def _parsed_string_to_bounds(self, reso: Resolution, parsed: datetime):
"""
Calculate datetime bounds for parsed time string and its resolution.
Parameters
----------
reso : str
Resolution provided by parsed string.
parsed : datetime
Datetime from parsed string.
Returns
-------
lower, upper: pd.Timestamp
"""
grp = reso.freq_group
per = Period(parsed, freq=grp.value)
start, end = per.start_time, per.end_time
# GH 24076
# If an incoming date string contained a UTC offset, need to localize
# the parsed date to this offset first before aligning with the index's
# timezone
start = start.tz_localize(parsed.tzinfo)
end = end.tz_localize(parsed.tzinfo)
if parsed.tzinfo is not None:
if self.tz is None:
raise ValueError(
"The index must be timezone aware when indexing "
"with a date string with a UTC offset")
start = self._maybe_cast_for_get_loc(start)
end = self._maybe_cast_for_get_loc(end)
return start, end
def _parsed_string_to_bounds(self, reso: Resolution, parsed: datetime):
"""
Calculate datetime bounds for parsed time string and its resolution.
Parameters
----------
reso : str
Resolution provided by parsed string.
parsed : datetime
Datetime from parsed string.
Returns
-------
lower, upper: pd.Timestamp
"""
assert isinstance(reso, Resolution), (type(reso), reso)
valid_resos = {
"year",
"month",
"quarter",
"day",
"hour",
"minute",
"second",
"minute",
"second",
"microsecond",
}
if reso.attrname not in valid_resos:
raise KeyError
grp = reso.freq_group
per = Period(parsed, freq=grp)
start, end = per.start_time, per.end_time
# GH 24076
# If an incoming date string contained a UTC offset, need to localize
# the parsed date to this offset first before aligning with the index's
# timezone
if parsed.tzinfo is not None:
if self.tz is None:
raise ValueError(
"The index must be timezone aware when indexing "
"with a date string with a UTC offset"
)
start = start.tz_localize(parsed.tzinfo).tz_convert(self.tz)
end = end.tz_localize(parsed.tzinfo).tz_convert(self.tz)
elif self.tz is not None:
start = start.tz_localize(self.tz)
end = end.tz_localize(self.tz)
return start, end
def _wrap_results(result, dtype: Dtype, fill_value=None):
""" wrap our results if needed """
if is_datetime64_any_dtype(dtype):
if fill_value is None:
# GH#24293
fill_value = iNaT
if not isinstance(result, np.ndarray):
tz = getattr(dtype, "tz", None)
assert not isna(fill_value), "Expected non-null fill_value"
if result == fill_value:
result = np.nan
result = Timestamp(result, tz=tz)
else:
# If we have float dtype, taking a view will give the wrong result
result = result.astype(dtype)
elif is_timedelta64_dtype(dtype):
if not isinstance(result, np.ndarray):
if result == fill_value:
result = np.nan
# raise if we have a timedelta64[ns] which is too large
if np.fabs(result) > _int64_max:
raise ValueError("overflow in timedelta operation")
result = Timedelta(result, unit="ns")
else:
result = result.astype("m8[ns]").view(dtype)
elif isinstance(dtype, PeriodDtype):
if is_float(result) and result.is_integer():
result = int(result)
if is_integer(result):
result = Period._from_ordinal(result, freq=dtype.freq)
else:
raise NotImplementedError(type(result), result)
return result
