GH49560 without GH50195 (DEPR: Remove int64 uint64 float64 index part 1)

pandas/_testing/__init__.py

@@ -27,6 +27,7 @@
 from pandas._typing import (
     Dtype,
     Frequency,
+    NpDtype,
 )
 from pandas.compat import pa_version_under6p0
 
@@ -124,12 +125,13 @@
 _N = 30
 _K = 4
 
-UNSIGNED_INT_NUMPY_DTYPES: list[Dtype] = ["uint8", "uint16", "uint32", "uint64"]
+UNSIGNED_INT_NUMPY_DTYPES: list[NpDtype] = ["uint8", "uint16", "uint32", "uint64"]
 UNSIGNED_INT_EA_DTYPES: list[Dtype] = ["UInt8", "UInt16", "UInt32", "UInt64"]
-SIGNED_INT_NUMPY_DTYPES: list[Dtype] = [int, "int8", "int16", "int32", "int64"]
+SIGNED_INT_NUMPY_DTYPES: list[NpDtype] = [int, "int8", "int16", "int32", "int64"]
 SIGNED_INT_EA_DTYPES: list[Dtype] = ["Int8", "Int16", "Int32", "Int64"]
 ALL_INT_NUMPY_DTYPES = UNSIGNED_INT_NUMPY_DTYPES + SIGNED_INT_NUMPY_DTYPES
 ALL_INT_EA_DTYPES = UNSIGNED_INT_EA_DTYPES + SIGNED_INT_EA_DTYPES
+ALL_INT_DTYPES: list[Dtype] = [*ALL_INT_NUMPY_DTYPES, *ALL_INT_EA_DTYPES]
 
 FLOAT_NUMPY_DTYPES: list[Dtype] = [float, "float32", "float64"]
 FLOAT_EA_DTYPES: list[Dtype] = ["Float32", "Float64"]

pandas/conftest.py

@@ -1486,7 +1486,7 @@ def any_int_ea_dtype(request):
     return request.param
 
 
-@pytest.fixture(params=tm.ALL_INT_NUMPY_DTYPES + tm.ALL_INT_EA_DTYPES)
+@pytest.fixture(params=tm.ALL_INT_DTYPES)
 def any_int_dtype(request):
     """
     Parameterized fixture for any nullable integer dtype.

pandas/core/arrays/datetimes.py

@@ -1385,7 +1385,7 @@ def isocalendar(self) -> DataFrame:
         0    2000
         1    2001
         2    2002
-        dtype: int64
+        dtype: int32
         """,
     )
     month = _field_accessor(
@@ -1408,7 +1408,7 @@ def isocalendar(self) -> DataFrame:
         0    1
         1    2
         2    3
-        dtype: int64
+        dtype: int32
         """,
     )
     day = _field_accessor(
@@ -1431,7 +1431,7 @@ def isocalendar(self) -> DataFrame:
         0    1
         1    2
         2    3
-        dtype: int64
+        dtype: int32
         """,
     )
     hour = _field_accessor(
@@ -1454,7 +1454,7 @@ def isocalendar(self) -> DataFrame:
         0    0
         1    1
         2    2
-        dtype: int64
+        dtype: int32
         """,
     )
     minute = _field_accessor(
@@ -1477,7 +1477,7 @@ def isocalendar(self) -> DataFrame:
         0    0
         1    1
         2    2
-        dtype: int64
+        dtype: int32
         """,
     )
     second = _field_accessor(
@@ -1500,7 +1500,7 @@ def isocalendar(self) -> DataFrame:
         0    0
         1    1
         2    2
-        dtype: int64
+        dtype: int32
         """,
     )
     microsecond = _field_accessor(
@@ -1523,7 +1523,7 @@ def isocalendar(self) -> DataFrame:
         0       0
         1       1
         2       2
-        dtype: int64
+        dtype: int32
         """,
     )
     nanosecond = _field_accessor(
@@ -1546,7 +1546,7 @@ def isocalendar(self) -> DataFrame:
         0       0
         1       1
         2       2
-        dtype: int64
+        dtype: int32
         """,
     )
     _dayofweek_doc = """
@@ -1581,7 +1581,7 @@ def isocalendar(self) -> DataFrame:
     2017-01-06    4
     2017-01-07    5
     2017-01-08    6
-    Freq: D, dtype: int64
+    Freq: D, dtype: int32
     """
     day_of_week = _field_accessor("day_of_week", "dow", _dayofweek_doc)
     dayofweek = day_of_week

pandas/core/arrays/timedeltas.py

@@ -771,7 +771,7 @@ def total_seconds(self) -> npt.NDArray[np.float64]:
                        dtype='timedelta64[ns]', freq=None)
 
         >>> idx.total_seconds()
-        Float64Index([0.0, 86400.0, 172800.0, 259200.0, 345600.0],
+        NumericIndex([0.0, 86400.0, 172800.0, 259200.0, 345600.0],
                      dtype='float64')
         """
         pps = periods_per_second(self._creso)

pandas/core/generic.py

@@ -6095,7 +6095,7 @@ def astype(
         0    1
         1    2
         dtype: category
-        Categories (2, int64): [1, 2]
+        Categories (2, int32): [1, 2]
 
         Convert to ordered categorical type with custom ordering:
 

pandas/core/indexes/accessors.py

@@ -161,7 +161,7 @@ class DatetimeProperties(Properties):
     0    0
     1    1
     2    2
-    dtype: int64
+    dtype: int32
 
     >>> hours_series = pd.Series(pd.date_range("2000-01-01", periods=3, freq="h"))
     >>> hours_series
@@ -173,7 +173,7 @@ class DatetimeProperties(Properties):
     0    0
     1    1
     2    2
-    dtype: int64
+    dtype: int32
 
     >>> quarters_series = pd.Series(pd.date_range("2000-01-01", periods=3, freq="q"))
     >>> quarters_series
@@ -185,7 +185,7 @@ class DatetimeProperties(Properties):
     0    1
     1    2
     2    3
-    dtype: int64
+    dtype: int32
 
     Returns a Series indexed like the original Series.
     Raises TypeError if the Series does not contain datetimelike values.
@@ -303,7 +303,7 @@ class TimedeltaProperties(Properties):
     0    1
     1    2
     2    3
-    dtype: int64
+    dtype: int32
     """
 
     def to_pytimedelta(self) -> np.ndarray: