def test_shift_fill_value(self, frame_or_series):
# GH#24128
dti = date_range("1/1/2000", periods=5, freq="H")
ts = frame_or_series([1.0, 2.0, 3.0, 4.0, 5.0], index=dti)
exp = frame_or_series([0.0, 1.0, 2.0, 3.0, 4.0], index=dti)
# check that fill value works
result = ts.shift(1, fill_value=0.0)
tm.assert_equal(result, exp)
exp = frame_or_series([0.0, 0.0, 1.0, 2.0, 3.0], index=dti)
result = ts.shift(2, fill_value=0.0)
tm.assert_equal(result, exp)
ts = frame_or_series([1, 2, 3])
res = ts.shift(2, fill_value=0)
assert tm.get_dtype(res) == tm.get_dtype(ts)
# retain integer dtype
obj = frame_or_series([1, 2, 3, 4, 5], index=dti)
exp = frame_or_series([0, 1, 2, 3, 4], index=dti)
result = obj.shift(1, fill_value=0)
tm.assert_equal(result, exp)
exp = frame_or_series([0, 0, 1, 2, 3], index=dti)
result = obj.shift(2, fill_value=0)
tm.assert_equal(result, exp)
def test_shift_dst(self, frame_or_series):
# GH#13926
dates = date_range("2016-11-06", freq="H", periods=10, tz="US/Eastern")
obj = frame_or_series(dates)
res = obj.shift(0)
tm.assert_equal(res, obj)
assert tm.get_dtype(res) == "datetime64[ns, US/Eastern]"
res = obj.shift(1)
exp_vals = [NaT] + dates.astype(object).values.tolist()[:9]
exp = frame_or_series(exp_vals)
tm.assert_equal(res, exp)
assert tm.get_dtype(res) == "datetime64[ns, US/Eastern]"
res = obj.shift(-2)
exp_vals = dates.astype(object).values.tolist()[2:] + [NaT, NaT]
exp = frame_or_series(exp_vals)
tm.assert_equal(res, exp)
assert tm.get_dtype(res) == "datetime64[ns, US/Eastern]"
for ex in [10, -10, 20, -20]:
res = obj.shift(ex)
exp = frame_or_series([NaT] * 10,
dtype="datetime64[ns, US/Eastern]")
tm.assert_equal(res, exp)
assert tm.get_dtype(res) == "datetime64[ns, US/Eastern]"
def _check_op(self, s, op, other, op_name, exc=NotImplementedError):
if exc is None:
sdtype = tm.get_dtype(s)
if (hasattr(other, "dtype")
and not is_extension_array_dtype(other.dtype)
and is_integer_dtype(other.dtype)
and sdtype.is_unsigned_integer):
# TODO: comment below is inaccurate; other can be int8, int16, ...
# and the trouble is that e.g. if s is UInt8 and other is int8,
# then result is UInt16
# other is np.int64 and would therefore always result in
# upcasting, so keeping other as same numpy_dtype
other = other.astype(sdtype.numpy_dtype)
result = op(s, other)
expected = self._combine(s, other, op)
if op_name in ("__rtruediv__", "__truediv__", "__div__"):
expected = expected.fillna(np.nan).astype("Float64")
else:
# combine method result in 'biggest' (int64) dtype
expected = expected.astype(sdtype)
self.assert_equal(result, expected)
else:
with pytest.raises(exc):
op(s, other)
def test_shift_dst_beyond(self, frame_or_series, ex):
# GH#13926
dates = date_range("2016-11-06", freq="H", periods=10, tz="US/Eastern")
obj = frame_or_series(dates)
res = obj.shift(ex)
exp = frame_or_series([NaT] * 10, dtype="datetime64[ns, US/Eastern]")
tm.assert_equal(res, exp)
assert tm.get_dtype(res) == "datetime64[ns, US/Eastern]"
def _check_op(self, s, op, other, op_name, exc=NotImplementedError):
if exc is None:
sdtype = tm.get_dtype(s)
if (hasattr(other, "dtype")
and not is_extension_array_dtype(other.dtype)
and is_float_dtype(other.dtype)):
# other is np.float64 and would therefore always result in
# upcasting, so keeping other as same numpy_dtype
other = other.astype(sdtype.numpy_dtype)
result = op(s, other)
expected = self._combine(s, other, op)
# combine method result in 'biggest' (float64) dtype
expected = expected.astype(sdtype)
self.assert_equal(result, expected)
else:
with pytest.raises(exc):
op(s, other)
def _check_op(self, s, op, other, op_name, exc=NotImplementedError):
if exc is None:
sdtype = tm.get_dtype(s)
if sdtype.is_unsigned_integer and (op_name == "__rsub__"):
# TODO see https://github.com/pandas-dev/pandas/issues/22023
pytest.skip("unsigned subtraction gives negative values")
if (hasattr(other, "dtype")
and not is_extension_array_dtype(other.dtype)
and is_integer_dtype(other.dtype)):
# other is np.int64 and would therefore always result in
# upcasting, so keeping other as same numpy_dtype
other = other.astype(sdtype.numpy_dtype)
result = op(s, other)
expected = self._combine(s, other, op)
if op_name in ("__rtruediv__", "__truediv__", "__div__"):
expected = expected.fillna(np.nan).astype("Float64")
elif op_name.startswith("__r"):
# TODO reverse operators result in object dtype
# see https://github.com/pandas-dev/pandas/issues/22024
expected = expected.astype(sdtype)
result = result.astype(sdtype)
else:
# combine method result in 'biggest' (int64) dtype
expected = expected.astype(sdtype)
pass
if (op_name == "__rpow__") and isinstance(other, pd.Series):
# TODO pow on Int arrays gives different result with NA
# see https://github.com/pandas-dev/pandas/issues/22022
result = result.fillna(1)
self.assert_equal(result, expected)
else:
with pytest.raises(exc):
op(s, other)
