def test_series_constructor_coerce_data_to_extension_dtype_raises():
xpr = (
"Cannot cast data to extension dtype 'decimal'. Pass the "
"extension array directly."
)
with pytest.raises(ValueError, match=xpr):
pd.Series([0, 1, 2], dtype=DecimalDtype())
def test_series_constructor_with_dtype():
arr = DecimalArray([decimal.Decimal("10.0")])
result = pd.Series(arr, dtype=DecimalDtype())
expected = pd.Series(arr)
tm.assert_series_equal(result, expected)
result = pd.Series(arr, dtype="int64")
expected = pd.Series([10])
tm.assert_series_equal(result, expected)
def test_dataframe_constructor_with_dtype():
arr = DecimalArray([decimal.Decimal("10.0")])
result = pd.DataFrame({"A": arr}, dtype=DecimalDtype())
expected = pd.DataFrame({"A": arr})
tm.assert_frame_equal(result, expected)
arr = DecimalArray([decimal.Decimal("10.0")])
result = pd.DataFrame({"A": arr}, dtype="int64")
expected = pd.DataFrame({"A": [10]})
tm.assert_frame_equal(result, expected)
def test_astype_dispatches(frame):
# This is a dtype-specific test that ensures Series[decimal].astype
# gets all the way through to ExtensionArray.astype
# Designing a reliable smoke test that works for arbitrary data types
# is difficult.
data = pd.Series(DecimalArray([decimal.Decimal(2)]), name="a")
ctx = decimal.Context()
ctx.prec = 5
if frame:
data = data.to_frame()
result = data.astype(DecimalDtype(ctx))
if frame:
result = result["a"]
assert result.dtype.context.prec == ctx.prec
def dtype():
return DecimalDtype()
def test_as_json_table_type_ext_decimal_dtype(self):
assert as_json_table_type(DecimalDtype()) == "any"