def test_modes_with_nans():
# GH39007
values = np.array([True, pd.NA, np.nan], dtype=np.object_)
# pd.Na and np.nan will have the same representative: np.nan
# thus we have 2 nans and 1 True
modes = ht.mode(values, False)
assert modes.size == 1
assert np.isnan(modes[0])
def test_mode(self, dtype, writable):
if dtype in (np.int8, np.uint8):
N = 53
else:
N = 11111
values = np.repeat(np.arange(N).astype(dtype), 5)
values[0] = 42
values.flags.writeable = writable
result = ht.mode(values, False)
assert result == 42
def test_mode(self, dtype):
values = np.array([42, np.nan, np.nan, np.nan], dtype=dtype)
assert ht.mode(values, True) == 42
assert np.isnan(ht.mode(values, False))
def test_modes_with_nans():
# GH42688, nans aren't mangled
nulls = [pd.NA, np.nan, pd.NaT, None]
values = np.array([True] + nulls * 2, dtype=np.object_)
modes = ht.mode(values, False)
assert modes.size == len(nulls)
def test_mode_stable(self, dtype, writable):
values = np.array([2, 1, 5, 22, 3, -1, 8]).astype(dtype)
values.flags.writeable = writable
keys = ht.mode(values, False)
tm.assert_numpy_array_equal(keys, values)
