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REF: move astype to ExtensionIndex #30800

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Merged
merged 1 commit into from
Jan 8, 2020
Merged

REF: move astype to ExtensionIndex #30800

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10 changes: 2 additions & 8 deletions pandas/core/indexes/category.py
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Original file line number Diff line number Diff line change
Expand Up @@ -190,13 +190,7 @@ def _engine_type(self):
# Constructors

def __new__(
cls,
data=None,
categories=None,
ordered=None,
dtype=None,
copy=False,
name=None,
cls, data=None, categories=None, ordered=None, dtype=None, copy=False, name=None
):

dtype = CategoricalDtype._from_values_or_dtype(data, categories, ordered, dtype)
Expand Down Expand Up @@ -414,7 +408,7 @@ def astype(self, dtype, copy=True):
if dtype == self.dtype:
return self.copy() if copy else self

return super().astype(dtype=dtype, copy=copy)
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Is there a consistent reason to use Index instead of super?

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IIRC i got test failures without this change

return Index.astype(self, dtype=dtype, copy=copy)

@cache_readonly
def _isnan(self):
Expand Down
12 changes: 0 additions & 12 deletions pandas/core/indexes/datetimelike.py
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Expand Up @@ -542,18 +542,6 @@ def _concat_same_dtype(self, to_concat, name):

return self._simple_new(new_data, **attribs)

@Appender(_index_shared_docs["astype"])
def astype(self, dtype, copy=True):
if is_dtype_equal(self.dtype, dtype) and copy is False:
# Ensure that self.astype(self.dtype) is self
return self

new_values = self._data.astype(dtype, copy=copy)

# pass copy=False because any copying will be done in the
# _data.astype call above
return Index(new_values, dtype=new_values.dtype, name=self.name, copy=False)

def shift(self, periods=1, freq=None):
"""
Shift index by desired number of time frequency increments.
Expand Down
13 changes: 12 additions & 1 deletion pandas/core/indexes/extension.py
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Expand Up @@ -6,7 +6,7 @@
from pandas.compat.numpy import function as nv
from pandas.util._decorators import cache_readonly

from pandas.core.dtypes.common import ensure_platform_int
from pandas.core.dtypes.common import ensure_platform_int, is_dtype_equal
from pandas.core.dtypes.generic import ABCSeries

from pandas.core.arrays import ExtensionArray
Expand Down Expand Up @@ -192,3 +192,14 @@ def _get_unique_index(self, dropna=False):
if dropna and self.hasnans:
result = result[~result.isna()]
return self._shallow_copy(result)

def astype(self, dtype, copy=True):
if is_dtype_equal(self.dtype, dtype) and copy is False:
# Ensure that self.astype(self.dtype) is self
return self

new_values = self._data.astype(dtype, copy=copy)

# pass copy=False because any copying will be done in the
# _data.astype call above
return Index(new_values, dtype=new_values.dtype, name=self.name, copy=False)
2 changes: 1 addition & 1 deletion pandas/core/indexes/interval.py
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Expand Up @@ -426,7 +426,7 @@ def astype(self, dtype, copy=True):
new_values = self.values.astype(dtype, copy=copy)
if is_interval_dtype(new_values):
return self._shallow_copy(new_values.left, new_values.right)
return super().astype(dtype, copy=copy)
return Index.astype(self, dtype, copy=copy)

@property
def inferred_type(self) -> str:
Expand Down