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STYLE: Inconsistent namespace - dtypes (pandas-dev#39992) #40161

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Mar 2, 2021
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STYLE: Inconsistent namespace - dtypes (pandas-dev#39992) #40161

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2 changes: 1 addition & 1 deletion pandas/tests/dtypes/test_dtypes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -821,7 +821,7 @@ class TestCategoricalDtypeParametrized:
np.arange(1000),
["a", "b", 10, 2, 1.3, True],
[True, False],
pd.date_range("2017", periods=4),
date_range("2017", periods=4),
],
)
def test_basic(self, categories, ordered):
Expand Down
8 changes: 4 additions & 4 deletions pandas/tests/dtypes/test_inference.py
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Expand Up @@ -808,7 +808,7 @@ def test_unicode(self):
(object, None, True, "empty"),
],
)
@pytest.mark.parametrize("box", [pd.Series, np.array])
@pytest.mark.parametrize("box", [Series, np.array])
def test_object_empty(self, box, missing, dtype, skipna, expected):
# GH 23421
arr = box([missing, missing], dtype=dtype)
Expand Down Expand Up @@ -915,7 +915,7 @@ def test_infer_dtype_period(self):
arr = np.array([Period("2011-01", freq="D"), Period("2011-02", freq="M")])
assert lib.infer_dtype(arr, skipna=True) == "period"

@pytest.mark.parametrize("klass", [pd.array, pd.Series, pd.Index])
@pytest.mark.parametrize("klass", [pd.array, Series, Index])
@pytest.mark.parametrize("skipna", [True, False])
def test_infer_dtype_period_array(self, klass, skipna):
# https://github.com/pandas-dev/pandas/issues/23553
Expand Down Expand Up @@ -1264,7 +1264,7 @@ def test_interval(self):
inferred = lib.infer_dtype(Series(idx), skipna=False)
assert inferred == "interval"

@pytest.mark.parametrize("klass", [pd.array, pd.Series])
@pytest.mark.parametrize("klass", [pd.array, Series])
@pytest.mark.parametrize("skipna", [True, False])
@pytest.mark.parametrize("data", [["a", "b", "c"], ["a", "b", pd.NA]])
def test_string_dtype(self, data, skipna, klass):
Expand All @@ -1273,7 +1273,7 @@ def test_string_dtype(self, data, skipna, klass):
inferred = lib.infer_dtype(val, skipna=skipna)
assert inferred == "string"

@pytest.mark.parametrize("klass", [pd.array, pd.Series])
@pytest.mark.parametrize("klass", [pd.array, Series])
@pytest.mark.parametrize("skipna", [True, False])
@pytest.mark.parametrize("data", [[True, False, True], [True, False, pd.NA]])
def test_boolean_dtype(self, data, skipna, klass):
Expand Down
28 changes: 14 additions & 14 deletions pandas/tests/dtypes/test_missing.py
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Expand Up @@ -205,16 +205,16 @@ def test_isna_datetime(self):

def test_isna_old_datetimelike(self):
# isna_old should work for dt64tz, td64, and period, not just tznaive
dti = pd.date_range("2016-01-01", periods=3)
dti = date_range("2016-01-01", periods=3)
dta = dti._data
dta[-1] = pd.NaT
dta[-1] = NaT
expected = np.array([False, False, True], dtype=bool)

objs = [dta, dta.tz_localize("US/Eastern"), dta - dta, dta.to_period("D")]

for obj in objs:
with cf.option_context("mode.use_inf_as_na", True):
result = pd.isna(obj)
result = isna(obj)

tm.assert_numpy_array_equal(result, expected)

Expand Down Expand Up @@ -320,38 +320,38 @@ def test_period(self):
def test_decimal(self):
# scalars GH#23530
a = Decimal(1.0)
assert pd.isna(a) is False
assert pd.notna(a) is True
assert isna(a) is False
assert notna(a) is True

b = Decimal("NaN")
assert pd.isna(b) is True
assert pd.notna(b) is False
assert isna(b) is True
assert notna(b) is False

# array
arr = np.array([a, b])
expected = np.array([False, True])
result = pd.isna(arr)
result = isna(arr)
tm.assert_numpy_array_equal(result, expected)

result = pd.notna(arr)
result = notna(arr)
tm.assert_numpy_array_equal(result, ~expected)

# series
ser = Series(arr)
expected = Series(expected)
result = pd.isna(ser)
result = isna(ser)
tm.assert_series_equal(result, expected)

result = pd.notna(ser)
result = notna(ser)
tm.assert_series_equal(result, ~expected)

# index
idx = pd.Index(arr)
expected = np.array([False, True])
result = pd.isna(idx)
result = isna(idx)
tm.assert_numpy_array_equal(result, expected)

result = pd.notna(idx)
result = notna(idx)
tm.assert_numpy_array_equal(result, ~expected)


Expand Down Expand Up @@ -578,7 +578,7 @@ def _check_behavior(self, arr, expected):
tm.assert_numpy_array_equal(result, expected)

def test_basic(self):
arr = np.array([1, None, "foo", -5.1, pd.NaT, np.nan])
arr = np.array([1, None, "foo", -5.1, NaT, np.nan])
expected = np.array([False, True, False, False, True, True])

self._check_behavior(arr, expected)
Expand Down