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Merged
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Dec 15, 2019
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CLN: various lgtm.com cleanups #30258

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1 change: 0 additions & 1 deletion pandas/core/apply.py
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Expand Up @@ -320,7 +320,6 @@ def apply_series_generator(self) -> Tuple[ResType, "Index"]:
series_gen = self.series_generator
res_index = self.result_index

i = None
keys = []
results = {}
if self.ignore_failures:
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1 change: 0 additions & 1 deletion pandas/core/arrays/datetimes.py
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Expand Up @@ -2109,7 +2109,6 @@ def _validate_dt64_dtype(dtype):
dtype = pandas_dtype(dtype)
if is_dtype_equal(dtype, np.dtype("M8")):
# no precision, disallowed GH#24806
dtype = _NS_DTYPE
msg = (
"Passing in 'datetime64' dtype with no precision is not allowed. "
"Please pass in 'datetime64[ns]' instead."
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3 changes: 2 additions & 1 deletion pandas/core/arrays/integer.py
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Expand Up @@ -78,7 +78,8 @@ def itemsize(self):

@classmethod
def construct_array_type(cls):
"""Return the array type associated with this dtype
"""
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Is this docstring not inherited from the base class?

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not as far as I'm aware. Should it be?

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@simonjayhawkins simonjayhawkins Dec 13, 2019 •
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It looks like inspect.getdoc(object) https://docs.python.org/3/library/inspect.html?highlight=inspect#inspect.getdoc could get the baseclass docstring.

I'm using VSCode and not showing baseclass docstring when no docstring exists on derived class.

_IntegerDtype().construct_array_type.__doc__ returns None if no docstring exists on derived class but help(_IntegerDtype().construct_array_type) does show the inherited doctstring.

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ok this is odd then I agree with @TomAugspurger that these should inherit the baseclass, odd that they are not.

Return the array type associated with this dtype.

Returns
-------
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8 changes: 8 additions & 0 deletions pandas/core/arrays/numpy_.py
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Expand Up @@ -79,7 +79,15 @@ def construct_from_string(cls, string):
f"Cannot construct a 'PandasDtype' from '{string}'"
) from err

@classmethod
def construct_array_type(cls):
"""
Return the array type associated with this dtype.

Returns
-------
type
"""
return PandasArray

@property
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7 changes: 7 additions & 0 deletions pandas/core/arrays/sparse/dtype.py
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Expand Up @@ -168,6 +168,13 @@ def __repr__(self) -> str:

@classmethod
def construct_array_type(cls):
"""
Return the array type associated with this dtype.

Returns
-------
type
"""
from .array import SparseArray

return SparseArray
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1 change: 0 additions & 1 deletion pandas/core/arrays/timedeltas.py
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Expand Up @@ -1122,7 +1122,6 @@ def _validate_td64_dtype(dtype):
dtype = pandas_dtype(dtype)
if is_dtype_equal(dtype, np.dtype("timedelta64")):
# no precision disallowed GH#24806
dtype = _TD_DTYPE
msg = (
"Passing in 'timedelta' dtype with no precision is not allowed. "
"Please pass in 'timedelta64[ns]' instead."
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2 changes: 1 addition & 1 deletion pandas/core/dtypes/base.py
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Expand Up @@ -183,7 +183,7 @@ def names(self) -> Optional[List[str]]:
@classmethod
def construct_array_type(cls):
"""
Return the array type associated with this dtype
Return the array type associated with this dtype.

Returns
-------
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15 changes: 11 additions & 4 deletions pandas/core/dtypes/dtypes.py
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Expand Up @@ -486,7 +486,7 @@ def _hash_categories(categories, ordered: Ordered = True) -> int:
@classmethod
def construct_array_type(cls):
"""
Return the array type associated with this dtype
Return the array type associated with this dtype.

Returns
-------
Expand Down Expand Up @@ -668,7 +668,7 @@ def __init__(self, unit="ns", tz=None):
unit = result.unit
tz = result.tz
msg = (
"Passing a dtype alias like 'datetime64[ns, {tz}]' "
f"Passing a dtype alias like 'datetime64[ns, {tz}]' "
"to DatetimeTZDtype is no longer supported. Use "
"'DatetimeTZDtype.construct_from_string()' instead."
)
Expand Down Expand Up @@ -704,7 +704,7 @@ def tz(self):
@classmethod
def construct_array_type(cls):
"""
Return the array type associated with this dtype
Return the array type associated with this dtype.

Returns
-------
Expand Down Expand Up @@ -936,6 +936,13 @@ def is_dtype(cls, dtype) -> bool:

@classmethod
def construct_array_type(cls):
"""
Return the array type associated with this dtype.

Returns
-------
type
"""
from pandas.core.arrays import PeriodArray

return PeriodArray
Expand Down Expand Up @@ -1030,7 +1037,7 @@ def subtype(self):
@classmethod
def construct_array_type(cls):
"""
Return the array type associated with this dtype
Return the array type associated with this dtype.

Returns
-------
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1 change: 0 additions & 1 deletion pandas/core/frame.py
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Expand Up @@ -2606,7 +2606,6 @@ def _ixs(self, i: int, axis: int = 0):
"""
# irow
if axis == 0:
label = self.index[i]
new_values = self._data.fast_xs(i)

# if we are a copy, mark as such
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2 changes: 0 additions & 2 deletions pandas/core/generic.py
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Expand Up @@ -5746,8 +5746,6 @@ def __deepcopy__(self: FrameOrSeries, memo=None) -> FrameOrSeries:
memo, default None
Standard signature. Unused
"""
if memo is None:
memo = {}
return self.copy(deep=True)

def _convert(
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2 changes: 1 addition & 1 deletion pandas/core/groupby/grouper.py
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Expand Up @@ -131,7 +131,7 @@ def _get_grouper(self, obj, validate: bool = True):
"""

self._set_grouper(obj)
self.grouper, exclusions, self.obj = get_grouper(
self.grouper, _, self.obj = get_grouper(
self.obj,
[self.key],
axis=self.axis,
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2 changes: 0 additions & 2 deletions pandas/core/indexes/base.py
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Expand Up @@ -910,8 +910,6 @@ def __deepcopy__(self, memo=None):
memo, default None
Standard signature. Unused
"""
if memo is None:
memo = {}
return self.copy(deep=True)

# --------------------------------------------------------------------
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1 change: 0 additions & 1 deletion pandas/core/internals/blocks.py
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Expand Up @@ -3024,7 +3024,6 @@ def _merge_blocks(blocks, dtype=None, _can_consolidate=True):
if dtype is None:
if len({b.dtype for b in blocks}) != 1:
raise AssertionError("_merge_blocks are invalid!")
dtype = blocks[0].dtype

# FIXME: optimization potential in case all mgrs contain slices and
# combination of those slices is a slice, too.
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2 changes: 0 additions & 2 deletions pandas/core/reshape/reshape.py
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Expand Up @@ -230,11 +230,9 @@ def get_new_values(self):
if needs_i8_conversion(values):
sorted_values = sorted_values.view("i8")
new_values = new_values.view("i8")
name = "int64"
elif is_bool_dtype(values):
sorted_values = sorted_values.astype("object")
new_values = new_values.astype("object")
name = "object"
else:
sorted_values = sorted_values.astype(name, copy=False)

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2 changes: 1 addition & 1 deletion pandas/plotting/_matplotlib/hist.py
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Expand Up @@ -27,7 +27,7 @@ def _args_adjust(self):
values = np.ravel(values)
values = values[~isna(values)]

hist, self.bins = np.histogram(
_, self.bins = np.histogram(
values,
bins=self.bins,
range=self.kwds.get("range", None),
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7 changes: 7 additions & 0 deletions pandas/tests/arrays/test_array.py
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Expand Up @@ -287,6 +287,13 @@ class DecimalDtype2(DecimalDtype):

@classmethod
def construct_array_type(cls):
"""
Return the array type associated with this dtype.

Returns
-------
type
"""
return DecimalArray2


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14 changes: 14 additions & 0 deletions pandas/tests/extension/arrow/arrays.py
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Expand Up @@ -37,6 +37,13 @@ def construct_from_string(cls, string):

@classmethod
def construct_array_type(cls):
"""
Return the array type associated with this dtype.

Returns
-------
type
"""
return ArrowBoolArray

def _is_boolean(self):
Expand All @@ -60,6 +67,13 @@ def construct_from_string(cls, string):

@classmethod
def construct_array_type(cls):
"""
Return the array type associated with this dtype.

Returns
-------
type
"""
return ArrowStringArray


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3 changes: 2 additions & 1 deletion pandas/tests/extension/decimal/array.py
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Expand Up @@ -27,7 +27,8 @@ def __repr__(self) -> str:

@classmethod
def construct_array_type(cls):
"""Return the array type associated with this dtype
"""
Return the array type associated with this dtype.

Returns
-------
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3 changes: 2 additions & 1 deletion pandas/tests/extension/json/array.py
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Expand Up @@ -31,7 +31,8 @@ class JSONDtype(ExtensionDtype):

@classmethod
def construct_array_type(cls):
"""Return the array type associated with this dtype
"""
Return the array type associated with this dtype.

Returns
-------
Expand Down