docstr: ```
  Checks and transforms label columns in DataFrame. DataFrame is modified in place
  Args:
    label_columns(list): list of columns storing labels
    is_regression(bool): If True, task is regression and integer targets are treated as numeric dependent variable.
                         IF False, task is classification and integer targets are treated as class IDs.
  ```
code: def __init__(self, label_columns=[], is_regression=False):
      """
      ```
      Checks and transforms label columns in DataFrame. DataFrame is modified in place
      Args:
        label_columns(list): list of columns storing labels
        is_regression(bool): If True, task is regression and integer targets are treated as numeric dependent variable.
                             IF False, task is classification and integer targets are treated as class IDs.
      ```
      """
      self.is_regression = is_regression
      if isinstance(label_columns, str):
          label_columns = [label_columns]
      self.label_columns = label_columns
      if not label_columns:
          raise ValueError("label_columns is required")
      self.label_columns = (
          [self.label_columns]
          if isinstance(self.label_columns, str)
          else self.label_columns
      )
      # class_names = label_columns if len(label_columns) > 1 else []
      super().__init__(class_names=[])
  
imports: from .imports import *
  from subprocess import Popen
label_desc: Use image node_id 1 to create a new YTransformDataFrame object from inherited base classes: YTransform with example: obj = YTransformDataFrame(label_columns, is_regression)