class_docstr: A data frame class, with only the methods required by the interchange
  protocol defined.
  Instances of this (private) class are returned from
  ``pd.DataFrame.__dataframe__`` as objects with the methods and
  attributes defined on this class.
class_docstr_tok: ["A","data","frame","class",",","with","only","the","methods","required","by","the","interchange","protocol","defined",".","Instances","of","this","(","private",")","class","are","returned","from","``","pd.DataFrame.__dataframe__","``","as","objects","with","the","methods","and","attributes","defined","on","this","class","."]
docstr: Constructor - an instance of this (private) class is returned from
  `pd.DataFrame.__dataframe__`.
docstr_tok: ["Constructor","-","an","instance","of","this","(","private",")","class","is","returned","from","`","pd.DataFrame.__dataframe__","`","."]
code: def __init__(
      self,
      df: DataFrame,
      nan_as_null: bool = False,
      allow_copy: bool = True,
  ) -> None:
      """
      Constructor - an instance of this (private) class is returned from
      `pd.DataFrame.__dataframe__`.
      """
      self._df = df
      # ``nan_as_null`` is a keyword intended for the consumer to tell the
      # producer to overwrite null values in the data with ``NaN`` (or ``NaT``).
      # This currently has no effect; once support for nullable extension
      # dtypes is added, this value should be propagated to columns.
      self._nan_as_null = nan_as_null
      self._allow_copy = allow_copy
  
file_path: catboost/contrib/python/pandas/py3/pandas/core/interchange/dataframe.py
imports: from __future__ import annotations
  from collections import abc
  from typing import TYPE_CHECKING
  from pandas.core.interchange.column import PandasColumn
  from pandas.core.interchange.dataframe_protocol import DataFrame
label_desc: Use image node_id 1 to create a new PandasDataFrameXchg object from inherited base classes: DataFrameXchg with example: obj = PandasDataFrameXchg(df, nan_as_null, allow_copy)