dtype(
          model.explainer.data[variable.variable]
      )
      if is_numeric and variable.levels is None:
          self.plot_component = "LinearShapleyDependence"
      else:
          self.plot_component = "CategoricalShapleyDependence"
      resource = self.arena.resource_manager.get_resource(
          "DatasetShapleyValues", {"model": model}, cache=self.use_cache
      )
      try:
          data, progress, is_done = resource.get_result()
          if data.get("result") is None:
              resource.wait_for_update()
              data, progress, is_done = resource.get_result()
      except Exception as e:
          self.set_message(str(e))
          return
      self.is_done = is_done
      self.progress = progress
      result = data.get("result")
      result = result[result["variable_name"] == variable.variable]
      stats = (
          result.groupby(["variable_value", "row"])
          .agg({"contribution": ["mean", "min", "max"]})
          .contribution
      )
      if self.plot_component == "LinearShapleyDependence":
          stats = stats.sort_index()
      transform_index = (
          float
          if self.plot_component == "LinearShapleyDependence"
          else str
      )
      self.data = {
          "x": [transform_index(x[0]) for x in stats.index],
          "mean": stats["mean"].values.tolist(),
          "min": stats["min"].values.tolist(),
          "max": stats["max"].values.tolist(),
          "variable": variable.variable,
      }
  
imports: from pandas.api.types import is_numeric_dtype
  from .._plot_container import PlotContainer
label_desc: Use image node_id 1 for calling the ShapleyValuesDependenceContainer obj's underlying member method code with example usage: obj._fit(model, variable) without return types