def test_constructors():
v1 = xf.StringArray(TEST_ARRAY)
assert isinstance(v1.dtype, xf.StringDtype)
v2 = xf.StringArray(np.array(TEST_ARRAY))
assert isinstance(v2.dtype, xf.StringDtype)
v3 = xf.StringArray(xnd.xnd(TEST_ARRAY))
assert isinstance(v3.dtype, xf.StringDtype)
def test_concatenate_blocks():
v1 = xf.StringArray(TEST_ARRAY)
sa = pd.Series(v1)
result = pd.concat([sa, sa], ignore_index=True)
EXPECTED_ARRAY = xnd.xnd(["Test", "string", None, "Test", "string", None])
expected = pd.Series(xf.StringArray(EXPECTED_ARRAY))
tm.assert_series_equal(result, expected)
def test_dataframe_from_series_no_dict():
s = pd.Series(xf.StringArray(TEST_ARRAY))
result = pd.DataFrame(s)
expected = pd.DataFrame({0: s})
tm.assert_frame_equal(result, expected)
s = pd.Series(xf.StringArray(TEST_ARRAY), name='A')
result = pd.DataFrame(s)
expected = pd.DataFrame({'A': s})
tm.assert_frame_equal(result, expected)
def test_getitem_scalar():
sa = xf.StringArray(TEST_ARRAY)
ser = pd.Series(sa)
result = ser[1]
assert result == sa.data[1]
result = ser[5]
assert result is None
result = ser[-3]
assert result == "Test"
def test_copy():
ser = pd.Series(xf.StringArray(TEST_ARRAY))
copy = ser.copy()
tm.assert_series_equal(ser, copy)
def test_isna():
ser = pd.Series(xf.StringArray(TEST_ARRAY))
result = ser.isna().values
expected = np.array([False, False, True])
np.testing.assert_array_equal(result, expected)
def test_getitem_iterable():
ser = pd.Series(xf.StringArray(TEST_ARRAY))
result = ser[[0, 1]]
expected = pd.Series(xf.StringArray(TEST_ARRAY[0:2]), index=range(0, 2))
tm.assert_series_equal(result, expected)
def test_getitem_slice():
ser = pd.Series(xf.StringArray(TEST_ARRAY))
result = ser[1:]
expected = pd.Series(xf.StringArray(TEST_ARRAY[1:]), index=range(1, 3))
tm.assert_series_equal(result, expected)
def test_dataframe_from_series():
s = pd.Series(xf.StringArray(TEST_ARRAY))
c = pd.Series(pd.Categorical(['a', 'b']))
result = pd.DataFrame({"A": s, "B": c})
assert isinstance(result.dtypes["A"], xf.StringDtype)
def test_dataframe_constructor():
v = xf.StringArray(TEST_ARRAY)
df = pd.DataFrame({"A": v})
assert isinstance(df.dtypes["A"], xf.StringDtype)
assert df.shape == (3, 1)
str(df)
def test_series_constructor():
v = xf.StringArray(TEST_ARRAY)
result = pd.Series(v)
assert result.dtype == v.dtype
assert isinstance(result._data.blocks[0], ExtensionBlock)
def test_take():
ser = pd.Series(xf.StringArray(TEST_ARRAY))
result = ser.take([0, 2, 1])
assert isinstance(result, pd.Series)
def test_size():
ser = pd.Series(xf.StringArray(TEST_ARRAY))
assert ser.size == len(TEST_ARRAY)
def test_astype():
ser = pd.Series(xf.StringArray(TEST_ARRAY))
as_ser = ser.astype('object')
result = as_ser.dtype
result is np.dtype('object')
def test_factorize():
ser = pd.Series(xf.StringArray(TEST_ARRAY))
labels, uniques = ser.factorize()
expected_labels = np.array([0, 1, -1])
np.testing.assert_array_equal(labels, expected_labels)
def test_nbytes():
sa = xf.StringArray(TEST_ARRAY)
result = sa.nbytes
expected = len(TEST_ARRAY) * 8
assert result == expected