DEPR: downcast keyword

doc/source/whatsnew/v2.1.0.rst

@@ -255,6 +255,7 @@ Deprecations
 - Deprecated making the functions in a list of functions given to :meth:`DataFrame.agg` attempt to operate on each element in the :class:`DataFrame` and only operate on the columns of the :class:`DataFrame` if the elementwise operations failed. To keep the current behavior, use :meth:`DataFrame.transform` instead. (:issue:`53325`)
 - Deprecated passing a :class:`DataFrame` to :meth:`DataFrame.from_records`, use :meth:`DataFrame.set_index` or :meth:`DataFrame.drop` instead (:issue:`51353`)
 - Deprecated silently dropping unrecognized timezones when parsing strings to datetimes (:issue:`18702`)
+- Deprecated the "downcast" keyword in :meth:`Series.interpolate`, :meth:`DataFrame.interpolate`, :meth:`Series.fillna`, :meth:`DataFrame.fillna`, :meth:`Series.ffill`, :meth:`DataFrame.ffill`, :meth:`Series.bfill`, :meth:`DataFrame.bfill` (:issue:`40988`)
 - Deprecated the ``axis`` keyword in :meth:`DataFrame.ewm`, :meth:`Series.ewm`, :meth:`DataFrame.rolling`, :meth:`Series.rolling`, :meth:`DataFrame.expanding`, :meth:`Series.expanding` (:issue:`51778`)
 - Deprecated the ``axis`` keyword in :meth:`DataFrame.resample`, :meth:`Series.resample` (:issue:`51778`)
 - Deprecated the behavior of :func:`concat` with both ``len(keys) != len(objs)``, in a future version this will raise instead of truncating to the shorter of the two sequences (:issue:`43485`)
@@ -292,7 +293,6 @@ Deprecations
 - Deprecated :meth:`Series.first` and :meth:`DataFrame.first` (please create a mask and filter using ``.loc`` instead) (:issue:`45908`)
 - Deprecated :meth:`Series.interpolate` and :meth:`DataFrame.interpolate` for object-dtype (:issue:`53631`)
 - Deprecated :meth:`Series.last` and :meth:`DataFrame.last` (please create a mask and filter using ``.loc`` instead) (:issue:`53692`)
-- Deprecated allowing ``downcast`` keyword other than ``None``, ``False``, "infer", or a dict with these as values in :meth:`Series.fillna`, :meth:`DataFrame.fillna` (:issue:`40988`)
 - Deprecated allowing arbitrary ``fill_value`` in :class:`SparseDtype`, in a future version the ``fill_value`` will need to be compatible with the ``dtype.subtype``, either a scalar that can be held by that subtype or ``NaN`` for integer or bool subtypes (:issue:`23124`)
 - Deprecated behavior of :func:`assert_series_equal` and :func:`assert_frame_equal` considering NA-like values (e.g. ``NaN`` vs ``None`` as equivalent) (:issue:`52081`)
 - Deprecated bytes input to :func:`read_excel`. To read a file path, use a string or path-like object. (:issue:`53767`)

pandas/core/generic.py

@@ -6870,25 +6870,21 @@ def convert_dtypes(
     # ----------------------------------------------------------------------
     # Filling NA's
 
-    def _deprecate_downcast(self, downcast) -> None:
-        if isinstance(downcast, dict):
-            # GH#40988
-            for dc in downcast.values():
-                if dc is not None and dc is not False and dc != "infer":
-                    warnings.warn(
-                        "downcast entries other than None, False, and 'infer' "
-                        "are deprecated and will raise in a future version",
-                        FutureWarning,
-                        stacklevel=find_stack_level(),
-                    )
-        elif downcast is not None and downcast is not False and downcast != "infer":
-            # GH#40988
+    def _deprecate_downcast(self, downcast, method_name: str):
+        # GH#40988
+        if downcast is not lib.no_default:
             warnings.warn(
-                "downcast other than None, False, and 'infer' are deprecated "
-                "and will raise in a future version",
+                f"The 'downcast' keyword in {method_name} is deprecated and "
+                "will be removed in a future version. Use "
+                "res.infer_objects(copy=False) to infer non-object dtype, or "
+                "pd.to_numeric with the 'downcast' keyword to downcast numeric "
+                "results.",
                 FutureWarning,
                 stacklevel=find_stack_level(),
             )
+        else:
+            downcast = None
+        return downcast
 
     @final
     def _pad_or_backfill(
@@ -6977,7 +6973,7 @@ def fillna(
         axis: Axis | None = None,
         inplace: bool_t = False,
         limit: int | None = None,
-        downcast: dict | None = None,
+        downcast: dict | None | lib.NoDefault = lib.no_default,
     ) -> Self | None:
         """
         Fill NA/NaN values using the specified method.
@@ -7096,7 +7092,8 @@ def fillna(
                 stacklevel=find_stack_level(),
             )
 
-        self._deprecate_downcast(downcast)
+        was_no_default = downcast is lib.no_default
+        downcast = self._deprecate_downcast(downcast, "fillna")
 
         # set the default here, so functions examining the signaure
         # can detect if something was set (e.g. in groupby) (GH9221)
@@ -7113,7 +7110,11 @@ def fillna(
                 axis=axis,
                 limit=limit,
                 inplace=inplace,
-                downcast=downcast,
+                # error: Argument "downcast" to "_fillna_with_method" of "NDFrame"
+                # has incompatible type "Union[Dict[Any, Any], None,
+                # Literal[_NoDefault.no_default]]"; expected
+                # "Optional[Dict[Any, Any]]"
+                downcast=downcast,  # type: ignore[arg-type]
             )
         else:
             if self.ndim == 1:
@@ -7157,13 +7158,20 @@ def fillna(
                     if k not in result:
                         continue
 
-                    # error: Item "None" of "Optional[Dict[Any, Any]]" has no
-                    # attribute "get"
-                    downcast_k = (
-                        downcast
-                        if not is_dict
-                        else downcast.get(k)  # type: ignore[union-attr]
-                    )
+                    if was_no_default:
+                        downcast_k = lib.no_default
+                    else:
+                        downcast_k = (
+                            # error: Incompatible types in assignment (expression
+                            # has type "Union[Dict[Any, Any], None,
+                            # Literal[_NoDefault.no_default], Any]", variable has
+                            # type "_NoDefault")
+                            downcast  # type: ignore[assignment]
+                            if not is_dict
+                            # error: Item "None" of "Optional[Dict[Any, Any]]" has
+                            # no attribute "get"
+                            else downcast.get(k)  # type: ignore[union-attr]
+                        )
 
                     res_k = result[k].fillna(v, limit=limit, downcast=downcast_k)
 
@@ -7236,7 +7244,7 @@ def ffill(
         axis: None | Axis = ...,
         inplace: Literal[False] = ...,
         limit: None | int = ...,
-        downcast: dict | None = ...,
+        downcast: dict | None | lib.NoDefault = ...,
     ) -> Self:
         ...
 
@@ -7247,7 +7255,7 @@ def ffill(
         axis: None | Axis = ...,
         inplace: Literal[True],
         limit: None | int = ...,
-        downcast: dict | None = ...,
+        downcast: dict | None | lib.NoDefault = ...,
     ) -> None:
         ...
 
@@ -7258,7 +7266,7 @@ def ffill(
         axis: None | Axis = ...,
         inplace: bool_t = ...,
         limit: None | int = ...,
-        downcast: dict | None = ...,
+        downcast: dict | None | lib.NoDefault = ...,
     ) -> Self | None:
         ...
 
@@ -7270,7 +7278,7 @@ def ffill(
         axis: None | Axis = None,
         inplace: bool_t = False,
         limit: None | int = None,
-        downcast: dict | None = None,
+        downcast: dict | None | lib.NoDefault = lib.no_default,
     ) -> Self | None:
         """
         Synonym for :meth:`DataFrame.fillna` with ``method='ffill'``.
@@ -7309,10 +7317,17 @@ def ffill(
         3   3.0
         dtype: float64
         """
-        self._deprecate_downcast(downcast)
+        downcast = self._deprecate_downcast(downcast, "ffill")
 
         return self._pad_or_backfill(
-            "ffill", axis=axis, inplace=inplace, limit=limit, downcast=downcast
+            "ffill",
+            axis=axis,
+            inplace=inplace,
+            limit=limit,
+            # error: Argument "downcast" to "_fillna_with_method" of "NDFrame"
+            # has incompatible type "Union[Dict[Any, Any], None,
+            # Literal[_NoDefault.no_default]]"; expected "Optional[Dict[Any, Any]]"
+            downcast=downcast,  # type: ignore[arg-type]
         )
 
     @final
@@ -7323,7 +7338,7 @@ def pad(
         axis: None | Axis = None,
         inplace: bool_t = False,
         limit: None | int = None,
-        downcast: dict | None = None,
+        downcast: dict | None | lib.NoDefault = lib.no_default,
     ) -> Self | None:
         """
         Synonym for :meth:`DataFrame.fillna` with ``method='ffill'``.
@@ -7352,7 +7367,7 @@ def bfill(
         axis: None | Axis = ...,
         inplace: Literal[False] = ...,
         limit: None | int = ...,
-        downcast: dict | None = ...,
+        downcast: dict | None | lib.NoDefault = ...,
     ) -> Self:
         ...
 
@@ -7363,7 +7378,7 @@ def bfill(
         axis: None | Axis = ...,
         inplace: Literal[True],
         limit: None | int = ...,
-        downcast: dict | None = ...,
+        downcast: dict | None | lib.NoDefault = ...,
     ) -> None:
         ...
 
@@ -7374,7 +7389,7 @@ def bfill(
         axis: None | Axis = ...,
         inplace: bool_t = ...,
         limit: None | int = ...,
-        downcast: dict | None = ...,
+        downcast: dict | None | lib.NoDefault = ...,
     ) -> Self | None:
         ...
 
@@ -7386,7 +7401,7 @@ def bfill(
         axis: None | Axis = None,
         inplace: bool_t = False,
         limit: None | int = None,
-        downcast: dict | None = None,
+        downcast: dict | None | lib.NoDefault = lib.no_default,
     ) -> Self | None:
         """
         Synonym for :meth:`DataFrame.fillna` with ``method='bfill'``.
@@ -7407,12 +7422,6 @@ def bfill(
         2    2.0
         3    2.0
         dtype: float64
-        >>> s.bfill(downcast='infer')
-        0    1
-        1    2
-        2    2
-        3    2
-        dtype: int64
         >>> s.bfill(limit=1)
         0    1.0
         1    NaN
@@ -7435,16 +7444,23 @@ def bfill(
         1   4.0   5.0
         2   4.0   7.0
         3   4.0   7.0
-        >>> df.bfill(downcast='infer', limit=1)
-              A	   B
-        0   1.0    5
-        1   NaN    5
-        2   4.0    7
-        3   4.0    7
-        """
-        self._deprecate_downcast(downcast)
+        >>> df.bfill(limit=1)
+              A     B
+        0   1.0   5.0
+        1   NaN   5.0
+        2   4.0   7.0
+        3   4.0   7.0
+        """
+        downcast = self._deprecate_downcast(downcast, "bfill")
         return self._pad_or_backfill(
-            "bfill", axis=axis, inplace=inplace, limit=limit, downcast=downcast
+            "bfill",
+            axis=axis,
+            inplace=inplace,
+            limit=limit,
+            # error: Argument "downcast" to "_fillna_with_method" of "NDFrame"
+            # has incompatible type "Union[Dict[Any, Any], None,
+            # Literal[_NoDefault.no_default]]"; expected "Optional[Dict[Any, Any]]"
+            downcast=downcast,  # type: ignore[arg-type]
         )
 
     @final
@@ -7455,7 +7471,7 @@ def backfill(
         axis: None | Axis = None,
         inplace: bool_t = False,
         limit: None | int = None,
-        downcast: dict | None = None,
+        downcast: dict | None | lib.NoDefault = lib.no_default,
     ) -> Self | None:
         """
         Synonym for :meth:`DataFrame.fillna` with ``method='bfill'``.
@@ -7780,7 +7796,7 @@ def interpolate(
         inplace: bool_t = False,
         limit_direction: Literal["forward", "backward", "both"] | None = None,
         limit_area: Literal["inside", "outside"] | None = None,
-        downcast: Literal["infer"] | None = None,
+        downcast: Literal["infer"] | None | lib.NoDefault = lib.no_default,
         **kwargs,
     ) -> Self | None:
         """
@@ -7851,6 +7867,9 @@ def interpolate(
 
         downcast : optional, 'infer' or None, defaults to None
             Downcast dtypes if possible.
+
+            .. deprecated:: 2.1.0
+
         ``**kwargs`` : optional
             Keyword arguments to pass on to the interpolating function.
 
@@ -7949,6 +7968,17 @@ def interpolate(
         3    16.0
         Name: d, dtype: float64
         """
+        if downcast is not lib.no_default:
+            # GH#40988
+            warnings.warn(
+                f"The 'downcast' keyword in {type(self).__name__}.interpolate "
+                "is deprecated and will be removed in a future version. "
+                "Call result.infer_objects(copy=False) on the result instead.",
+                FutureWarning,
+                stacklevel=find_stack_level(),
+            )
+        else:
+            downcast = None
         if downcast is not None and downcast != "infer":
             raise ValueError("downcast must be either None or 'infer'")
 

pandas/core/groupby/generic.py

@@ -868,7 +868,7 @@ def fillna(
         axis: Axis | None | lib.NoDefault = lib.no_default,
         inplace: bool = False,
         limit: int | None = None,
-        downcast: dict | None = None,
+        downcast: dict | None | lib.NoDefault = lib.no_default,
     ) -> Series | None:
         """
         Fill NA/NaN values using the specified method within groups.
@@ -912,6 +912,8 @@ def fillna(
             or the string 'infer' which will try to downcast to an appropriate
             equal type (e.g. float64 to int64 if possible).
 
+            .. deprecated:: 2.1.0
+
         Returns
         -------
         Series
@@ -2390,7 +2392,7 @@ def fillna(
         axis: Axis | None | lib.NoDefault = lib.no_default,
         inplace: bool = False,
         limit: int | None = None,
-        downcast=None,
+        downcast=lib.no_default,
     ) -> DataFrame | None:
         """
         Fill NA/NaN values using the specified method within groups.
@@ -2434,6 +2436,8 @@ def fillna(
             or the string 'infer' which will try to downcast to an appropriate
             equal type (e.g. float64 to int64 if possible).
 
+            .. deprecated:: 2.1.0
+
         Returns
         -------
         DataFrame

pandas/core/resample.py

@@ -844,7 +844,7 @@ def interpolate(
         inplace: bool = False,
         limit_direction: Literal["forward", "backward", "both"] = "forward",
         limit_area=None,
-        downcast=None,
+        downcast=lib.no_default,
         **kwargs,
     ):
         """
@@ -917,6 +917,9 @@ def interpolate(
 
         downcast : optional, 'infer' or None, defaults to None
             Downcast dtypes if possible.
+
+            .. deprecated::2.1.0
+
         ``**kwargs`` : optional
             Keyword arguments to pass on to the interpolating function.
 
@@ -1000,6 +1003,7 @@ def interpolate(
         Note that the series erroneously increases between two anchors
         ``07:00:00`` and ``07:00:02``.
         """
+        assert downcast is lib.no_default  # just checking coverage
         result = self._upsample("asfreq")
         return result.interpolate(
             method=method,