REF: enforce annotation in maybe_downcast_to_dtype (pandas-dev#40982)

Author: jbrockmendel

pandas/core/dtypes/cast.py

@@ -4,7 +4,6 @@
 
 from __future__ import annotations
 
-from contextlib import suppress
 from datetime import (
     date,
     datetime,
@@ -29,7 +28,6 @@
     NaT,
     OutOfBoundsDatetime,
     OutOfBoundsTimedelta,
-    Period,
     Timedelta,
     Timestamp,
     conversion,
@@ -87,7 +85,6 @@
     PeriodDtype,
 )
 from pandas.core.dtypes.generic import (
-    ABCDataFrame,
     ABCExtensionArray,
     ABCSeries,
 )
@@ -249,9 +246,6 @@ def maybe_downcast_to_dtype(result: ArrayLike, dtype: str | np.dtype) -> ArrayLi
     try to cast to the specified dtype (e.g. convert back to bool/int
     or could be an astype of float64->float32
     """
-    if isinstance(result, ABCDataFrame):
-        # see test_pivot_table_doctest_case
-        return result
     do_round = False
 
     if isinstance(dtype, str):
@@ -278,15 +272,9 @@ def maybe_downcast_to_dtype(result: ArrayLike, dtype: str | np.dtype) -> ArrayLi
 
         dtype = np.dtype(dtype)
 
-    elif dtype.type is Period:
-        from pandas.core.arrays import PeriodArray
-
-        with suppress(TypeError):
-            # e.g. TypeError: int() argument must be a string, a
-            #  bytes-like object or a number, not 'Period
-
-            # error: "dtype[Any]" has no attribute "freq"
-            return PeriodArray(result, freq=dtype.freq)  # type: ignore[attr-defined]
+    if not isinstance(dtype, np.dtype):
+        # enforce our signature annotation
+        raise TypeError(dtype)  # pragma: no cover
 
     converted = maybe_downcast_numeric(result, dtype, do_round)
     if converted is not result:
@@ -295,15 +283,7 @@ def maybe_downcast_to_dtype(result: ArrayLike, dtype: str | np.dtype) -> ArrayLi
     # a datetimelike
     # GH12821, iNaT is cast to float
     if dtype.kind in ["M", "m"] and result.dtype.kind in ["i", "f"]:
-        if isinstance(dtype, DatetimeTZDtype):
-            # convert to datetime and change timezone
-            i8values = result.astype("i8", copy=False)
-            cls = dtype.construct_array_type()
-            # equiv: DatetimeArray(i8values).tz_localize("UTC").tz_convert(dtype.tz)
-            dt64values = i8values.view("M8[ns]")
-            result = cls._simple_new(dt64values, dtype=dtype)
-        else:
-            result = result.astype(dtype)
+        result = result.astype(dtype)
 
     return result
 

pandas/core/reshape/pivot.py

@@ -64,7 +64,6 @@ def pivot_table(
     dropna=True,
     margins_name="All",
     observed=False,
-    sort=True,
 ) -> DataFrame:
     index = _convert_by(index)
     columns = _convert_by(columns)
@@ -84,7 +83,6 @@ def pivot_table(
                 dropna=dropna,
                 margins_name=margins_name,
                 observed=observed,
-                sort=sort,
             )
             pieces.append(_table)
             keys.append(getattr(func, "__name__", func))
@@ -103,7 +101,6 @@ def pivot_table(
         dropna,
         margins_name,
         observed,
-        sort,
     )
     return table.__finalize__(data, method="pivot_table")
 
@@ -119,7 +116,6 @@ def __internal_pivot_table(
     dropna: bool,
     margins_name: str,
     observed: bool,
-    sort: bool,
 ) -> DataFrame:
     """
     Helper of :func:`pandas.pivot_table` for any non-list ``aggfunc``.
@@ -161,7 +157,7 @@ def __internal_pivot_table(
                 pass
         values = list(values)
 
-    grouped = data.groupby(keys, observed=observed, sort=sort)
+    grouped = data.groupby(keys, observed=observed)
     agged = grouped.agg(aggfunc)
     if dropna and isinstance(agged, ABCDataFrame) and len(agged.columns):
         agged = agged.dropna(how="all")
@@ -184,6 +180,7 @@ def __internal_pivot_table(
                     # TODO: why does test_pivot_table_doctest_case fail if
                     # we don't do this apparently-unnecessary setitem?
                     agged[v] = agged[v]
+                    pass
                 else:
                     agged[v] = maybe_downcast_to_dtype(agged[v], data[v].dtype)