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PERF: avoid object-dtype comparisons #24792

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Merged
merged 1 commit into from
Jan 16, 2019
Merged

PERF: avoid object-dtype comparisons #24792

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6 changes: 6 additions & 0 deletions pandas/core/internals/blocks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2465,6 +2465,12 @@ def setitem(self, indexer, value):
klass=ObjectBlock,)
return newb.setitem(indexer, value)

def equals(self, other):
# override for significant performance improvement
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why would u do this here and not in array_equivalent

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Because array_equivalent's docstring specifically says it assumes it is dealing with numpy arrays

if self.dtype != other.dtype or self.shape != other.shape:
return False
return (self.values.view('i8') == other.values.view('i8')).all()


class TimeDeltaBlock(DatetimeLikeBlockMixin, IntBlock):
__slots__ = ()
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5 changes: 5 additions & 0 deletions pandas/util/testing.py
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Expand Up @@ -1199,6 +1199,11 @@ def assert_extension_array_equal(left, right, check_dtype=True,
if check_dtype:
assert_attr_equal('dtype', left, right, obj='ExtensionArray')

if hasattr(left, "asi8") and type(right) == type(left):
# Avoid slow object-dtype comparisons
assert_numpy_array_equal(left.asi8, right.asi8)
return

left_na = np.asarray(left.isna())
right_na = np.asarray(right.isna())
assert_numpy_array_equal(left_na, right_na, obj='ExtensionArray NA mask')
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