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DTA/TDA/PA use self._data instead of self.asi8 for self._ndarray #36171

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Merged
merged 5 commits into from
Sep 7, 2020
Merged

DTA/TDA/PA use self._data instead of self.asi8 for self._ndarray #36171

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9ecda1a
REF: assign _ndarray to _data, not asi8
jbrockmendel Sep 6, 2020
24d28b6
remove comment
jbrockmendel Sep 6, 2020
64e665e
REF: _ndarray use _data instead of asi8
jbrockmendel Sep 6, 2020
0ec876a
REF: implement _rebox_native
jbrockmendel Sep 6, 2020
032c542
update assertion
jbrockmendel Sep 6, 2020
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REF: _ndarray use _data instead of asi8
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@jbrockmendel
jbrockmendel committed Sep 6, 2020
commit 64e665e698e54abdd76c50619cd704c47cee0475
28 changes: 13 additions & 15 deletions pandas/core/arrays/datetimelike.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,7 @@
from pandas.compat import set_function_name
from pandas.compat.numpy import function as nv
from pandas.errors import AbstractMethodError, NullFrequencyError, PerformanceWarning
from pandas.util._decorators import Appender, Substitution
from pandas.util._decorators import Appender, Substitution, cache_readonly
from pandas.util._validators import validate_fillna_kwargs

from pandas.core.dtypes.common import (
Expand Down Expand Up @@ -458,9 +458,7 @@ class DatetimeLikeArrayMixin(
# ------------------------------------------------------------------
# NDArrayBackedExtensionArray compat

# TODO: make this a cache_readonly; need to get around _index_data
# kludge in libreduction
@property
@cache_readonly
def _ndarray(self) -> np.ndarray:
return self._data

Expand Down Expand Up @@ -523,7 +521,7 @@ def __array__(self, dtype=None) -> np.ndarray:
# used for Timedelta/DatetimeArray, overwritten by PeriodArray
if is_object_dtype(dtype):
return np.array(list(self), dtype=object)
return self._data
return self._ndarray

def __getitem__(self, key):
"""
Expand All @@ -533,7 +531,7 @@ def __getitem__(self, key):

if lib.is_integer(key):
# fast-path
result = self._data[key]
result = self._ndarray[key]
if self.ndim == 1:
return self._box_func(result)
return self._simple_new(result, dtype=self.dtype)
Expand All @@ -554,7 +552,7 @@ def __getitem__(self, key):
key = check_array_indexer(self, key)

freq = self._get_getitem_freq(key)
result = self._data[key]
result = self._ndarray[key]
if lib.is_scalar(result):
return self._box_func(result)
return self._simple_new(result, dtype=self.dtype, freq=freq)
Expand Down Expand Up @@ -609,7 +607,7 @@ def __setitem__(

value = self._validate_setitem_value(value)
key = check_array_indexer(self, key)
self._data[key] = value
self._ndarray[key] = value
self._maybe_clear_freq()

def _maybe_clear_freq(self):
Expand Down Expand Up @@ -660,8 +658,8 @@ def astype(self, dtype, copy=True):

def view(self, dtype=None):
if dtype is None or dtype is self.dtype:
return type(self)(self._data, dtype=self.dtype)
return self._data.view(dtype=dtype)
return type(self)(self._ndarray, dtype=self.dtype)
return self._ndarray.view(dtype=dtype)

# ------------------------------------------------------------------
# ExtensionArray Interface
Expand Down Expand Up @@ -702,7 +700,7 @@ def _from_factorized(cls, values, original):
return cls(values, dtype=original.dtype)

def _values_for_argsort(self):
return self._data
return self._ndarray

# ------------------------------------------------------------------
# Validation Methods
Expand Down Expand Up @@ -954,9 +952,9 @@ def value_counts(self, dropna=False):
from pandas import Index, Series

if dropna:
values = self[~self.isna()]._data
values = self[~self.isna()]._ndarray
else:
values = self._data
values = self._ndarray

cls = type(self)

Expand Down Expand Up @@ -1047,9 +1045,9 @@ def fillna(self, value=None, method=None, limit=None):
else:
func = missing.backfill_1d

values = self._data
values = self._ndarray
if not is_period_dtype(self.dtype):
# For PeriodArray self._data is i8, which gets copied
# For PeriodArray self._ndarray is i8, which gets copied
# by `func`. Otherwise we need to make a copy manually
# to avoid modifying `self` in-place.
values = values.copy()
Expand Down