Merge branch 'main' into depr-fastpath

Author: jbrockmendel

asv_bench/benchmarks/dtypes.py

@@ -24,7 +24,7 @@
 
 
 class Dtypes:
-    params = _dtypes + list(map(lambda dt: dt.name, _dtypes))
+    params = _dtypes + [dt.name for dt in _dtypes]
     param_names = ["dtype"]
 
     def time_pandas_dtype(self, dtype):

doc/source/whatsnew/v2.0.2.rst

@@ -13,6 +13,7 @@ including other versions of pandas.
 
 Fixed regressions
 ~~~~~~~~~~~~~~~~~
+- Fixed regression in :meth:`DataFrame.loc` losing :class:`MultiIndex` name when enlarging object (:issue:`53053`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/_typing.py

@@ -155,7 +155,7 @@
 
 RandomState = Union[
     int,
-    ArrayLike,
+    np.ndarray,
     np.random.Generator,
     np.random.BitGenerator,
     np.random.RandomState,

pandas/core/array_algos/putmask.py

@@ -136,7 +136,7 @@ def setitem_datetimelike_compat(values: np.ndarray, num_set: int, other):
     other : Any
     """
     if values.dtype == object:
-        dtype, _ = infer_dtype_from(other, pandas_dtype=True)
+        dtype, _ = infer_dtype_from(other)
 
         if isinstance(dtype, np.dtype) and dtype.kind in "mM":
             # https://github.com/numpy/numpy/issues/12550

pandas/core/arrays/arrow/array.py

@@ -18,22 +18,6 @@
 import numpy as np
 
 from pandas._libs import lib
-from pandas._typing import (
-    ArrayLike,
-    AxisInt,
-    Dtype,
-    FillnaOptions,
-    Iterator,
-    NpDtype,
-    PositionalIndexer,
-    Scalar,
-    Self,
-    SortKind,
-    TakeIndexer,
-    TimeAmbiguous,
-    TimeNonexistent,
-    npt,
-)
 from pandas.compat import (
     pa_version_under7p0,
     pa_version_under8p0,
@@ -140,8 +124,22 @@ def floordiv_compat(
 
 if TYPE_CHECKING:
     from pandas._typing import (
+        ArrayLike,
+        AxisInt,
+        Dtype,
+        FillnaOptions,
+        Iterator,
+        NpDtype,
         NumpySorter,
         NumpyValueArrayLike,
+        PositionalIndexer,
+        Scalar,
+        Self,
+        SortKind,
+        TakeIndexer,
+        TimeAmbiguous,
+        TimeNonexistent,
+        npt,
     )
 
     from pandas import Series
@@ -805,8 +803,9 @@ def fillna(
             fallback_performancewarning()
             return super().fillna(value=value, method=method, limit=limit)
 
-        if is_array_like(value):
-            value = cast(ArrayLike, value)
+        if isinstance(value, (np.ndarray, ExtensionArray)):
+            # Similar to check_value_size, but we do not mask here since we may
+            #  end up passing it to the super() method.
             if len(value) != len(self):
                 raise ValueError(
                     f"Length of 'value' does not match. Got ({len(value)}) "

pandas/core/arrays/base.py

@@ -38,7 +38,7 @@
     validate_insert_loc,
 )
 
-from pandas.core.dtypes.cast import maybe_cast_to_extension_array
+from pandas.core.dtypes.cast import maybe_cast_pointwise_result
 from pandas.core.dtypes.common import (
     is_list_like,
     is_scalar,
@@ -1957,7 +1957,7 @@ def _maybe_convert(arr):
                     # https://github.com/pandas-dev/pandas/issues/22850
                     # We catch all regular exceptions here, and fall back
                     # to an ndarray.
-                    res = maybe_cast_to_extension_array(type(self), arr)
+                    res = maybe_cast_pointwise_result(arr, self.dtype, same_dtype=False)
                     if not isinstance(res, type(self)):
                         # exception raised in _from_sequence; ensure we have ndarray
                         res = np.asarray(arr)

pandas/core/arrays/masked.py

@@ -75,7 +75,11 @@
 from pandas.core.array_algos.quantile import quantile_with_mask
 from pandas.core.arraylike import OpsMixin
 from pandas.core.arrays.base import ExtensionArray
-from pandas.core.construction import ensure_wrapped_if_datetimelike
+from pandas.core.construction import (
+    array as pd_array,
+    ensure_wrapped_if_datetimelike,
+    extract_array,
+)
 from pandas.core.indexers import check_array_indexer
 from pandas.core.ops import invalid_comparison
 
@@ -645,20 +649,8 @@ def _arith_method(self, other, op):
             and len(other) == len(self)
         ):
             # Try inferring masked dtype instead of casting to object
-            inferred_dtype = lib.infer_dtype(other, skipna=True)
-            if inferred_dtype == "integer":
-                from pandas.core.arrays import IntegerArray
-
-                other = IntegerArray._from_sequence(other)
-            elif inferred_dtype in ["floating", "mixed-integer-float"]:
-                from pandas.core.arrays import FloatingArray
-
-                other = FloatingArray._from_sequence(other)
-
-            elif inferred_dtype in ["boolean"]:
-                from pandas.core.arrays import BooleanArray
-
-                other = BooleanArray._from_sequence(other)
+            other = pd_array(other)
+            other = extract_array(other, extract_numpy=True)
 
         if isinstance(other, BaseMaskedArray):
             other, omask = other._data, other._mask

pandas/core/common.py

@@ -33,11 +33,9 @@
 
 from pandas.core.dtypes.cast import construct_1d_object_array_from_listlike
 from pandas.core.dtypes.common import (
-    is_array_like,
     is_bool_dtype,
     is_integer,
 )
-from pandas.core.dtypes.dtypes import ExtensionDtype
 from pandas.core.dtypes.generic import (
     ABCExtensionArray,
     ABCIndex,
@@ -120,9 +118,7 @@ def is_bool_indexer(key: Any) -> bool:
     check_array_indexer : Check that `key` is a valid array to index,
         and convert to an ndarray.
     """
-    if isinstance(key, (ABCSeries, np.ndarray, ABCIndex)) or (
-        is_array_like(key) and isinstance(key.dtype, ExtensionDtype)
-    ):
+    if isinstance(key, (ABCSeries, np.ndarray, ABCIndex, ABCExtensionArray)):
         if key.dtype == np.object_:
             key_array = np.asarray(key)
 
@@ -420,7 +416,7 @@ def random_state(state: np.random.Generator) -> np.random.Generator:
 
 @overload
 def random_state(
-    state: int | ArrayLike | np.random.BitGenerator | np.random.RandomState | None,
+    state: int | np.ndarray | np.random.BitGenerator | np.random.RandomState | None,
 ) -> np.random.RandomState:
     ...
 
@@ -445,24 +441,8 @@ def random_state(state: RandomState | None = None):
     np.random.RandomState or np.random.Generator. If state is None, returns np.random
 
     """
-    if (
-        is_integer(state)
-        or is_array_like(state)
-        or isinstance(state, np.random.BitGenerator)
-    ):
-        # error: Argument 1 to "RandomState" has incompatible type "Optional[Union[int,
-        # Union[ExtensionArray, ndarray[Any, Any]], Generator, RandomState]]"; expected
-        # "Union[None, Union[Union[_SupportsArray[dtype[Union[bool_, integer[Any]]]],
-        # Sequence[_SupportsArray[dtype[Union[bool_, integer[Any]]]]],
-        # Sequence[Sequence[_SupportsArray[dtype[Union[bool_, integer[Any]]]]]],
-        # Sequence[Sequence[Sequence[_SupportsArray[dtype[Union[bool_,
-        # integer[Any]]]]]]],
-        # Sequence[Sequence[Sequence[Sequence[_SupportsArray[dtype[Union[bool_,
-        # integer[Any]]]]]]]]], Union[bool, int, Sequence[Union[bool, int]],
-        # Sequence[Sequence[Union[bool, int]]], Sequence[Sequence[Sequence[Union[bool,
-        # int]]]], Sequence[Sequence[Sequence[Sequence[Union[bool, int]]]]]]],
-        # BitGenerator]"
-        return np.random.RandomState(state)  # type: ignore[arg-type]
+    if is_integer(state) or isinstance(state, (np.ndarray, np.random.BitGenerator)):
+        return np.random.RandomState(state)
     elif isinstance(state, np.random.RandomState):
         return state
     elif isinstance(state, np.random.Generator):

pandas/core/computation/expr.py

@@ -192,7 +192,7 @@ def _filter_nodes(superclass, all_nodes=_all_nodes):
     return frozenset(node_names)
 
 
-_all_node_names = frozenset(map(lambda x: x.__name__, _all_nodes))
+_all_node_names = frozenset(x.__name__ for x in _all_nodes)
 _mod_nodes = _filter_nodes(ast.mod)
 _stmt_nodes = _filter_nodes(ast.stmt)
 _expr_nodes = _filter_nodes(ast.expr)