REF: implement Manager.concat_vertical, concat_horizontal

pandas/core/internals/array_manager.py

@@ -3,6 +3,7 @@
 """
 from __future__ import annotations
 
+import itertools
 from typing import (
     TYPE_CHECKING,
     Any,
@@ -20,9 +21,13 @@
 )
 from pandas.util._validators import validate_bool_kwarg
 
-from pandas.core.dtypes.astype import astype_array_safe
+from pandas.core.dtypes.astype import (
+    astype_array,
+    astype_array_safe,
+)
 from pandas.core.dtypes.cast import (
     ensure_dtype_can_hold_na,
+    find_common_type,
     infer_dtype_from_scalar,
 )
 from pandas.core.dtypes.common import (
@@ -1136,6 +1141,30 @@ def as_array(
 
         return result
 
+    @classmethod
+    def concat_horizontal(cls, mgrs: list[Self], axes: list[Index]) -> Self:
+        """
+        Concatenate uniformly-indexed ArrayManagers horizontally.
+        """
+        # concatting along the columns -> combine reindexed arrays in a single manager
+        arrays = list(itertools.chain.from_iterable([mgr.arrays for mgr in mgrs]))
+        new_mgr = cls(arrays, [axes[1], axes[0]], verify_integrity=False)
+        return new_mgr
+
+    @classmethod
+    def concat_vertical(cls, mgrs: list[Self], axes: list[Index]) -> Self:
+        """
+        Concatenate uniformly-indexed ArrayManagers vertically.
+        """
+        # concatting along the rows -> concat the reindexed arrays
+        # TODO(ArrayManager) doesn't yet preserve the correct dtype
+        arrays = [
+            concat_arrays([mgrs[i].arrays[j] for i in range(len(mgrs))])
+            for j in range(len(mgrs[0].arrays))
+        ]
+        new_mgr = cls(arrays, [axes[1], axes[0]], verify_integrity=False)
+        return new_mgr
+
 
 class SingleArrayManager(BaseArrayManager, SingleDataManager):
     __slots__ = [
@@ -1354,3 +1383,59 @@ def to_array(self, dtype: DtypeObj) -> ArrayLike:
             arr = np.empty(self.n, dtype=dtype)
             arr.fill(fill_value)
             return ensure_wrapped_if_datetimelike(arr)
+
+
+def concat_arrays(to_concat: list) -> ArrayLike:
+    """
+    Alternative for concat_compat but specialized for use in the ArrayManager.
+
+    Differences: only deals with 1D arrays (no axis keyword), assumes
+    ensure_wrapped_if_datetimelike and does not skip empty arrays to determine
+    the dtype.
+    In addition ensures that all NullArrayProxies get replaced with actual
+    arrays.
+
+    Parameters
+    ----------
+    to_concat : list of arrays
+
+    Returns
+    -------
+    np.ndarray or ExtensionArray
+    """
+    # ignore the all-NA proxies to determine the resulting dtype
+    to_concat_no_proxy = [x for x in to_concat if not isinstance(x, NullArrayProxy)]
+
+    dtypes = {x.dtype for x in to_concat_no_proxy}
+    single_dtype = len(dtypes) == 1
+
+    if single_dtype:
+        target_dtype = to_concat_no_proxy[0].dtype
+    elif all(x.kind in "iub" and isinstance(x, np.dtype) for x in dtypes):
+        # GH#42092
+        target_dtype = np.find_common_type(list(dtypes), [])
+    else:
+        target_dtype = find_common_type([arr.dtype for arr in to_concat_no_proxy])
+
+    to_concat = [
+        arr.to_array(target_dtype)
+        if isinstance(arr, NullArrayProxy)
+        else astype_array(arr, target_dtype, copy=False)
+        for arr in to_concat
+    ]
+
+    if isinstance(to_concat[0], ExtensionArray):
+        cls = type(to_concat[0])
+        return cls._concat_same_type(to_concat)
+
+    result = np.concatenate(to_concat)
+
+    # TODO decide on exact behaviour (we shouldn't do this only for empty result)
+    # see https://github.com/pandas-dev/pandas/issues/39817
+    if len(result) == 0:
+        # all empties -> check for bool to not coerce to float
+        kinds = {obj.dtype.kind for obj in to_concat_no_proxy}
+        if len(kinds) != 1:
+            if "b" in kinds:
+                result = result.astype(object)
+    return result

pandas/core/internals/concat.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-import itertools
 from typing import (
     TYPE_CHECKING,
     Sequence,
@@ -20,7 +19,6 @@
 from pandas.util._decorators import cache_readonly
 from pandas.util._exceptions import find_stack_level
 
-from pandas.core.dtypes.astype import astype_array
 from pandas.core.dtypes.cast import (
     ensure_dtype_can_hold_na,
     find_common_type,
@@ -38,13 +36,9 @@
     isna_all,
 )
 
-from pandas.core.arrays import ExtensionArray
 from pandas.core.arrays.sparse import SparseDtype
 from pandas.core.construction import ensure_wrapped_if_datetimelike
-from pandas.core.internals.array_manager import (
-    ArrayManager,
-    NullArrayProxy,
-)
+from pandas.core.internals.array_manager import ArrayManager
 from pandas.core.internals.blocks import (
     ensure_block_shape,
     new_block_2d,
@@ -59,7 +53,7 @@
         ArrayLike,
         AxisInt,
         DtypeObj,
-        Manager,
+        Manager2D,
         Shape,
     )
 
@@ -71,8 +65,8 @@
 
 
 def _concatenate_array_managers(
-    mgrs: list[Manager], axes: list[Index], concat_axis: AxisInt
-) -> Manager:
+    mgrs: list[ArrayManager], axes: list[Index], concat_axis: AxisInt
+) -> Manager2D:
     """
     Concatenate array managers into one.
 
@@ -87,80 +81,16 @@ def _concatenate_array_managers(
     ArrayManager
     """
     if concat_axis == 1:
-        # concatting along the rows -> concat the reindexed arrays
-        # TODO(ArrayManager) doesn't yet preserve the correct dtype
-        arrays = [
-            concat_arrays([mgrs[i].arrays[j] for i in range(len(mgrs))])
-            for j in range(len(mgrs[0].arrays))
-        ]
+        return mgrs[0].concat_vertical(mgrs, axes)
     else:
         # concatting along the columns -> combine reindexed arrays in a single manager
         assert concat_axis == 0
-        arrays = list(itertools.chain.from_iterable([mgr.arrays for mgr in mgrs]))
-
-    new_mgr = ArrayManager(arrays, [axes[1], axes[0]], verify_integrity=False)
-    return new_mgr
-
-
-def concat_arrays(to_concat: list) -> ArrayLike:
-    """
-    Alternative for concat_compat but specialized for use in the ArrayManager.
-
-    Differences: only deals with 1D arrays (no axis keyword), assumes
-    ensure_wrapped_if_datetimelike and does not skip empty arrays to determine
-    the dtype.
-    In addition ensures that all NullArrayProxies get replaced with actual
-    arrays.
-
-    Parameters
-    ----------
-    to_concat : list of arrays
-
-    Returns
-    -------
-    np.ndarray or ExtensionArray
-    """
-    # ignore the all-NA proxies to determine the resulting dtype
-    to_concat_no_proxy = [x for x in to_concat if not isinstance(x, NullArrayProxy)]
-
-    dtypes = {x.dtype for x in to_concat_no_proxy}
-    single_dtype = len(dtypes) == 1
-
-    if single_dtype:
-        target_dtype = to_concat_no_proxy[0].dtype
-    elif all(x.kind in "iub" and isinstance(x, np.dtype) for x in dtypes):
-        # GH#42092
-        target_dtype = np.find_common_type(list(dtypes), [])
-    else:
-        target_dtype = find_common_type([arr.dtype for arr in to_concat_no_proxy])
-
-    to_concat = [
-        arr.to_array(target_dtype)
-        if isinstance(arr, NullArrayProxy)
-        else astype_array(arr, target_dtype, copy=False)
-        for arr in to_concat
-    ]
-
-    if isinstance(to_concat[0], ExtensionArray):
-        cls = type(to_concat[0])
-        return cls._concat_same_type(to_concat)
-
-    result = np.concatenate(to_concat)
-
-    # TODO decide on exact behaviour (we shouldn't do this only for empty result)
-    # see https://github.com/pandas-dev/pandas/issues/39817
-    if len(result) == 0:
-        # all empties -> check for bool to not coerce to float
-        kinds = {obj.dtype.kind for obj in to_concat_no_proxy}
-        if len(kinds) != 1:
-            if "b" in kinds:
-                result = result.astype(object)
-    return result
+        return mgrs[0].concat_horizontal(mgrs, axes)
 
 
 def concatenate_managers(
     mgrs_indexers, axes: list[Index], concat_axis: AxisInt, copy: bool
-) -> Manager:
+) -> Manager2D:
     """
     Concatenate block managers into one.
 
@@ -196,7 +126,7 @@ def concatenate_managers(
 
     if concat_axis == 0:
         mgrs = _maybe_reindex_columns_na_proxy(axes, mgrs_indexers, needs_copy)
-        return _concat_managers_axis0(mgrs, axes)
+        return mgrs[0].concat_horizontal(mgrs, axes)
 
     if len(mgrs_indexers) > 0 and mgrs_indexers[0][0].nblocks > 0:
         first_dtype = mgrs_indexers[0][0].blocks[0].dtype
@@ -266,29 +196,6 @@ def concatenate_managers(
     return BlockManager(tuple(blocks), axes)
 
 
-def _concat_managers_axis0(mgrs: list[BlockManager], axes: list[Index]) -> BlockManager:
-    """
-    concat_managers specialized to concat_axis=0, with reindexing already
-    having been done in _maybe_reindex_columns_na_proxy.
-    """
-
-    offset = 0
-    blocks: list[Block] = []
-    for i, mgr in enumerate(mgrs):
-        for blk in mgr.blocks:
-            # We need to do getitem_block here otherwise we would be altering
-            #  blk.mgr_locs in place, which would render it invalid. This is only
-            #  relevant in the copy=False case.
-            nb = blk.getitem_block(slice(None))
-            nb._mgr_locs = nb._mgr_locs.add(offset)
-            blocks.append(nb)
-
-        offset += len(mgr.items)
-
-    result = BlockManager(tuple(blocks), axes)
-    return result
-
-
 def _maybe_reindex_columns_na_proxy(
     axes: list[Index],
     mgrs_indexers: list[tuple[BlockManager, dict[int, np.ndarray]]],

pandas/core/internals/managers.py

@@ -1841,6 +1841,37 @@ def _consolidate_inplace(self) -> None:
             self._known_consolidated = True
             self._rebuild_blknos_and_blklocs()
 
+    # ----------------------------------------------------------------
+    # Concatenation
+
+    @classmethod
+    def concat_horizontal(cls, mgrs: list[Self], axes: list[Index]) -> Self:
+        """
+        Concatenate uniformly-indexed BlockManagers horizontally.
+        """
+        offset = 0
+        blocks: list[Block] = []
+        for i, mgr in enumerate(mgrs):
+            for blk in mgr.blocks:
+                # We need to do getitem_block here otherwise we would be altering
+                #  blk.mgr_locs in place, which would render it invalid. This is only
+                #  relevant in the copy=False case.
+                nb = blk.getitem_block(slice(None))
+                nb._mgr_locs = nb._mgr_locs.add(offset)
+                blocks.append(nb)
+
+            offset += len(mgr.items)
+
+        new_mgr = cls(tuple(blocks), axes)
+        return new_mgr
+
+    @classmethod
+    def concat_vertical(cls, mgrs: list[Self], axes: list[Index]) -> Self:
+        """
+        Concatenate uniformly-indexed BlockManagers vertically.
+        """
+        raise NotImplementedError("This logic lives (for now) in internals.concat")
+
 
 class SingleBlockManager(BaseBlockManager, SingleDataManager):
     """manage a single block with"""