DEPR: Remove (Int|UInt|Float)64Index (#50908)

* DEPR: Remove (Int|UInt|Float)64Index

* fix pre-commit

* fix stuff

Author: topper-123

pandas/_testing/asserters.py

@@ -75,8 +75,8 @@ def assert_almost_equal(
     right : object
     check_dtype : bool or {'equiv'}, default 'equiv'
         Check dtype if both a and b are the same type. If 'equiv' is passed in,
-        then `RangeIndex` and `Int64Index` are also considered equivalent
-        when doing type checking.
+        then `RangeIndex` and `NumericIndex` with int64 dtype are also considered
+        equivalent when doing type checking.
     rtol : float, default 1e-5
         Relative tolerance.
 
@@ -197,7 +197,7 @@ def assert_index_equal(
     exact : bool or {'equiv'}, default 'equiv'
         Whether to check the Index class, dtype and inferred_type
         are identical. If 'equiv', then RangeIndex can be substituted for
-        Int64Index as well.
+        NumericIndex with an int64 dtype as well.
     check_names : bool, default True
         Whether to check the names attribute.
     check_exact : bool, default True
@@ -511,7 +511,7 @@ def assert_interval_array_equal(
     exact : bool or {'equiv'}, default 'equiv'
         Whether to check the Index class, dtype and inferred_type
         are identical. If 'equiv', then RangeIndex can be substituted for
-        Int64Index as well.
+        NumericIndex with an int64 dtype as well.
     obj : str, default 'IntervalArray'
         Specify object name being compared, internally used to show appropriate
         assertion message

pandas/compat/pickle_compat.py

@@ -94,8 +94,8 @@ def load_reduce(self):
     ("pandas.indexes.base", "_new_Index"): ("pandas.core.indexes.base", "_new_Index"),
     ("pandas.indexes.base", "Index"): ("pandas.core.indexes.base", "Index"),
     ("pandas.indexes.numeric", "Int64Index"): (
-        "pandas.core.indexes.numeric",
-        "Int64Index",
+        "pandas.core.indexes.base",
+        "Index",  # updated in 50775
     ),
     ("pandas.indexes.range", "RangeIndex"): ("pandas.core.indexes.range", "RangeIndex"),
     ("pandas.indexes.multi", "MultiIndex"): ("pandas.core.indexes.multi", "MultiIndex"),
@@ -119,7 +119,7 @@ def load_reduce(self):
         "TimedeltaIndex",
     ),
     ("pandas.indexes.numeric", "Float64Index"): (
-        "pandas.core.indexes.numeric",
+        "pandas.core.indexes.base",
         "Index",  # updated in 50775
     ),
     # 50775, remove Int64Index, UInt64Index & Float64Index from codabase

pandas/conftest.py

@@ -520,7 +520,7 @@ def multiindex_year_month_day_dataframe_random_data():
     """
     tdf = tm.makeTimeDataFrame(100)
     ymd = tdf.groupby([lambda x: x.year, lambda x: x.month, lambda x: x.day]).sum()
-    # use Int64Index, to make sure things work
+    # use int64 Index, to make sure things work
     ymd.index = ymd.index.set_levels([lev.astype("i8") for lev in ymd.index.levels])
     ymd.index.set_names(["year", "month", "day"], inplace=True)
     return ymd

pandas/core/algorithms.py

@@ -1305,7 +1305,7 @@ def __init__(self, obj: DataFrame, n: int, keep: str, columns: IndexLabel) -> No
 
     def compute(self, method: str) -> DataFrame:
 
-        from pandas.core.api import Int64Index
+        from pandas.core.api import NumericIndex
 
         n = self.n
         frame = self.obj
@@ -1333,7 +1333,7 @@ def get_indexer(current_indexer, other_indexer):
         original_index = frame.index
         cur_frame = frame = frame.reset_index(drop=True)
         cur_n = n
-        indexer = Int64Index([])
+        indexer = NumericIndex([], dtype=np.int64)
 
         for i, column in enumerate(columns):
             # For each column we apply method to cur_frame[column].

pandas/core/api.py

@@ -51,16 +51,13 @@
 from pandas.core.indexes.api import (
     CategoricalIndex,
     DatetimeIndex,
-    Float64Index,
     Index,
-    Int64Index,
     IntervalIndex,
     MultiIndex,
     NumericIndex,
     PeriodIndex,
     RangeIndex,
     TimedeltaIndex,
-    UInt64Index,
 )
 from pandas.core.indexes.datetimes import (
     bdate_range,
@@ -101,14 +98,12 @@
     "Flags",
     "Float32Dtype",
     "Float64Dtype",
-    "Float64Index",
     "Grouper",
     "Index",
     "IndexSlice",
     "Int16Dtype",
     "Int32Dtype",
     "Int64Dtype",
-    "Int64Index",
     "Int8Dtype",
     "Interval",
     "IntervalDtype",
@@ -141,7 +136,6 @@
     "UInt16Dtype",
     "UInt32Dtype",
     "UInt64Dtype",
-    "UInt64Index",
     "UInt8Dtype",
     "unique",
     "value_counts",

pandas/core/arrays/timedeltas.py

@@ -726,10 +726,10 @@ def total_seconds(self) -> npt.NDArray[np.float64]:
 
         Returns
         -------
-        ndarray, Float64Index or Series
+        ndarray, Index or Series
             When the calling object is a TimedeltaArray, the return type
             is ndarray.  When the calling object is a TimedeltaIndex,
-            the return type is a Float64Index. When the calling object
+            the return type is an Index with a float64 dtype. When the calling object
             is a Series, the return type is Series of type `float64` whose
             index is the same as the original.
 

pandas/core/frame.py

@@ -10870,11 +10870,7 @@ def quantile(
                 f"Invalid method: {method}. Method must be in {valid_method}."
             )
         if method == "single":
-            # error: Argument "qs" to "quantile" of "BlockManager" has incompatible type
-            # "Index"; expected "Float64Index"
-            res = data._mgr.quantile(
-                qs=q, axis=1, interpolation=interpolation  # type: ignore[arg-type]
-            )
+            res = data._mgr.quantile(qs=q, axis=1, interpolation=interpolation)
         elif method == "table":
             valid_interpolation = {"nearest", "lower", "higher"}
             if interpolation not in valid_interpolation:

pandas/core/groupby/grouper.py

@@ -880,7 +880,7 @@ def is_in_axis(key) -> bool:
             try:
                 items.get_loc(key)
             except (KeyError, TypeError, InvalidIndexError):
-                # TypeError shows up here if we pass e.g. Int64Index
+                # TypeError shows up here if we pass e.g. an Index
                 return False
 
         return True

pandas/core/indexes/api.py

@@ -26,12 +26,7 @@
 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 (
-    Float64Index,
-    Int64Index,
-    NumericIndex,
-    UInt64Index,
-)
+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
@@ -52,12 +47,9 @@
     "Index",
     "MultiIndex",
     "NumericIndex",
-    "Float64Index",
-    "Int64Index",
     "CategoricalIndex",
     "IntervalIndex",
     "RangeIndex",
-    "UInt64Index",
     "InvalidIndexError",
     "TimedeltaIndex",
     "PeriodIndex",

pandas/core/indexes/base.py

@@ -296,9 +296,6 @@ class Index(IndexOpsMixin, PandasObject):
     TimedeltaIndex : Index of timedelta64 data.
     PeriodIndex : Index of Period data.
     NumericIndex : Index of numpy int/uint/float data.
-    Int64Index : Index of purely int64 labels (deprecated).
-    UInt64Index : Index of purely uint64 labels (deprecated).
-    Float64Index : Index of  purely float64 labels (deprecated).
 
     Notes
     -----
@@ -498,7 +495,7 @@ def __new__(
 
         klass = cls._dtype_to_subclass(arr.dtype)
 
-        # _ensure_array _may_ be unnecessary once Int64Index etc are gone
+        # _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)
 
@@ -1026,7 +1023,7 @@ def take(
             taken = values.take(
                 indices, allow_fill=allow_fill, fill_value=self._na_value
             )
-        # _constructor so RangeIndex->Int64Index
+        # _constructor so RangeIndex-> Index with an int64 dtype
         return self._constructor._simple_new(taken, name=self.name)
 
     @final
@@ -1097,7 +1094,7 @@ def repeat(self, repeats, axis=None):
         nv.validate_repeat((), {"axis": axis})
         res_values = self._values.repeat(repeats)
 
-        # _constructor so RangeIndex->Int64Index
+        # _constructor so RangeIndex-> Index with an int64 dtype
         return self._constructor._simple_new(res_values, name=self.name)
 
     # --------------------------------------------------------------------
@@ -6228,7 +6225,7 @@ def _maybe_cast_slice_bound(self, label, side: str_t):
         """
 
         # We are a plain index here (sub-class override this method if they
-        # wish to have special treatment for floats/ints, e.g. Float64Index and
+        # wish to have special treatment for floats/ints, e.g. NumericIndex and
         # datetimelike Indexes
         # Special case numeric EA Indexes, since they are not handled by NumericIndex
 
@@ -6442,7 +6439,7 @@ def delete(self: _IndexT, loc) -> _IndexT:
         else:
             res_values = values.delete(loc)
 
-        # _constructor so RangeIndex->Int64Index
+        # _constructor so RangeIndex-> Index with an int64 dtype
         return self._constructor._simple_new(res_values, name=self.name)
 
     def insert(self, loc: int, item) -> Index:

pandas/core/indexes/datetimes.py

@@ -63,7 +63,7 @@
 if TYPE_CHECKING:
     from pandas.core.api import (
         DataFrame,
-        Float64Index,
+        NumericIndex,
         PeriodIndex,
     )
 
@@ -284,11 +284,11 @@ def to_period(self, freq=None) -> PeriodIndex:
         return PeriodIndex._simple_new(arr, name=self.name)
 
     @doc(DatetimeArray.to_julian_date)
-    def to_julian_date(self) -> Float64Index:
-        from pandas.core.indexes.api import Float64Index
+    def to_julian_date(self) -> NumericIndex:
+        from pandas.core.indexes.api import NumericIndex
 
         arr = self._data.to_julian_date()
-        return Float64Index._simple_new(arr, name=self.name)
+        return NumericIndex._simple_new(arr, name=self.name)
 
     @doc(DatetimeArray.isocalendar)
     def isocalendar(self) -> DataFrame:

pandas/core/indexes/interval.py

@@ -520,7 +520,7 @@ def _maybe_convert_i8(self, key):
         -------
         scalar or list-like
             The original key if no conversion occurred, int if converted scalar,
-            Int64Index if converted list-like.
+            Index with an int64 dtype if converted list-like.
         """
         if is_list_like(key):
             key = ensure_index(key)

pandas/core/indexes/multi.py

@@ -1642,7 +1642,7 @@ def get_level_values(self, level):
         level_1    int64
         dtype: object
         >>> pd.MultiIndex.from_arrays([[1, None, 2], [3, 4, 5]]).get_level_values(0)
-        Float64Index([1.0, nan, 2.0], dtype='float64')
+        NumericIndex([1.0, nan, 2.0], dtype='float64')
         """
         level = self._get_level_number(level)
         values = self._get_level_values(level)