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[ArrayManager] TST: include subset of ArrayManager tests in all CI builds #40496
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Original file line number | Diff line number | Diff line change |
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@@ -926,7 +926,9 @@ def test_setitem_duplicate_columns_not_inplace(self): | |
tm.assert_frame_equal(df_view, df_copy) | ||
tm.assert_frame_equal(df, expected) | ||
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@pytest.mark.parametrize("value", [1, np.array([[1], [1]]), [[1], [1]]]) | ||
@pytest.mark.parametrize( | ||
"value", [1, np.array([[1], [1]], dtype="int64"), [[1], [1]]] | ||
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. why? this is causing me problems in #35417 and i thinking making this change would fix that, but would feel like cheating 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. This is just adding a fixed dtype, doesn't change anything else. The default dtype of numpy is platform dependent, while in pandas it's always int64 (as you know ;)) |
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) | ||
def test_setitem_same_dtype_not_inplace(self, value, using_array_manager, request): | ||
# GH#39510 | ||
if not using_array_manager: | ||
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@@ -905,7 +905,7 @@ def test_unstack_nan_index3(self, using_array_manager): | |
if using_array_manager: | ||
# INFO(ArrayManager) with ArrayManager preserve dtype where possible | ||
cols = right.columns[[1, 2, 3, 5]] | ||
right[cols] = right[cols].astype("int64") | ||
right[cols] = right[cols].astype(df["C"].dtype) | ||
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. i take it this is a 32bit thing? 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. Yes, it was to fix the windows builds |
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tm.assert_frame_equal(left, right) | ||
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def test_unstack_nan_index4(self): | ||
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