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CLN: make CategoricalIndex._create_categorical a classmethod #21618

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Merged
merged 1 commit into from
Jun 25, 2018
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CLN: make CategoricalIndex._create_categorical a classmethod #21618

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3 changes: 2 additions & 1 deletion pandas/core/indexes/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1130,7 +1130,8 @@ def to_frame(self, index=True):
"""

from pandas import DataFrame
result = DataFrame(self._shallow_copy(), columns=[self.name or 0])
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@topper-123 topper-123 Jun 24, 2018 •
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_shallow_copy does not guarantee that _data is copied, so a test fails. to_frame should get a copy, else smething like this could happen:

>>> ci = pd.CategoricalIndex(['a', 'b', 'c'])
>>> df = ci.to_frame()
>>> df.iloc[0] = 'c'
>>> df
   0
c  c  # index label changed!
b  b
c  c

By using self.values.copy() rather than _shallow_copy, this issue is avoided.

name = self.name or 0
result = DataFrame({name: self.values.copy()})

if index:
result.index = self
Expand Down
18 changes: 9 additions & 9 deletions pandas/core/indexes/category.py
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Original file line number Diff line number Diff line change
Expand Up @@ -85,11 +85,11 @@ def __new__(cls, data=None, categories=None, ordered=None, dtype=None,
name = data.name

if isinstance(data, ABCCategorical):
data = cls._create_categorical(cls, data, categories, ordered,
data = cls._create_categorical(data, categories, ordered,
dtype)
elif isinstance(data, CategoricalIndex):
data = data._data
data = cls._create_categorical(cls, data, categories, ordered,
data = cls._create_categorical(data, categories, ordered,
dtype)
else:

Expand All @@ -99,7 +99,7 @@ def __new__(cls, data=None, categories=None, ordered=None, dtype=None,
if data is not None or categories is None:
cls._scalar_data_error(data)
data = []
data = cls._create_categorical(cls, data, categories, ordered,
data = cls._create_categorical(data, categories, ordered,
dtype)

if copy:
Expand Down Expand Up @@ -136,8 +136,8 @@ def _create_from_codes(self, codes, categories=None, ordered=None,
ordered=self.ordered)
return CategoricalIndex(cat, name=name)

@staticmethod
def _create_categorical(self, data, categories=None, ordered=None,
@classmethod
def _create_categorical(cls, data, categories=None, ordered=None,
dtype=None):
"""
*this is an internal non-public method*
Expand All @@ -155,7 +155,7 @@ def _create_categorical(self, data, categories=None, ordered=None,
-------
Categorical
"""
if (isinstance(data, (ABCSeries, type(self))) and
if (isinstance(data, (cls, ABCSeries)) and
is_categorical_dtype(data)):
data = data.values

Expand All @@ -179,7 +179,7 @@ def _simple_new(cls, values, name=None, categories=None, ordered=None,
dtype=None, **kwargs):
result = object.__new__(cls)

values = cls._create_categorical(cls, values, categories, ordered,
values = cls._create_categorical(values, categories, ordered,
dtype=dtype)
result._data = values
result.name = name
Expand Down Expand Up @@ -236,7 +236,7 @@ def _is_dtype_compat(self, other):
if not is_list_like(values):
values = [values]
other = CategoricalIndex(self._create_categorical(
self, other, categories=self.categories, ordered=self.ordered))
other, categories=self.categories, ordered=self.ordered))
if not other.isin(values).all():
raise TypeError("cannot append a non-category item to a "
"CategoricalIndex")
Expand Down Expand Up @@ -798,7 +798,7 @@ def _evaluate_compare(self, other):
other = other._values
elif isinstance(other, Index):
other = self._create_categorical(
self, other._values, categories=self.categories,
other._values, categories=self.categories,
ordered=self.ordered)

if isinstance(other, (ABCCategorical, np.ndarray,
Expand Down