def test_concat_different_extension_dtypes_upcasts(self):
a = Series(pd.core.arrays.integer_array([1, 2]))
b = Series(to_decimal([1, 2]))
result = pd.concat([a, b], ignore_index=True)
expected = Series([1, 2, Decimal(1), Decimal(2)], dtype=object)
tm.assert_series_equal(result, expected)
# String
(["a", None], "string", StringArray._from_sequence(["a", None])),
(["a", None], pd.StringDtype(), StringArray._from_sequence(["a", None])),
# Boolean
([True, None], "boolean", BooleanArray._from_sequence([True, None])),
([True, None], pd.BooleanDtype(), BooleanArray._from_sequence([True, None])),
# Index
(pd.Index([1, 2]), None, PandasArray(np.array([1, 2], dtype=np.int64))),
# Series[EA] returns the EA
(
pd.Series(pd.Categorical(["a", "b"], categories=["a", "b", "c"])),
None,
pd.Categorical(["a", "b"], categories=["a", "b", "c"]),
),
# "3rd party" EAs work
([decimal.Decimal(0), decimal.Decimal(1)], "decimal", to_decimal([0, 1])),
# pass an ExtensionArray, but a different dtype
(
period_array(["2000", "2001"], freq="D"),
"category",
pd.Categorical([pd.Period("2000", "D"), pd.Period("2001", "D")]),
),
],
)
def test_array(data, dtype, expected):
result = pd.array(data, dtype=dtype)
tm.assert_equal(result, expected)
def test_array_copy():
a = np.array([1, 2])
([0, 1], 'Sparse[int64]', pd.SparseArray([0, 1], dtype='int64')),
# IntegerNA
([1, None], 'Int16', integer_array([1, None], dtype='Int16')),
(pd.Series([1, 2]), None, PandasArray(np.array([1, 2], dtype=np.int64))),
# Index
(pd.Index([1, 2]), None, PandasArray(np.array([1, 2], dtype=np.int64))),
# Series[EA] returns the EA
(pd.Series(pd.Categorical(['a', 'b'], categories=['a', 'b', 'c'])),
None,
pd.Categorical(['a', 'b'], categories=['a', 'b', 'c'])),
# "3rd party" EAs work
([decimal.Decimal(0), decimal.Decimal(1)], 'decimal', to_decimal([0, 1])),
# pass an ExtensionArray, but a different dtype
(period_array(['2000', '2001'], freq='D'),
'category',
pd.Categorical([pd.Period('2000', 'D'), pd.Period('2001', 'D')])),
])
def test_array(data, dtype, expected):
result = pd.array(data, dtype=dtype)
tm.assert_equal(result, expected)
def test_array_copy():
a = np.array([1, 2])
# default is to copy
b = pd.array(a)
