def test_is_datetimelike():
assert not com.is_datetimelike([1, 2, 3])
assert not com.is_datetimelike(pd.Index([1, 2, 3]))
assert com.is_datetimelike(pd.DatetimeIndex([1, 2, 3]))
assert com.is_datetimelike(pd.PeriodIndex([], freq="A"))
assert com.is_datetimelike(np.array([], dtype=np.datetime64))
assert com.is_datetimelike(pd.Series([], dtype="timedelta64[ns]"))
assert com.is_datetimelike(pd.DatetimeIndex([1, 2, 3], tz="US/Eastern"))
dtype = DatetimeTZDtype("ns", tz="US/Eastern")
s = pd.Series([], dtype=dtype)
assert com.is_datetimelike(s)
def test_is_datetimelike():
assert not com.is_datetimelike([1, 2, 3])
assert not com.is_datetimelike(pd.Index([1, 2, 3]))
assert com.is_datetimelike(pd.DatetimeIndex([1, 2, 3]))
assert com.is_datetimelike(pd.PeriodIndex([], freq="A"))
assert com.is_datetimelike(np.array([], dtype=np.datetime64))
assert com.is_datetimelike(pd.Series([], dtype="timedelta64[ns]"))
assert com.is_datetimelike(pd.DatetimeIndex([1, 2, 3], tz="US/Eastern"))
dtype = DatetimeTZDtype("ns", tz="US/Eastern")
s = pd.Series([], dtype=dtype)
assert com.is_datetimelike(s)
def __iter__(self):
"""
Return an iterator of the values.
These are each a scalar type, which is a Python scalar
(for str, int, float) or a pandas scalar
(for Timestamp/Timedelta/Interval/Period)
"""
# We are explicity making element iterators.
if is_datetimelike(self._values):
return map(com.maybe_box_datetimelike, self._values)
elif is_extension_array_dtype(self._values):
return iter(self._values)
else:
return map(self._values.item, range(self._values.size))
def __iter__(self):
"""
Return an iterator of the values.
These are each a scalar type, which is a Python scalar
(for str, int, float) or a pandas scalar
(for Timestamp/Timedelta/Interval/Period)
"""
# We are explicity making element iterators.
if is_datetimelike(self._values):
return map(com.maybe_box_datetimelike, self._values)
elif is_extension_array_dtype(self._values):
return iter(self._values)
else:
return map(self._values.item, range(self._values.size))
def tolist(self):
"""
Return a list of the values.
These are each a scalar type, which is a Python scalar
(for str, int, float) or a pandas scalar
(for Timestamp/Timedelta/Interval/Period)
See Also
--------
numpy.ndarray.tolist
"""
if is_datetimelike(self):
return [com._maybe_box_datetimelike(x) for x in self._values]
else:
return self._values.tolist()
def tolist(self):
"""
Return a list of the values.
These are each a scalar type, which is a Python scalar
(for str, int, float) or a pandas scalar
(for Timestamp/Timedelta/Interval/Period)
See Also
--------
numpy.ndarray.tolist
"""
if is_datetimelike(self):
return [_maybe_box_datetimelike(x) for x in self._values]
else:
return self._values.tolist()
def wrapper(self, other):
meth = getattr(dtl.DatetimeLikeArrayMixin, opname)
if isinstance(other, (datetime, np.datetime64, compat.string_types)):
if isinstance(other, datetime):
# GH#18435 strings get a pass from tzawareness compat
self._assert_tzawareness_compat(other)
other = _to_m8(other, tz=self.tz)
result = meth(self, other)
if isna(other):
result.fill(nat_result)
else:
if isinstance(other, list):
other = type(self)(other)
elif not isinstance(other, (np.ndarray, ABCIndexClass, ABCSeries)):
# Following Timestamp convention, __eq__ is all-False
# and __ne__ is all True, others raise TypeError.
if opname == '__eq__':
return np.zeros(shape=self.shape, dtype=bool)
elif opname == '__ne__':
return np.ones(shape=self.shape, dtype=bool)
raise TypeError('%s type object %s' %
(type(other), str(other)))
if is_datetimelike(other):
self._assert_tzawareness_compat(other)
result = meth(self, np.asarray(other))
result = com.values_from_object(result)
# Make sure to pass an array to result[...]; indexing with
# Series breaks with older version of numpy
o_mask = np.array(isna(other))
if o_mask.any():
result[o_mask] = nat_result
if self.hasnans:
result[self._isnan] = nat_result
return result
def wrapper(self, other):
meth = getattr(dtl.DatetimeLikeArrayMixin, opname)
if isinstance(other, (datetime, np.datetime64, compat.string_types)):
if isinstance(other, datetime):
# GH#18435 strings get a pass from tzawareness compat
self._assert_tzawareness_compat(other)
other = _to_m8(other, tz=self.tz)
result = meth(self, other)
if isna(other):
result.fill(nat_result)
else:
if isinstance(other, list):
other = type(self)(other)
elif not isinstance(other, (np.ndarray, ABCIndexClass, ABCSeries)):
# Following Timestamp convention, __eq__ is all-False
# and __ne__ is all True, others raise TypeError.
if opname == '__eq__':
return np.zeros(shape=self.shape, dtype=bool)
elif opname == '__ne__':
return np.ones(shape=self.shape, dtype=bool)
raise TypeError('%s type object %s' %
(type(other), str(other)))
if is_datetimelike(other):
self._assert_tzawareness_compat(other)
result = meth(self, np.asarray(other))
result = com._values_from_object(result)
# Make sure to pass an array to result[...]; indexing with
# Series breaks with older version of numpy
o_mask = np.array(isna(other))
if o_mask.any():
result[o_mask] = nat_result
if self.hasnans:
result[self._isnan] = nat_result
return result
