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DEPR: remove NumericIndex.__new__ & ._should_fallback_to_positional #51118

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Merged
merged 3 commits into from
Feb 2, 2023
Merged

DEPR: remove NumericIndex.__new__ & ._should_fallback_to_positional #51118

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3cbcff1
DEPR: move NumericIndex._should_fallback_to_positional to Index
topper-123 Feb 2, 2023
71fbd3f
fix pre-commit
topper-123 Feb 2, 2023
91ac9ae
remove NumericIndex.__new__
topper-123 Feb 2, 2023
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2 changes: 2 additions & 0 deletions pandas/core/indexes/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5689,6 +5689,8 @@ def _should_fallback_to_positional(self) -> bool:
"""
Should an integer key be treated as positional?
"""
if isinstance(self.dtype, np.dtype) and self.dtype.kind in ["i", "u", "f"]:
return False
return not self._holds_integer()

_index_shared_docs[
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28 changes: 1 addition & 27 deletions pandas/core/indexes/numeric.py
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@@ -1,33 +1,7 @@
from __future__ import annotations

import numpy as np

from pandas._typing import Dtype
from pandas.util._decorators import (
cache_readonly,
doc,
)

from pandas.core.indexes.base import Index


class NumericIndex(Index):
def __new__(
cls, data=None, dtype: Dtype | None = None, copy: bool = False, name=None
) -> NumericIndex:
# temporary scaffolding, will be removed soon.
if isinstance(data, list) and len(data) == 0:
data = np.array([], dtype=np.int64)
elif isinstance(data, range):
data = np.arange(data.start, data.stop, data.step, dtype=np.int64)
return super().__new__(
cls, data=data, dtype=dtype, copy=copy, name=name
) # type: ignore[return-value]

# ----------------------------------------------------------------
# Indexing Methods

@cache_readonly
@doc(Index._should_fallback_to_positional)
def _should_fallback_to_positional(self) -> bool:
return False
pass
4 changes: 2 additions & 2 deletions pandas/tests/indexes/test_base.py
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Expand Up @@ -486,7 +486,7 @@ def test_fancy(self, simple_index):
@pytest.mark.parametrize("dtype", [np.int_, np.bool_])
def test_empty_fancy(self, index, dtype):
empty_arr = np.array([], dtype=dtype)
empty_index = type(index)([])
empty_index = type(index)([], dtype=index.dtype)

assert index[[]].identical(empty_index)
assert index[empty_arr].identical(empty_index)
Expand All @@ -500,7 +500,7 @@ def test_empty_fancy_raises(self, index):
# DatetimeIndex is excluded, because it overrides getitem and should
# be tested separately.
empty_farr = np.array([], dtype=np.float_)
empty_index = type(index)([])
empty_index = type(index)([], dtype=index.dtype)

assert index[[]].identical(empty_index)
# np.ndarray only accepts ndarray of int & bool dtypes, so should Index
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