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CLN: Follow-up to #24100 (#24116)
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@jbrockmendel @jreback
jbrockmendel authored and jreback committed Dec 5, 2018
1 parent 8ea7744 commit 2643721
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Showing 6 changed files with 178 additions and 207 deletions.
314 changes: 150 additions & 164 deletions pandas/core/arrays/datetimelike.py
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Original file line number Diff line number Diff line change
Expand Up @@ -854,173 +854,159 @@ def _time_shift(self, periods, freq=None):
return self._generate_range(start=start, end=end, periods=None,
freq=self.freq)

@classmethod
def _add_datetimelike_methods(cls):
"""
add in the datetimelike methods (as we may have to override the
superclass)
"""
def __add__(self, other):
other = lib.item_from_zerodim(other)
if isinstance(other, (ABCSeries, ABCDataFrame)):
return NotImplemented

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
# 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

cls.__add__ = __add__

def __radd__(self, other):
# alias for __add__
return self.__add__(other)
cls.__radd__ = __radd__

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
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 __radd__(self, other):
# alias for __add__
return self.__add__(other)

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 __rsub__(self, other):
if is_datetime64_dtype(other) and is_timedelta64_dtype(self):
# ndarray[datetime64] cannot be subtracted from self, so
# we need to wrap in DatetimeArray/Index and flip the operation
if not isinstance(other, DatetimeLikeArrayMixin):
# Avoid down-casting DatetimeIndex
from pandas.core.arrays import DatetimeArrayMixin
other = DatetimeArrayMixin(other)
return other - self
elif (is_datetime64_any_dtype(self) and hasattr(other, 'dtype') and
not is_datetime64_any_dtype(other)):
# GH#19959 datetime - datetime is well-defined as timedelta,
# but any other type - datetime is not well-defined.
raise TypeError("cannot subtract {cls} from {typ}"
.format(cls=type(self).__name__,
typ=type(other).__name__))
elif is_period_dtype(self) and is_timedelta64_dtype(other):
# TODO: Can we simplify/generalize these cases at all?
raise TypeError("cannot subtract {cls} from {dtype}"
.format(cls=type(self).__name__,
dtype=other.dtype))
return -(self - other)

# FIXME: DTA/TDA/PA inplace methods should actually be inplace, GH#24115
def __iadd__(self, other):
# alias for __add__
return self.__add__(other)

cls.__sub__ = __sub__

def __rsub__(self, other):
if is_datetime64_dtype(other) and is_timedelta64_dtype(self):
# ndarray[datetime64] cannot be subtracted from self, so
# we need to wrap in DatetimeArray/Index and flip the operation
if not isinstance(other, DatetimeLikeArrayMixin):
# Avoid down-casting DatetimeIndex
from pandas.core.arrays import DatetimeArrayMixin
other = DatetimeArrayMixin(other)
return other - self
elif (is_datetime64_any_dtype(self) and hasattr(other, 'dtype') and
not is_datetime64_any_dtype(other)):
# GH#19959 datetime - datetime is well-defined as timedelta,
# but any other type - datetime is not well-defined.
raise TypeError("cannot subtract {cls} from {typ}"
.format(cls=type(self).__name__,
typ=type(other).__name__))
elif is_period_dtype(self) and is_timedelta64_dtype(other):
# TODO: Can we simplify/generalize these cases at all?
raise TypeError("cannot subtract {cls} from {dtype}"
.format(cls=type(self).__name__,
dtype=other.dtype))
return -(self - other)
cls.__rsub__ = __rsub__

def __iadd__(self, other):
# alias for __add__
return self.__add__(other)
cls.__iadd__ = __iadd__

def __isub__(self, other):
# alias for __sub__
return self.__sub__(other)
cls.__isub__ = __isub__
def __isub__(self, other):
# alias for __sub__
return self.__sub__(other)

# --------------------------------------------------------------
# Comparison Methods
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1 change: 0 additions & 1 deletion pandas/core/arrays/datetimes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1438,7 +1438,6 @@ def to_julian_date(self):


DatetimeArrayMixin._add_comparison_ops()
DatetimeArrayMixin._add_datetimelike_methods()


# -------------------------------------------------------------------
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1 change: 0 additions & 1 deletion pandas/core/arrays/period.py
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Original file line number Diff line number Diff line change
Expand Up @@ -830,7 +830,6 @@ def _values_for_argsort(self):


PeriodArray._add_comparison_ops()
PeriodArray._add_datetimelike_methods()


# -------------------------------------------------------------------
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1 change: 0 additions & 1 deletion pandas/core/arrays/timedeltas.py
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Original file line number Diff line number Diff line change
Expand Up @@ -734,7 +734,6 @@ def f(x):


TimedeltaArrayMixin._add_comparison_ops()
TimedeltaArrayMixin._add_datetimelike_methods()


# ---------------------------------------------------------------------
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13 changes: 0 additions & 13 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -463,19 +463,6 @@ def __init__(self, data=None, index=None, columns=None, dtype=None,

NDFrame.__init__(self, mgr, fastpath=True)

def _init_dict(self, data, index, columns, dtype=None):
"""
Segregate Series based on type and coerce into matrices.
Needs to handle a lot of exceptional cases.
"""
return init_dict(data, index, columns, dtype=dtype)
# TODO: Can we get rid of this as a method?

def _init_ndarray(self, values, index, columns, dtype=None, copy=False):
# input must be a ndarray, list, Series, index
return init_ndarray(values, index, columns, dtype=dtype, copy=copy)
# TODO: can we just get rid of this as a method?

# ----------------------------------------------------------------------

@property
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