DEPR: Remove NumericIndex (#51139)

Author: topper-123

pandas/_testing/asserters.py

@@ -363,14 +363,7 @@ def is_class_equiv(idx: Index) -> bool:
         This only checks class equivalence. There is a separate check that the
         dtype is int64.
         """
-        from pandas.core.indexes.numeric import NumericIndex
-
-        if isinstance(idx, RangeIndex):
-            return True
-        elif type(idx) is Index or type(idx) is NumericIndex:
-            return True
-        else:
-            return False
+        return type(idx) is Index or isinstance(idx, RangeIndex)
 
     if type(left) == type(right):
         return

pandas/core/algorithms.py

@@ -1313,8 +1313,7 @@ def __init__(self, obj: DataFrame, n: int, keep: str, columns: IndexLabel) -> No
         self.columns = columns
 
     def compute(self, method: str) -> DataFrame:
-
-        from pandas.core.api import NumericIndex
+        from pandas.core.api import Index
 
         n = self.n
         frame = self.obj
@@ -1342,7 +1341,7 @@ def get_indexer(current_indexer, other_indexer):
         original_index = frame.index
         cur_frame = frame = frame.reset_index(drop=True)
         cur_n = n
-        indexer = NumericIndex([], dtype=np.int64)
+        indexer = Index([], dtype=np.int64)
 
         for i, column in enumerate(columns):
             # For each column we apply method to cur_frame[column].

pandas/core/api.py

@@ -54,7 +54,6 @@
     Index,
     IntervalIndex,
     MultiIndex,
-    NumericIndex,
     PeriodIndex,
     RangeIndex,
     TimedeltaIndex,
@@ -117,7 +116,6 @@
     "NaT",
     "notna",
     "notnull",
-    "NumericIndex",
     "Period",
     "PeriodDtype",
     "PeriodIndex",

pandas/core/base.py

@@ -1161,7 +1161,7 @@ def factorize(
             uniques = uniques.astype(np.float32)
 
         if isinstance(self, ABCIndex):
-            # preserve e.g. NumericIndex, preserve MultiIndex
+            # preserve e.g. MultiIndex
             uniques = self._constructor(uniques)
         else:
             from pandas import Index

pandas/core/dtypes/generic.py

@@ -93,7 +93,6 @@ def _subclasscheck(cls, inst) -> bool:
         {
             "index",
             "rangeindex",
-            "numericindex",
             "multiindex",
             "datetimeindex",
             "timedeltaindex",

pandas/core/indexes/api.py

@@ -26,7 +26,6 @@
 from pandas.core.indexes.datetimes import DatetimeIndex
 from pandas.core.indexes.interval import IntervalIndex
 from pandas.core.indexes.multi import MultiIndex
-from pandas.core.indexes.numeric import NumericIndex
 from pandas.core.indexes.period import PeriodIndex
 from pandas.core.indexes.range import RangeIndex
 from pandas.core.indexes.timedeltas import TimedeltaIndex
@@ -46,7 +45,6 @@
 __all__ = [
     "Index",
     "MultiIndex",
-    "NumericIndex",
     "CategoricalIndex",
     "IntervalIndex",
     "RangeIndex",

pandas/core/indexes/base.py

@@ -317,7 +317,6 @@ class Index(IndexOpsMixin, PandasObject):
     DatetimeIndex : Index of datetime64 data.
     TimedeltaIndex : Index of timedelta64 data.
     PeriodIndex : Index of Period data.
-    NumericIndex : Index of numpy int/uint/float data.
 
     Notes
     -----
@@ -539,7 +538,6 @@ def __new__(
 
         klass = cls._dtype_to_subclass(arr.dtype)
 
-        # _ensure_array _may_ be unnecessary once NumericIndex etc are gone
         arr = klass._ensure_array(arr, arr.dtype, copy=False)
         return klass._simple_new(arr, name)
 
@@ -596,18 +594,11 @@ def _dtype_to_subclass(cls, dtype: DtypeObj):
 
             return TimedeltaIndex
 
-        elif dtype.kind in ["i", "f", "u"]:
-            from pandas.core.api import NumericIndex
-
-            return NumericIndex
-
         elif dtype.kind == "O":
             # NB: assuming away MultiIndex
             return Index
 
-        elif issubclass(
-            dtype.type, (str, bool, np.bool_, complex, np.complex64, np.complex128)
-        ):
+        elif issubclass(dtype.type, str) or is_numeric_dtype(dtype):
             return Index
 
         raise NotImplementedError(dtype)
@@ -1207,10 +1198,6 @@ def __repr__(self) -> str_t:
         Return a string representation for this object.
         """
         klass_name = type(self).__name__
-        from pandas.core.indexes.numeric import NumericIndex
-
-        if type(self) is NumericIndex:
-            klass_name = "Index"
         data = self._format_data()
         attrs = self._format_attrs()
         space = self._format_space()
@@ -5375,6 +5362,7 @@ def identical(self, other) -> bool:
                 for c in self._comparables
             )
             and type(self) == type(other)
+            and self.dtype == other.dtype
         )
 
     @final

pandas/core/indexes/numeric.py

@@ -49,13 +49,12 @@
     Index,
     maybe_extract_name,
 )
-from pandas.core.indexes.numeric import NumericIndex
 from pandas.core.ops.common import unpack_zerodim_and_defer
 
 _empty_range = range(0)
 
 
-class RangeIndex(NumericIndex):
+class RangeIndex(Index):
     """
     Immutable Index implementing a monotonic integer range.
 
@@ -196,7 +195,7 @@ def _validate_dtype(cls, dtype: Dtype | None) -> None:
     @cache_readonly
     def _constructor(self) -> type[Index]:  # type: ignore[override]
         """return the class to use for construction"""
-        return NumericIndex
+        return Index
 
     # error: Signature of "_data" incompatible with supertype "Index"
     @cache_readonly
@@ -408,7 +407,7 @@ def _shallow_copy(self, values, name: Hashable = no_default):
             new_range = range(values[0], values[-1] + diff, diff)
             return type(self)._simple_new(new_range, name=name)
         else:
-            return NumericIndex._simple_new(values, name=name)
+            return self._constructor._simple_new(values, name=name)
 
     def _view(self: RangeIndex) -> RangeIndex:
         result = type(self)._simple_new(self._range, name=self._name)

pandas/core/indexes/range.py

@@ -165,7 +165,7 @@
     >>> s = pd.Series(text_values, index=int_values)
     >>> s.info()
     <class 'pandas.core.series.Series'>
-    NumericIndex: 5 entries, 1 to 5
+    Index: 5 entries, 1 to 5
     Series name: None
     Non-Null Count  Dtype
     --------------  -----
@@ -177,7 +177,7 @@
 
     >>> s.info(verbose=False)
     <class 'pandas.core.series.Series'>
-    NumericIndex: 5 entries, 1 to 5
+    Index: 5 entries, 1 to 5
     dtypes: object(1)
     memory usage: 80.0+ bytes
 

pandas/io/formats/info.py

@@ -737,7 +737,7 @@ def test_getitem_setitem_float_labels(self, using_array_manager):
 
         # positional slicing only via iloc!
         msg = (
-            "cannot do positional indexing on NumericIndex with "
+            "cannot do positional indexing on Index with "
             r"these indexers \[1.0\] of type float"
         )
         with pytest.raises(TypeError, match=msg):

pandas/tests/frame/indexing/test_indexing.py

@@ -146,7 +146,6 @@ def test_setting_names_from_levels_raises():
         new.index.name = "bar"
 
     assert pd.Index._no_setting_name is False
-    assert pd.core.api.NumericIndex._no_setting_name is False
     assert pd.RangeIndex._no_setting_name is False
 
 

pandas/tests/indexes/multi/test_names.py

@@ -43,8 +43,6 @@ def float_index(self, dtype):
         return self._index_cls([0.0, 2.5, 5.0, 7.5, 10.0], dtype=dtype)
 
     def test_repr_roundtrip(self, index):
-        from pandas.core.api import NumericIndex  # noqa: F401
-
         tm.assert_index_equal(eval(repr(index)), index, exact=True)
 
     def check_coerce(self, a, b, is_float_index=True):

pandas/tests/indexes/numeric/test_numeric.py

@@ -154,8 +154,6 @@ def test_str(self, index):
         # test the string repr
         index.name = "foo"
         assert "'foo'" in str(index)
-        if type(index).__name__ == "NumericIndex":  # TODO: remove NumericIndex
-            return
         assert type(index).__name__ in str(index)
 
 

pandas/tests/indexes/test_any_index.py

@@ -31,7 +31,6 @@
     RangeIndex,
 )
 import pandas._testing as tm
-from pandas.core.api import NumericIndex
 
 
 class TestCommon:
@@ -431,7 +430,7 @@ def test_hasnans_isnans(self, index_flat):
 
         if len(index) == 0:
             return
-        elif isinstance(index, NumericIndex) and is_integer_dtype(index.dtype):
+        elif is_integer_dtype(index.dtype):
             return
         elif index.dtype == bool:
             # values[1] = np.nan below casts to True!

pandas/tests/indexes/test_common.py

@@ -646,7 +646,7 @@ def test_selection_api_validation():
     # non DatetimeIndex
     msg = (
         "Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, "
-        "but got an instance of 'NumericIndex'"
+        "but got an instance of 'Index'"
     )
     with pytest.raises(TypeError, match=msg):
         df.resample("2D", level="v")