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BUG: Index constructor does not maintain CategoricalDtype #19048

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Merged
merged 1 commit into from
Jan 3, 2018
Merged

BUG: Index constructor does not maintain CategoricalDtype #19048

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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.23.0.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -300,6 +300,7 @@ Conversion
- Bug in :class:`FY5253` where ``datetime`` addition and subtraction incremented incorrectly for dates on the year-end but not normalized to midnight (:issue:`18854`)
- Bug in :class:`DatetimeIndex` where adding or subtracting an array-like of ``DateOffset`` objects either raised (``np.array``, ``pd.Index``) or broadcast incorrectly (``pd.Series``) (:issue:`18849`)
- Bug in :class:`Series` floor-division where operating on a scalar ``timedelta`` raises an exception (:issue:`18846`)
- Bug in :class:`Index` constructor with ``dtype=CategoricalDtype(...)`` where ``categories`` and ``ordered`` are not maintained (issue:`19032`)


Indexing
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8 changes: 4 additions & 4 deletions pandas/core/indexes/base.py
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Expand Up @@ -197,13 +197,13 @@ def __new__(cls, data=None, dtype=None, copy=False, name=None,
# categorical
if is_categorical_dtype(data) or is_categorical_dtype(dtype):
from .category import CategoricalIndex
return CategoricalIndex(data, copy=copy, name=name, **kwargs)
return CategoricalIndex(data, dtype=dtype, copy=copy, name=name,
**kwargs)

# interval
if is_interval_dtype(data):
if is_interval_dtype(data) or is_interval_dtype(dtype):
from .interval import IntervalIndex
return IntervalIndex.from_intervals(data, name=name,
copy=copy)
return IntervalIndex(data, dtype=dtype, name=name, copy=copy)
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The IntervalIndex changes are more about future proofing; the dtype kwarg currently doesn't do anything for IntervalIndex, so there aren't really any tests that can be added. I plan to create a PR to allow conversion between subtypes and initializing with non-inferred subtype (e.g. interval[int64] to interval[float64]) where I believe the same issue will come into play, so figured I'd put this code in place now while it's fresh on my mind.

Also, switched from IntervalIndex.from_intervals to the IntervalIndex constructor since the constructor does everything from_intervals does, but has more features and better testing. Would eventually like to either remove from_intervals or just redirect it to the constructor.


# index-like
elif isinstance(data, (np.ndarray, Index, ABCSeries)):
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29 changes: 19 additions & 10 deletions pandas/tests/indexes/test_category.py
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Expand Up @@ -137,18 +137,27 @@ def test_construction_with_categorical_dtype(self):
data, cats, ordered = 'a a b b'.split(), 'c b a'.split(), True
dtype = CategoricalDtype(categories=cats, ordered=ordered)

result = pd.CategoricalIndex(data, dtype=dtype)
expected = pd.CategoricalIndex(data, categories=cats,
ordered=ordered)
result = CategoricalIndex(data, dtype=dtype)
expected = CategoricalIndex(data, categories=cats, ordered=ordered)
tm.assert_index_equal(result, expected, exact=True)

# error to combine categories or ordered and dtype keywords args
with pytest.raises(ValueError, match="Cannot specify both `dtype` and "
"`categories` or `ordered`."):
pd.CategoricalIndex(data, categories=cats, dtype=dtype)
with pytest.raises(ValueError, match="Cannot specify both `dtype` and "
"`categories` or `ordered`."):
pd.CategoricalIndex(data, ordered=ordered, dtype=dtype)
# GH 19032
result = Index(data, dtype=dtype)
tm.assert_index_equal(result, expected, exact=True)

# error when combining categories/ordered and dtype kwargs
msg = 'Cannot specify both `dtype` and `categories` or `ordered`.'
with pytest.raises(ValueError, match=msg):
CategoricalIndex(data, categories=cats, dtype=dtype)

with pytest.raises(ValueError, match=msg):
Index(data, categories=cats, dtype=dtype)

with pytest.raises(ValueError, match=msg):
CategoricalIndex(data, ordered=ordered, dtype=dtype)

with pytest.raises(ValueError, match=msg):
Index(data, ordered=ordered, dtype=dtype)

def test_create_categorical(self):
# https://github.com/pandas-dev/pandas/pull/17513
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