def test_basic_binop():
# Just a basic smoke test. The EA interface tests exercise this
# more thoroughly.
x = PandasArray(np.array([1, 2, 3]))
result = x + x
expected = PandasArray(np.array([2, 4, 6]))
tm.assert_extension_array_equal(result, expected)
def test_quantile_empty(dtype):
# we should get back np.nans, not -1s
arr = PandasArray(np.array([], dtype=dtype))
idx = pd.Index([0.0, 0.5])
result = arr._quantile(idx, interpolation="linear")
expected = PandasArray(np.array([np.nan, np.nan]))
tm.assert_extension_array_equal(result, expected)
def test_setitem(any_numpy_array):
nparr = any_numpy_array
arr = PandasArray(nparr, copy=True)
arr[0] = arr[1]
nparr[0] = nparr[1]
tm.assert_numpy_array_equal(arr.to_numpy(), nparr)
def test_setitem(any_numpy_array):
nparr = any_numpy_array
arr = PandasArray(nparr, copy=True)
arr[0] = arr[1]
nparr[0] = nparr[1]
tm.assert_numpy_array_equal(arr.to_numpy(), nparr)
def test_ufunc():
arr = PandasArray(np.array([-1.0, 0.0, 1.0]))
r1, r2 = np.divmod(arr, np.add(arr, 2))
e1, e2 = np.divmod(arr._ndarray, np.add(arr._ndarray, 2))
e1 = PandasArray(e1)
e2 = PandasArray(e2)
tm.assert_extension_array_equal(r1, e1)
tm.assert_extension_array_equal(r2, e2)
def test_np_reduce_2d():
raw = np.arange(12).reshape(4, 3)
arr = PandasArray(raw)
res = np.maximum.reduce(arr, axis=0)
tm.assert_extension_array_equal(res, arr[-1])
alt = arr.max(axis=0)
tm.assert_extension_array_equal(alt, arr[-1])
def test_ufunc_unary(ufunc):
arr = PandasArray(np.array([-1.0, 0.0, 1.0]))
result = ufunc(arr)
expected = PandasArray(ufunc(arr._ndarray))
tm.assert_extension_array_equal(result, expected)
# same thing but with the 'out' keyword
out = PandasArray(np.array([-9.0, -9.0, -9.0]))
ufunc(arr, out=out)
tm.assert_extension_array_equal(out, expected)
def test_factorize_unsigned():
# don't raise when calling factorize on unsigned int PandasArray
arr = np.array([1, 2, 3], dtype=np.uint64)
obj = PandasArray(arr)
res_codes, res_unique = obj.factorize()
exp_codes, exp_unique = pd.factorize(arr)
tm.assert_numpy_array_equal(res_codes, exp_codes)
tm.assert_extension_array_equal(res_unique, PandasArray(exp_unique))
def test_to_numpy():
arr = PandasArray(np.array([1, 2, 3]))
result = arr.to_numpy()
assert result is arr._ndarray
result = arr.to_numpy(copy=True)
assert result is not arr._ndarray
result = arr.to_numpy(dtype='f8')
expected = np.array([1, 2, 3], dtype='f8')
tm.assert_numpy_array_equal(result, expected)
def test_to_numpy():
arr = PandasArray(np.array([1, 2, 3]))
result = arr.to_numpy()
assert result is arr._ndarray
result = arr.to_numpy(copy=True)
assert result is not arr._ndarray
result = arr.to_numpy(dtype='f8')
expected = np.array([1, 2, 3], dtype='f8')
tm.assert_numpy_array_equal(result, expected)
def test_setitem_preserves_views():
# GH#28150, see also extension test of the same name
arr = PandasArray(np.array([1, 2, 3]))
view1 = arr.view()
view2 = arr[:]
view3 = np.asarray(arr)
arr[0] = 9
assert view1[0] == 9
assert view2[0] == 9
assert view3[0] == 9
arr[-1] = 2.5
view1[-1] = 5
assert arr[-1] == 5
def test_setitem_no_coercion():
# https://github.com/pandas-dev/pandas/issues/28150
arr = PandasArray(np.array([1, 2, 3]))
with pytest.raises(ValueError, match="int"):
arr[0] = "a"
# With a value that we do coerce, check that we coerce the value
# and not the underlying array.
arr[0] = 2.5
assert isinstance(arr[0], (int, np.integer)), type(arr[0])
def test_constructor_with_data(any_numpy_array):
nparr = any_numpy_array
arr = PandasArray(nparr)
assert arr.dtype.numpy_dtype == nparr.dtype
def test_from_sequence_dtype():
arr = np.array([1, 2, 3], dtype='int64')
result = PandasArray._from_sequence(arr, dtype='uint64')
expected = PandasArray(np.array([1, 2, 3], dtype='uint64'))
tm.assert_extension_array_equal(result, expected)
def test_from_sequence_dtype():
arr = np.array([1, 2, 3], dtype='int64')
result = PandasArray._from_sequence(arr, dtype='uint64')
expected = PandasArray(np.array([1, 2, 3], dtype='uint64'))
tm.assert_extension_array_equal(result, expected)
def test_series_constructor_with_astype():
ndarray = np.array([1, 2, 3])
result = pd.Series(PandasArray(ndarray), dtype="float64")
expected = pd.Series([1.0, 2.0, 3.0], dtype="float64")
tm.assert_series_equal(result, expected)
def test_series_constructor_with_copy():
ndarray = np.array([1, 2, 3])
ser = pd.Series(PandasArray(ndarray), copy=True)
assert ser.values is not ndarray
def test_constructor_no_coercion():
with pytest.raises(ValueError, match='NumPy array'):
PandasArray([1, 2, 3])
def test_constructor_copy():
arr = np.array([0, 1])
result = PandasArray(arr, copy=True)
assert not tm.shares_memory(result, arr)
def test_validate_reduction_keyword_args():
arr = PandasArray(np.array([1, 2, 3]))
msg = "the 'keepdims' parameter is not supported .*all"
with pytest.raises(ValueError, match=msg):
arr.all(keepdims=True)
def test_bad_reduce_raises():
arr = np.array([1, 2, 3], dtype='int64')
arr = PandasArray(arr)
msg = "cannot perform not_a_method with type int"
with pytest.raises(TypeError, match=msg):
arr._reduce(msg)
def test_setitem_object_typecode(dtype):
arr = PandasArray(np.array(["a", "b", "c"], dtype=dtype))
arr[0] = "t"
expected = PandasArray(np.array(["t", "b", "c"], dtype=dtype))
tm.assert_extension_array_equal(arr, expected)
def test_setitem_no_coercion():
# https://github.com/pandas-dev/pandas/issues/28150
arr = PandasArray(np.array([1, 2, 3]))
with pytest.raises(ValueError, match="int"):
arr[0] = "a"
def test_bad_reduce_raises():
arr = np.array([1, 2, 3], dtype='int64')
arr = PandasArray(arr)
msg = "cannot perform not_a_method with type int"
with pytest.raises(TypeError, match=msg):
arr._reduce(msg)
def test_constructor_copy():
arr = np.array([0, 1])
result = PandasArray(arr, copy=True)
assert np.shares_memory(result._ndarray, arr) is False
def test_validate_reduction_keyword_args():
arr = PandasArray(np.array([1, 2, 3]))
msg = "the 'keepdims' parameter is not supported .*all"
with pytest.raises(ValueError, match=msg):
arr.all(keepdims=True)
def test_ufunc_unary(ufunc):
arr = PandasArray(np.array([-1.0, 0.0, 1.0]))
result = ufunc(arr)
expected = PandasArray(ufunc(arr._ndarray))
tm.assert_extension_array_equal(result, expected)
