Merge remote-tracking branch 'upstream/main' into ref/index_equiv

Author: mroeschke

.github/workflows/wheels.yml

@@ -139,8 +139,7 @@ jobs:
         shell: bash -el {0}
         run: echo "sdist_name=$(cd ./dist && ls -d */)" >> "$GITHUB_ENV"
 
-      - name: Build normal wheels
-        if: ${{ (env.IS_SCHEDULE_DISPATCH != 'true' || env.IS_PUSH == 'true') }}
+      - name: Build wheels
         uses: pypa/[email protected]
         with:
          package-dir: ./dist/${{ startsWith(matrix.buildplat[1], 'macosx') && env.sdist_name || needs.build_sdist.outputs.sdist_file }}

doc/source/whatsnew/v3.0.0.rst

@@ -297,6 +297,8 @@ Performance improvements
 ~~~~~~~~~~~~~~~~~~~~~~~~
 - :attr:`Categorical.categories` returns a :class:`RangeIndex` columns instead of an :class:`Index` if the constructed ``values`` was a ``range``. (:issue:`57787`)
 - :class:`DataFrame` returns a :class:`RangeIndex` columns when possible when ``data`` is a ``dict`` (:issue:`57943`)
+- :class:`Series` returns a :class:`RangeIndex` index when possible when ``data`` is a ``dict`` (:issue:`58118`)
+- :func:`concat` returns a :class:`RangeIndex` column when possible when ``objs`` contains :class:`Series` and :class:`DataFrame` and ``axis=0`` (:issue:`58119`)
 - :func:`concat` returns a :class:`RangeIndex` level in the :class:`MultiIndex` result when ``keys`` is a ``range`` or :class:`RangeIndex` (:issue:`57542`)
 - :meth:`RangeIndex.append` returns a :class:`RangeIndex` instead of a :class:`Index` when appending values that could continue the :class:`RangeIndex` (:issue:`57467`)
 - :meth:`Series.str.extract` returns a :class:`RangeIndex` columns instead of an :class:`Index` column when possible (:issue:`57542`)

pandas/core/indexes/base.py

@@ -6453,6 +6453,10 @@ def slice_locs(self, start=None, end=None, step=None) -> tuple[int, int]:
         >>> idx = pd.Index(list("abcd"))
         >>> idx.slice_locs(start="b", end="c")
         (1, 3)
+
+        >>> idx = pd.Index(list("bcde"))
+        >>> idx.slice_locs(start="a", end="c")
+        (0, 2)
         """
         inc = step is None or step >= 0
 
@@ -7144,7 +7148,10 @@ def maybe_sequence_to_range(sequence) -> Any | range:
         return sequence
     if len(sequence) == 0:
         return range(0)
-    np_sequence = np.asarray(sequence, dtype=np.int64)
+    try:
+        np_sequence = np.asarray(sequence, dtype=np.int64)
+    except OverflowError:
+        return sequence
     diff = np_sequence[1] - np_sequence[0]
     if diff == 0:
         return sequence

pandas/core/reshape/concat.py

@@ -518,8 +518,11 @@ def _sanitize_mixed_ndim(
                         # to have unique names
                         name = current_column
                         current_column += 1
-
-                obj = sample._constructor({name: obj}, copy=False)
+                    obj = sample._constructor(obj, copy=False)
+                    if isinstance(obj, ABCDataFrame):
+                        obj.columns = range(name, name + 1, 1)
+                else:
+                    obj = sample._constructor({name: obj}, copy=False)
 
             new_objs.append(obj)
 

pandas/core/series.py

@@ -132,6 +132,7 @@
     PeriodIndex,
     default_index,
     ensure_index,
+    maybe_sequence_to_range,
 )
 import pandas.core.indexes.base as ibase
 from pandas.core.indexes.multi import maybe_droplevels
@@ -538,16 +539,14 @@ def _init_dict(
         _data : BlockManager for the new Series
         index : index for the new Series
         """
-        keys: Index | tuple
-
         # Looking for NaN in dict doesn't work ({np.nan : 1}[float('nan')]
         # raises KeyError), so we iterate the entire dict, and align
         if data:
             # GH:34717, issue was using zip to extract key and values from data.
             # using generators in effects the performance.
             # Below is the new way of extracting the keys and values
 
-            keys = tuple(data.keys())
+            keys = maybe_sequence_to_range(tuple(data.keys()))
             values = list(data.values())  # Generating list of values- faster way
         elif index is not None:
             # fastpath for Series(data=None). Just use broadcasting a scalar

pandas/tests/reshape/concat/test_concat.py

@@ -912,3 +912,11 @@ def test_concat_none_with_timezone_timestamp():
         result = concat([df1, df2], ignore_index=True)
     expected = DataFrame({"A": [None, pd.Timestamp("1990-12-20 00:00:00+00:00")]})
     tm.assert_frame_equal(result, expected)
+
+
+def test_concat_with_series_and_frame_returns_rangeindex_columns():
+    ser = Series([0])
+    df = DataFrame([1, 2])
+    result = concat([ser, df])
+    expected = DataFrame([0, 1, 2], index=[0, 0, 1])
+    tm.assert_frame_equal(result, expected, check_column_type=True)

pandas/tests/series/test_constructors.py

@@ -2251,3 +2251,9 @@ def test_series_with_complex_nan(input_list):
     result = Series(ser.array)
     assert ser.dtype == "complex128"
     tm.assert_series_equal(ser, result)
+
+
+def test_dict_keys_rangeindex():
+    result = Series({0: 1, 1: 2})
+    expected = Series([1, 2], index=RangeIndex(2))
+    tm.assert_series_equal(result, expected, check_index_type=True)