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BUG/PERF: merge_asof with multiple "by" keys #55580
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Original file line number | Diff line number | Diff line change |
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@@ -9,7 +9,6 @@ | |
) | ||
import datetime | ||
from functools import partial | ||
import string | ||
from typing import ( | ||
TYPE_CHECKING, | ||
Literal, | ||
|
@@ -90,7 +89,6 @@ | |
BaseMaskedArray, | ||
ExtensionArray, | ||
) | ||
from pandas.core.arrays._mixins import NDArrayBackedExtensionArray | ||
from pandas.core.arrays.string_ import StringDtype | ||
import pandas.core.common as com | ||
from pandas.core.construction import ( | ||
|
@@ -99,7 +97,10 @@ | |
) | ||
from pandas.core.frame import _merge_doc | ||
from pandas.core.indexes.api import default_index | ||
from pandas.core.sorting import is_int64_overflow_possible | ||
from pandas.core.sorting import ( | ||
get_group_index, | ||
is_int64_overflow_possible, | ||
) | ||
|
||
if TYPE_CHECKING: | ||
from pandas import DataFrame | ||
|
@@ -2117,34 +2118,6 @@ def _convert_values_for_libjoin( | |
def _get_join_indexers(self) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: | ||
"""return the join indexers""" | ||
|
||
def flip(xs: list[ArrayLike]) -> np.ndarray: | ||
"""unlike np.transpose, this returns an array of tuples""" | ||
|
||
def injection(obj: ArrayLike): | ||
if not isinstance(obj.dtype, ExtensionDtype): | ||
# ndarray | ||
return obj | ||
obj = extract_array(obj) | ||
if isinstance(obj, NDArrayBackedExtensionArray): | ||
# fastpath for e.g. dt64tz, categorical | ||
return obj._ndarray | ||
# FIXME: returning obj._values_for_argsort() here doesn't | ||
# break in any existing test cases, but i (@jbrockmendel) | ||
# am pretty sure it should! | ||
# e.g. | ||
# arr = pd.array([0, pd.NA, 255], dtype="UInt8") | ||
# will have values_for_argsort (before GH#45434) | ||
# np.array([0, 255, 255], dtype=np.uint8) | ||
# and the non-injectivity should make a difference somehow | ||
# shouldn't it? | ||
return np.asarray(obj) | ||
|
||
xs = [injection(x) for x in xs] | ||
labels = list(string.ascii_lowercase[: len(xs)]) | ||
dtypes = [x.dtype for x in xs] | ||
labeled_dtypes = list(zip(labels, dtypes)) | ||
return np.array(list(zip(*xs)), labeled_dtypes) | ||
|
||
# values to compare | ||
left_values = ( | ||
self.left.index._values if self.left_index else self.left_join_keys[-1] | ||
|
@@ -2197,11 +2170,23 @@ def injection(obj: ArrayLike): | |
else: | ||
# We get here with non-ndarrays in test_merge_by_col_tz_aware | ||
# and test_merge_groupby_multiple_column_with_categorical_column | ||
lbv = flip(left_by_values) | ||
rbv = flip(right_by_values) | ||
lbv = ensure_object(lbv) | ||
rbv = ensure_object(rbv) | ||
|
||
mapped = [ | ||
_factorize_keys( | ||
left_by_values[n], | ||
right_by_values[n], | ||
sort=False, | ||
how="outer", | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Not super familiar with this code but does hard coding There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Good point, we can use how=left here. Updated. |
||
) | ||
for n in range(len(left_by_values)) | ||
] | ||
arrs = [np.concatenate(m[:2]) for m in mapped] | ||
shape = tuple(m[2] for m in mapped) | ||
group_index = get_group_index( | ||
arrs, shape=shape, sort=False, xnull=False | ||
) | ||
left_len = len(left_by_values[0]) | ||
lbv = group_index[:left_len] | ||
rbv = group_index[left_len:] | ||
# error: Incompatible types in assignment (expression has type | ||
# "Union[ndarray[Any, dtype[Any]], ndarray[Any, dtype[object_]]]", | ||
# variable has type "List[Union[Union[ExtensionArray, | ||
|
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I'm assuming this work alright with ExtensionArrays? Do we have tests for merging on
by
that is a extension column?There was a problem hiding this comment.
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Yes, this will work with EAs. I've parameterized an existing test to include EA dtypes.
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Added an additional test as this seems to fix #43541