def __sub__(self, other): other = lib.item_from_zerodim(other) if isinstance(other, (ABCSeries, ABCDataFrame)): return NotImplemented # scalar others elif other is NaT: result = self._sub_nat() elif isinstance(other, (Tick, timedelta, np.timedelta64)): result = self._add_delta(-other) elif isinstance(other, DateOffset): # specifically _not_ a Tick result = self._add_offset(-other) elif isinstance(other, (datetime, np.datetime64)): result = self._sub_datetimelike_scalar(other) elif lib.is_integer(other): # This check must come after the check for np.timedelta64 # as is_integer returns True for these if not is_period_dtype(self): maybe_integer_op_deprecated(self) result = self._time_shift(-other) elif isinstance(other, Period): result = self._sub_period(other) # array-like others elif is_timedelta64_dtype(other): # TimedeltaIndex, ndarray[timedelta64] result = self._add_delta(-other) elif is_offsetlike(other): # Array/Index of DateOffset objects result = self._addsub_offset_array(other, operator.sub) elif is_datetime64_dtype(other) or is_datetime64tz_dtype(other): # DatetimeIndex, ndarray[datetime64] result = self._sub_datetime_arraylike(other) elif is_period_dtype(other): # PeriodIndex result = self._sub_period_array(other) elif is_integer_dtype(other): if not is_period_dtype(self): maybe_integer_op_deprecated(self) result = self._addsub_int_array(other, operator.sub) elif isinstance(other, ABCIndexClass): raise TypeError("cannot subtract {cls} and {typ}".format( cls=type(self).__name__, typ=type(other).__name__)) elif is_float_dtype(other): # Explicitly catch invalid dtypes raise TypeError("cannot subtract {dtype}-dtype from {cls}".format( dtype=other.dtype, cls=type(self).__name__)) elif is_extension_array_dtype(other): # Categorical op will raise; defer explicitly return NotImplemented else: # pragma: no cover return NotImplemented if is_timedelta64_dtype(result) and isinstance(result, np.ndarray): from pandas.core.arrays import TimedeltaArrayMixin # TODO: infer freq? return TimedeltaArrayMixin(result) return result
def __sub__(self, other): other = lib.item_from_zerodim(other) if isinstance(other, (ABCSeries, ABCDataFrame)): return NotImplemented # scalar others elif other is NaT: result = self._sub_nat() elif isinstance(other, (Tick, timedelta, np.timedelta64)): result = self._add_delta(-other) elif isinstance(other, DateOffset): # specifically _not_ a Tick result = self._add_offset(-other) elif isinstance(other, (datetime, np.datetime64)): result = self._sub_datetimelike_scalar(other) elif lib.is_integer(other): # This check must come after the check for np.timedelta64 # as is_integer returns True for these maybe_integer_op_deprecated(self) result = self._time_shift(-other) elif isinstance(other, Period): result = self._sub_period(other) # array-like others elif is_timedelta64_dtype(other): # TimedeltaIndex, ndarray[timedelta64] result = self._add_delta(-other) elif is_offsetlike(other): # Array/Index of DateOffset objects result = self._addsub_offset_array(other, operator.sub) elif is_datetime64_dtype(other) or is_datetime64tz_dtype(other): # DatetimeIndex, ndarray[datetime64] result = self._sub_datetime_arraylike(other) elif is_period_dtype(other): # PeriodIndex result = self._sub_period_array(other) elif is_integer_dtype(other): maybe_integer_op_deprecated(self) result = self._addsub_int_array(other, operator.sub) elif isinstance(other, ABCIndexClass): raise TypeError("cannot subtract {cls} and {typ}" .format(cls=type(self).__name__, typ=type(other).__name__)) elif is_float_dtype(other): # Explicitly catch invalid dtypes raise TypeError("cannot subtract {dtype}-dtype from {cls}" .format(dtype=other.dtype, cls=type(self).__name__)) elif is_extension_array_dtype(other): # Categorical op will raise; defer explicitly return NotImplemented else: # pragma: no cover return NotImplemented if is_timedelta64_dtype(result) and isinstance(result, np.ndarray): from pandas.core.arrays import TimedeltaArrayMixin # TODO: infer freq? return TimedeltaArrayMixin(result) return result
def __add__(self, other): other = lib.item_from_zerodim(other) if isinstance(other, (ABCSeries, ABCDataFrame)): return NotImplemented # scalar others elif other is NaT: result = self._add_nat() elif isinstance(other, (Tick, timedelta, np.timedelta64)): result = self._add_delta(other) elif isinstance(other, DateOffset): # specifically _not_ a Tick result = self._add_offset(other) elif isinstance(other, (datetime, np.datetime64)): result = self._add_datetimelike_scalar(other) elif lib.is_integer(other): # This check must come after the check for np.timedelta64 # as is_integer returns True for these if not is_period_dtype(self): maybe_integer_op_deprecated(self) result = self._time_shift(other) # array-like others elif is_timedelta64_dtype(other): # TimedeltaIndex, ndarray[timedelta64] result = self._add_delta(other) elif is_offsetlike(other): # Array/Index of DateOffset objects result = self._addsub_offset_array(other, operator.add) elif is_datetime64_dtype(other) or is_datetime64tz_dtype(other): # DatetimeIndex, ndarray[datetime64] return self._add_datetime_arraylike(other) elif is_integer_dtype(other): if not is_period_dtype(self): maybe_integer_op_deprecated(self) result = self._addsub_int_array(other, operator.add) elif is_float_dtype(other): # Explicitly catch invalid dtypes raise TypeError("cannot add {dtype}-dtype to {cls}" .format(dtype=other.dtype, cls=type(self).__name__)) elif is_period_dtype(other): # if self is a TimedeltaArray and other is a PeriodArray with # a timedelta-like (i.e. Tick) freq, this operation is valid. # Defer to the PeriodArray implementation. # In remaining cases, this will end up raising TypeError. return NotImplemented elif is_extension_array_dtype(other): # Categorical op will raise; defer explicitly return NotImplemented else: # pragma: no cover return NotImplemented if is_timedelta64_dtype(result) and isinstance(result, np.ndarray): from pandas.core.arrays import TimedeltaArrayMixin # TODO: infer freq? return TimedeltaArrayMixin(result) return result
def __add__(self, other): other = lib.item_from_zerodim(other) if isinstance(other, (ABCSeries, ABCDataFrame)): return NotImplemented # scalar others elif other is NaT: result = self._add_nat() elif isinstance(other, (Tick, timedelta, np.timedelta64)): result = self._add_delta(other) elif isinstance(other, DateOffset): # specifically _not_ a Tick result = self._add_offset(other) elif isinstance(other, (datetime, np.datetime64)): result = self._add_datetimelike_scalar(other) elif lib.is_integer(other): # This check must come after the check for np.timedelta64 # as is_integer returns True for these maybe_integer_op_deprecated(self) result = self._time_shift(other) # array-like others elif is_timedelta64_dtype(other): # TimedeltaIndex, ndarray[timedelta64] result = self._add_delta(other) elif is_offsetlike(other): # Array/Index of DateOffset objects result = self._addsub_offset_array(other, operator.add) elif is_datetime64_dtype(other) or is_datetime64tz_dtype(other): # DatetimeIndex, ndarray[datetime64] return self._add_datetime_arraylike(other) elif is_integer_dtype(other): maybe_integer_op_deprecated(self) result = self._addsub_int_array(other, operator.add) elif is_float_dtype(other): # Explicitly catch invalid dtypes raise TypeError("cannot add {dtype}-dtype to {cls}" .format(dtype=other.dtype, cls=type(self).__name__)) elif is_period_dtype(other): # if self is a TimedeltaArray and other is a PeriodArray with # a timedelta-like (i.e. Tick) freq, this operation is valid. # Defer to the PeriodArray implementation. # In remaining cases, this will end up raising TypeError. return NotImplemented elif is_extension_array_dtype(other): # Categorical op will raise; defer explicitly return NotImplemented else: # pragma: no cover return NotImplemented if is_timedelta64_dtype(result) and isinstance(result, np.ndarray): from pandas.core.arrays import TimedeltaArrayMixin # TODO: infer freq? return TimedeltaArrayMixin(result) return result