From 4f4a4be29eb8cf37d537586de7c0e3e35b6b2cef Mon Sep 17 00:00:00 2001
From: Ralf Gommers <ralf.gommers@gmail.com>
Date: Tue, 29 Aug 2023 14:02:21 +0200
Subject: [PATCH] DEPR: remove use of `nan_as_null` from callers of
 `__dataframe__`

No one was using it yet and it seemed easier to clean it up
from libraries than to ask everyone to add support for it - see
https://github.com/data-apis/dataframe-api/issues/125.
---
 pandas/core/frame.py                 |  9 +++------
 pandas/core/interchange/dataframe.py | 20 +++++++-------------
 2 files changed, 10 insertions(+), 19 deletions(-)

diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 3a4e8fdd91362..9881232cfea99 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -893,8 +893,8 @@ def __dataframe__(
         Parameters
         ----------
         nan_as_null : bool, default False
-            Whether to tell the DataFrame to overwrite null values in the data
-            with ``NaN`` (or ``NaT``).
+            `nan_as_null` is DEPRECATED and has no effect. Please avoid using
+            it; it will be removed in a future release (after Aug 2024).
         allow_copy : bool, default True
             Whether to allow memory copying when exporting. If set to False
             it would cause non-zero-copy exports to fail.
@@ -909,9 +909,6 @@ def __dataframe__(
         Details on the interchange protocol:
         https://data-apis.org/dataframe-protocol/latest/index.html
 
-        `nan_as_null` currently has no effect; once support for nullable extension
-        dtypes is added, this value should be propagated to columns.
-
         Examples
         --------
         >>> df_not_necessarily_pandas = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
@@ -931,7 +928,7 @@ def __dataframe__(
 
         from pandas.core.interchange.dataframe import PandasDataFrameXchg
 
-        return PandasDataFrameXchg(self, nan_as_null, allow_copy)
+        return PandasDataFrameXchg(self, allow_copy=allow_copy)
 
     def __dataframe_consortium_standard__(
         self, *, api_version: str | None = None
diff --git a/pandas/core/interchange/dataframe.py b/pandas/core/interchange/dataframe.py
index 0ddceb6b8139b..28324872c15ac 100644
--- a/pandas/core/interchange/dataframe.py
+++ b/pandas/core/interchange/dataframe.py
@@ -27,25 +27,20 @@ class PandasDataFrameXchg(DataFrameXchg):
     attributes defined on this class.
     """
 
-    def __init__(
-        self, df: DataFrame, nan_as_null: bool = False, allow_copy: bool = True
-    ) -> None:
+    def __init__(self, df: DataFrame, 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
 
     def __dataframe__(
         self, nan_as_null: bool = False, allow_copy: bool = True
     ) -> PandasDataFrameXchg:
-        return PandasDataFrameXchg(self._df, nan_as_null, allow_copy)
+        # `nan_as_null` can be removed here once it's removed from
+        # Dataframe.__dataframe__
+        return PandasDataFrameXchg(self._df, allow_copy)
 
     @property
     def metadata(self) -> dict[str, Index]:
@@ -84,7 +79,7 @@ def select_columns(self, indices: Sequence[int]) -> PandasDataFrameXchg:
             indices = list(indices)
 
         return PandasDataFrameXchg(
-            self._df.iloc[:, indices], self._nan_as_null, self._allow_copy
+            self._df.iloc[:, indices], allow_copy=self._allow_copy
         )
 
     def select_columns_by_name(self, names: list[str]) -> PandasDataFrameXchg:  # type: ignore[override]  # noqa: E501
@@ -94,7 +89,7 @@ def select_columns_by_name(self, names: list[str]) -> PandasDataFrameXchg:  # ty
             names = list(names)
 
         return PandasDataFrameXchg(
-            self._df.loc[:, names], self._nan_as_null, self._allow_copy
+            self._df.loc[:, names], allow_copy=self._allow_copy
         )
 
     def get_chunks(self, n_chunks: int | None = None) -> Iterable[PandasDataFrameXchg]:
@@ -109,8 +104,7 @@ def get_chunks(self, n_chunks: int | None = None) -> Iterable[PandasDataFrameXch
             for start in range(0, step * n_chunks, step):
                 yield PandasDataFrameXchg(
                     self._df.iloc[start : start + step, :],
-                    self._nan_as_null,
-                    self._allow_copy,
+                    allow_copy=self._allow_copy,
                 )
         else:
             yield self