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REF: Remove DatetimelikeArrayMixin._shallow_copy #23430

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Merged
merged 3 commits into from
Nov 2, 2018
Merged

REF: Remove DatetimelikeArrayMixin._shallow_copy #23430

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6659cff
avoid use of shallow_copy in EA mixins
jbrockmendel Oct 31, 2018
f7c0382
Remove DatetimelikeArrayMixin._shallow_copy
jbrockmendel Oct 31, 2018
e0f02db
simplify usages of shallow_copy in datetimelike indexes
jbrockmendel Oct 31, 2018
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16 changes: 3 additions & 13 deletions pandas/core/arrays/datetimelike.py
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Original file line number Diff line number Diff line change
Expand Up @@ -89,18 +89,6 @@ def _get_attributes_dict(self):
"""return an attributes dict for my class"""
return {k: getattr(self, k, None) for k in self._attributes}

def _shallow_copy(self, values=None, **kwargs):
if values is None:
# Note: slightly different from Index implementation which defaults
# to self.values
values = self._ndarray_values

attributes = self._get_attributes_dict()
attributes.update(kwargs)
if not len(values) and 'dtype' not in kwargs:
attributes['dtype'] = self.dtype
return self._simple_new(values, **attributes)


class DatetimeLikeArrayMixin(ExtensionOpsMixin, AttributesMixin):
"""
Expand Down Expand Up @@ -422,7 +410,9 @@ def _add_nat(self):
# and datetime dtypes
result = np.zeros(len(self), dtype=np.int64)
result.fill(iNaT)
return self._shallow_copy(result, freq=None)
if is_timedelta64_dtype(self):
return type(self)(result, freq=None)
return type(self)(result, tz=self.tz, freq=None)

def _sub_nat(self):
"""Subtract pd.NaT from self"""
Expand Down
4 changes: 2 additions & 2 deletions pandas/core/arrays/datetimes.py
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Expand Up @@ -586,7 +586,7 @@ def tz_convert(self, tz):
'tz_localize to localize')

# No conversion since timestamps are all UTC to begin with
return self._shallow_copy(tz=tz)
return self._simple_new(self.asi8, tz=tz, freq=self.freq)
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Why self.asi8 and not self or self._data here? Simple_new doesn't take M8 values?

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_simple_new(int64values, tz=tz) will get you the same thing as __new__(int64values, tz=tz), but the same is not true with M8 values. I find that really helpful.

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You are referring to the timezone difference you mentioned earlier?

I personally find that very confusing that DatetimeArray(self._data, tz=..) and DatetimeArray(self._data.view(int), tz=..) do not give the same. To the extent possible, I would not repeat this pattern for our Arrays?
(of course, in the DatetimeIndex constructor we cannot just change it, unless we want to deprecate that first).


def tz_localize(self, tz, ambiguous='raise', nonexistent='raise',
errors=None):
Expand Down Expand Up @@ -708,7 +708,7 @@ def tz_localize(self, tz, ambiguous='raise', nonexistent='raise',
self.asi8, tz, ambiguous=ambiguous, nonexistent=nonexistent,
)
new_dates = new_dates.view(_NS_DTYPE)
return self._shallow_copy(new_dates, tz=tz)
return self._simple_new(new_dates, tz=tz, freq=self.freq)

# ----------------------------------------------------------------
# Conversion Methods - Vectorized analogues of Timestamp methods
Expand Down
6 changes: 2 additions & 4 deletions pandas/core/indexes/datetimelike.py
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Expand Up @@ -189,8 +189,7 @@ def _round(self, freq, mode, ambiguous):
result = self._maybe_mask_results(result, fill_value=NaT)

attribs = self._get_attributes_dict()
if 'freq' in attribs:
attribs['freq'] = None
attribs['freq'] = None
if 'tz' in attribs:
attribs['tz'] = None
return self._ensure_localized(
Expand Down Expand Up @@ -640,8 +639,7 @@ def where(self, cond, other=None):
result = np.where(cond, values, other).astype('i8')

result = self._ensure_localized(result, from_utc=True)
return self._shallow_copy(result,
**self._get_attributes_dict())
return self._shallow_copy(result)

def _summary(self, name=None):
"""
Expand Down
2 changes: 2 additions & 0 deletions pandas/core/indexes/datetimes.py
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Expand Up @@ -1134,6 +1134,8 @@ def slice_indexer(self, start=None, end=None, step=None, kind=None):
is_year_end = wrap_field_accessor(DatetimeArrayMixin.is_year_end)
is_leap_year = wrap_field_accessor(DatetimeArrayMixin.is_leap_year)

tz_localize = wrap_array_method(DatetimeArrayMixin.tz_localize, True)
tz_convert = wrap_array_method(DatetimeArrayMixin.tz_convert, True)
to_perioddelta = wrap_array_method(DatetimeArrayMixin.to_perioddelta,
False)
to_period = wrap_array_method(DatetimeArrayMixin.to_period, True)
Expand Down