Merge branch 'main' into add_prefix_feature

Author: zhangbowen-coder

.github/workflows/code-checks.yml

@@ -33,7 +33,7 @@ jobs:
 
     steps:
     - name: Checkout
-      uses: actions/checkout@v5
+      uses: actions/checkout@v6
       with:
         fetch-depth: 0
 
@@ -114,7 +114,7 @@ jobs:
 
     steps:
     - name: Checkout
-      uses: actions/checkout@v5
+      uses: actions/checkout@v6
       with:
         fetch-depth: 0
 
@@ -142,7 +142,7 @@ jobs:
 
     steps:
       - name: Checkout
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 

.github/workflows/codeql.yml

@@ -27,7 +27,7 @@ jobs:
           - python
 
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
       - uses: github/codeql-action/init@v4
         with:
           languages: ${{ matrix.language }}

.github/workflows/docbuild-and-upload.yml

@@ -36,7 +36,7 @@ jobs:
 
     steps:
     - name: Checkout
-      uses: actions/checkout@v5
+      uses: actions/checkout@v6
       with:
         fetch-depth: 0
 

.github/workflows/package-checks.yml

@@ -34,7 +34,7 @@ jobs:
 
     steps:
       - name: Checkout
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
@@ -58,7 +58,7 @@ jobs:
       cancel-in-progress: true
     steps:
       - name: Checkout
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 

.github/workflows/unit-tests.yml

@@ -139,7 +139,7 @@ jobs:
 
     steps:
     - name: Checkout
-      uses: actions/checkout@v5
+      uses: actions/checkout@v6
       with:
         fetch-depth: 0
 
@@ -198,7 +198,7 @@ jobs:
 
     steps:
       - name: Checkout
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
@@ -216,7 +216,7 @@ jobs:
   Linux-32-bit:
     runs-on: ubuntu-24.04
     container:
-      image: quay.io/pypa/manylinux2014_i686
+      image: quay.io/pypa/manylinux_2_28_i686
       options: --platform linux/386
     steps:
       - name: Checkout pandas Repo
@@ -336,7 +336,7 @@ jobs:
       PYTEST_TARGET: pandas
 
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
@@ -373,7 +373,7 @@ jobs:
       cancel-in-progress: true
     steps:
       - name: Checkout pandas Repo
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 

.github/workflows/wheels.yml

@@ -51,7 +51,7 @@ jobs:
       sdist_file: ${{ steps.save-path.outputs.sdist_name }}
     steps:
       - name: Checkout pandas
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
@@ -122,7 +122,7 @@ jobs:
       IS_SCHEDULE_DISPATCH: ${{ github.event_name == 'schedule' || github.event_name == 'workflow_dispatch' }}
     steps:
       - name: Checkout pandas
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 

.gitignore

@@ -21,6 +21,7 @@
 .noseids
 .ipynb_checkpoints
 .tags
+tags
 .cache/
 .vscode/
 

ci/code_checks.sh

@@ -73,12 +73,10 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Period.freq GL08" \
         -i "pandas.Period.ordinal GL08" \
         -i "pandas.errors.IncompatibleFrequency SA01,SS06,EX01" \
-        -i "pandas.errors.InvalidVersion GL08" \
         -i "pandas.api.extensions.ExtensionArray.value_counts EX01,RT03,SA01" \
         -i "pandas.api.typing.DataFrameGroupBy.plot PR02" \
         -i "pandas.api.typing.SeriesGroupBy.plot PR02" \
         -i "pandas.api.typing.Resampler.quantile PR01,PR07" \
-        -i "pandas.arrays.NumpyExtensionArray GL08" \
         -i "pandas.tseries.offsets.BDay PR02,SA01" \
         -i "pandas.tseries.offsets.BHalfYearBegin.is_on_offset GL08" \
         -i "pandas.tseries.offsets.BHalfYearBegin.n GL08" \

doc/source/whatsnew/v3.0.0.rst

@@ -233,6 +233,9 @@ Other enhancements
 - Support reading Stata 102-format (Stata 1) dta files (:issue:`58978`)
 - Support reading Stata 110-format (Stata 7) dta files (:issue:`47176`)
 - Switched wheel upload to **PyPI Trusted Publishing** (OIDC) for release-tag pushes in ``wheels.yml``. (:issue:`61718`)
+- Added a new :meth:`DataFrame.from_arrow` method to import any Arrow-compatible
+  tabular data object into a pandas :class:`DataFrame` through the
+  `Arrow PyCapsule Protocol <https://arrow.apache.org/docs/format/CDataInterface/PyCapsuleInterface.html>`__ (:issue:`59631`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_300.notable_bug_fixes:
@@ -745,10 +748,16 @@ Other API changes
   the dtype of the resulting Index (:issue:`60797`)
 - :class:`IncompatibleFrequency` now subclasses ``TypeError`` instead of ``ValueError``. As a result, joins with mismatched frequencies now cast to object like other non-comparable joins, and arithmetic with indexes with mismatched frequencies align (:issue:`55782`)
 - :class:`Series` "flex" methods like :meth:`Series.add` no longer allow passing a :class:`DataFrame` for ``other``; use the DataFrame reversed method instead (:issue:`46179`)
+- :func:`date_range` and :func:`timedelta_range` no longer default to ``unit="ns"``, instead will infer a unit from the ``start``, ``end``, and ``freq`` parameters. Explicitly specify a desired ``unit`` to override these (:issue:`59031`)
 - :meth:`CategoricalIndex.append` no longer attempts to cast different-dtype indexes to the caller's dtype (:issue:`41626`)
 - :meth:`ExtensionDtype.construct_array_type` is now a regular method instead of a ``classmethod`` (:issue:`58663`)
+- Arithmetic operations between a :class:`Series`, :class:`Index`, or :class:`ExtensionArray` with a ``list`` now consistently wrap that list with an array equivalent to ``Series(my_list).array``. To do any other kind of type inference or casting, do so explicitly before operating (:issue:`62552`)
 - Comparison operations between :class:`Index` and :class:`Series` now consistently return :class:`Series` regardless of which object is on the left or right (:issue:`36759`)
 - Numpy functions like ``np.isinf`` that return a bool dtype when called on a :class:`Index` object now return a bool-dtype :class:`Index` instead of ``np.ndarray`` (:issue:`52676`)
+- Methods that can operate in-place (:meth:`~DataFrame.replace`, :meth:`~DataFrame.fillna`,
+  :meth:`~DataFrame.ffill`, :meth:`~DataFrame.bfill`, :meth:`~DataFrame.interpolate`,
+  :meth:`~DataFrame.where`, :meth:`~DataFrame.mask`, :meth:`~DataFrame.clip`) now return
+  the modified DataFrame or Series (``self``) instead of ``None`` when ``inplace=True`` (:issue:`63207`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_300.deprecations:
@@ -1182,6 +1191,7 @@ I/O
 - Fix bug in ``on_bad_lines`` callable when returning too many fields: now emits
   ``ParserWarning`` and truncates extra fields regardless of ``index_col`` (:issue:`61837`)
 - Bug in :func:`pandas.json_normalize` inconsistently handling non-dict items in ``data`` when ``max_level`` was set. The function will now raise a ``TypeError`` if ``data`` is a list containing non-dict items (:issue:`62829`)
+- Bug in :func:`pandas.json_normalize` raising ``TypeError`` when ``meta`` contained a non-string key (e.g., ``int``) and ``record_path`` was specified, which was inconsistent with the behavior when ``record_path`` was ``None`` (:issue:`63019`)
 - Bug in :meth:`.DataFrame.to_json` when ``"index"`` was a value in the :attr:`DataFrame.column` and :attr:`Index.name` was ``None``. Now, this will fail with a ``ValueError`` (:issue:`58925`)
 - Bug in :meth:`.io.common.is_fsspec_url` not recognizing chained fsspec URLs (:issue:`48978`)
 - Bug in :meth:`DataFrame._repr_html_` which ignored the ``"display.float_format"`` option (:issue:`59876`)
@@ -1244,6 +1254,7 @@ Groupby/resample/rolling
 - Bug in :meth:`.DataFrameGroupBy.groups` and :meth:`.SeriesGroupby.groups` that would not respect groupby argument ``dropna`` (:issue:`55919`)
 - Bug in :meth:`.DataFrameGroupBy.median` where nat values gave an incorrect result. (:issue:`57926`)
 - Bug in :meth:`.DataFrameGroupBy.quantile` when ``interpolation="nearest"`` is inconsistent with :meth:`DataFrame.quantile` (:issue:`47942`)
+- Bug in :meth:`.DataFrameGroupBy.sum` and :meth:`.SeriesGroupby.groups` returning ``NaN`` on overflow. These methods now returns ``inf`` or ``-inf`` on overflow. (:issue:`60303`)
 - Bug in :meth:`.DataFrameGroupBy` reductions where non-Boolean values were allowed for the ``numeric_only`` argument; passing a non-Boolean value will now raise (:issue:`62778`)
 - Bug in :meth:`.Resampler.interpolate` on a :class:`DataFrame` with non-uniform sampling and/or indices not aligning with the resulting resampled index would result in wrong interpolation (:issue:`21351`)
 - Bug in :meth:`.Series.rolling` when used with a :class:`.BaseIndexer` subclass and computing min/max (:issue:`46726`)
@@ -1263,6 +1274,7 @@ Groupby/resample/rolling
 - Bug in :meth:`DataFrameGroupby.transform` and :meth:`SeriesGroupby.transform` with a reducer and ``observed=False`` that coerces dtype to float when there are unobserved categories. (:issue:`55326`)
 - Bug in :meth:`Rolling.apply` for ``method="table"`` where column order was not being respected due to the columns getting sorted by default. (:issue:`59666`)
 - Bug in :meth:`Rolling.apply` where the applied function could be called on fewer than ``min_period`` periods if ``method="table"``. (:issue:`58868`)
+- Bug in :meth:`Rolling.sem` computing incorrect results because it divided by ``sqrt((n - 1) * (n - ddof))`` instead of ``sqrt(n * (n - ddof))``. (:issue:`63180`)
 - Bug in :meth:`Rolling.skew` incorrectly computing skewness for windows following outliers due to numerical instability. The calculation now properly handles catastrophic cancellation by recomputing affected windows (:issue:`47461`)
 - Bug in :meth:`Series.resample` could raise when the date range ended shortly before a non-existent time. (:issue:`58380`)
 - Bug in :meth:`Series.resample` raising error when resampling non-nanosecond resolutions out of bounds for nanosecond precision (:issue:`57427`)

pandas/_libs/groupby.pyx

@@ -5,6 +5,7 @@ from cython cimport (
 )
 from libc.math cimport (
     NAN,
+    isfinite,
     sqrt,
 )
 from libc.stdlib cimport (
@@ -778,9 +779,9 @@ def group_sum(
                 if not isna_entry:
                     nobs[lab, j] += 1
 
-                    if sum_t is object:
+                    if sum_t is object or sum_t is int64_t or sum_t is uint64_t:
                         # NB: this does not use 'compensation' like the non-object
-                        #  track does.
+                        #  and non-integer track does.
                         if nobs[lab, j] == 1:
                             # i.e. we haven't added anything yet; avoid TypeError
                             #  if e.g. val is a str and sumx[lab, j] is 0
@@ -793,13 +794,29 @@ def group_sum(
                         y = val - compensation[lab, j]
                         t = sumx[lab, j] + y
                         compensation[lab, j] = t - sumx[lab, j] - y
-                        if compensation[lab, j] != compensation[lab, j]:
-                            # GH#53606
+
+                        # Handle float overflow
+                        if (
+                            sum_t is float32_t or sum_t is float64_t
+                        ) and not isfinite(compensation[lab, j]):
+                            # GH#53606; GH#60303
                             # If val is +/- infinity compensation is NaN
                             # which would lead to results being NaN instead
                             # of +/- infinity. We cannot use util.is_nan
                             # because of no gil
                             compensation[lab, j] = 0
+
+                        # Handle complex overflow
+                        if (
+                            sum_t is complex64_t or sum_t is complex128_t
+                        ) and not isfinite(compensation[lab, j].real):
+                            compensation[lab, j].real = 0
+
+                        if (
+                            sum_t is complex64_t or sum_t is complex128_t
+                        ) and not isfinite(compensation[lab, j].imag):
+                            compensation[lab, j].imag = 0
+
                         sumx[lab, j] = t
                 elif not skipna:
                     if uses_mask: