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Remove deprecated behavior from dataset.drop docstring #3451

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Oct 29, 2019
Merged

Remove deprecated behavior from dataset.drop docstring #3451

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44fbf9c
remove deprecated behavior from dataset.drop docstring
max-sixty Oct 26, 2019
88863a2
remove a few warnings too
max-sixty Oct 26, 2019
acbe79e
actually keep original form but test for warnings
max-sixty Oct 26, 2019
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1 change: 0 additions & 1 deletion xarray/core/dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3536,7 +3536,6 @@ def drop( # noqa: F811
----------
labels : hashable or iterable of hashables
Name(s) of variables or index labels to drop.
If dim is not None, labels can be any array-like.
dim : None or hashable, optional
Dimension along which to drop index labels. By default (if
``dim is None``), drops variables rather than index labels.
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18 changes: 12 additions & 6 deletions xarray/tests/test_dataset.py
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Expand Up @@ -2118,25 +2118,31 @@ def test_drop_variables(self):
def test_drop_index_labels(self):
data = Dataset({"A": (["x", "y"], np.random.randn(2, 3)), "x": ["a", "b"]})

actual = data.drop(["a"], "x")
with pytest.warns(DeprecationWarning):
actual = data.drop(["a"], "x")
expected = data.isel(x=[1])
assert_identical(expected, actual)

actual = data.drop(["a", "b"], "x")
with pytest.warns(DeprecationWarning):
actual = data.drop(["a", "b"], "x")
expected = data.isel(x=slice(0, 0))
assert_identical(expected, actual)

with pytest.raises(KeyError):
# not contained in axis
data.drop(["c"], dim="x")
with pytest.warns(DeprecationWarning):
data.drop(["c"], dim="x")

actual = data.drop(["c"], dim="x", errors="ignore")
with pytest.warns(DeprecationWarning):
actual = data.drop(["c"], dim="x", errors="ignore")
assert_identical(data, actual)

with pytest.raises(ValueError):
data.drop(["c"], dim="x", errors="wrong_value")
with pytest.warns(DeprecationWarning):
data.drop(["c"], dim="x", errors="wrong_value")

actual = data.drop(["a", "b", "c"], "x", errors="ignore")
with pytest.warns(DeprecationWarning):
actual = data.drop(["a", "b", "c"], "x", errors="ignore")
expected = data.isel(x=slice(0, 0))
assert_identical(expected, actual)

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