Merge branch 'main' into fix-loc-dtype

Author: sanggon6107

.github/workflows/wheels.yml

@@ -95,6 +95,7 @@ jobs:
         - [ubuntu-24.04, manylinux_x86_64]
         - [ubuntu-24.04, musllinux_x86_64]
         - [ubuntu-24.04-arm, manylinux_aarch64]
+        - [ubuntu-24.04-arm, musllinux_aarch64]
         - [macos-13, macosx_x86_64]
         # Note: M1 images on Github Actions start from macOS 14
         - [macos-14, macosx_arm64]

doc/source/getting_started/install.rst

@@ -308,7 +308,7 @@ Dependency                                             Minimum Version    pip ex
 `zlib <https://github.com/madler/zlib>`__                                 hdf5             Compression for HDF5
 `fastparquet <https://github.com/dask/fastparquet>`__  2024.2.0           -                Parquet reading / writing (pyarrow is default)
 `pyarrow <https://github.com/apache/arrow>`__          10.0.1             parquet, feather Parquet, ORC, and feather reading / writing
-`PyIceberg <https://py.iceberg.apache.org/>`__         0.7.1              iceberg          Apache Iceberg reading
+`PyIceberg <https://py.iceberg.apache.org/>`__         0.7.1              iceberg          Apache Iceberg reading / writing
 `pyreadstat <https://github.com/Roche/pyreadstat>`__   1.2.6              spss             SPSS files (.sav) reading
 `odfpy <https://github.com/eea/odfpy>`__               1.4.1              excel            Open document format (.odf, .ods, .odt) reading / writing
 ====================================================== ================== ================ ==========================================================

doc/source/reference/io.rst

@@ -162,6 +162,7 @@ Iceberg
     :toctree: api/
 
     read_iceberg
+    DataFrame.to_iceberg
 
 .. warning:: ``read_iceberg`` is experimental and may change without warning.
 

doc/source/user_guide/io.rst

@@ -29,7 +29,7 @@ The pandas I/O API is a set of top level ``reader`` functions accessed like
     binary,`HDF5 Format <https://support.hdfgroup.org/documentation/hdf5/latest/_intro_h_d_f5.html>`__, :ref:`read_hdf<io.hdf5>`, :ref:`to_hdf<io.hdf5>`
     binary,`Feather Format <https://github.com/wesm/feather>`__, :ref:`read_feather<io.feather>`, :ref:`to_feather<io.feather>`
     binary,`Parquet Format <https://parquet.apache.org/>`__, :ref:`read_parquet<io.parquet>`, :ref:`to_parquet<io.parquet>`
-    binary,`Apache Iceberg <https://iceberg.apache.org/>`__, :ref:`read_iceberg<io.iceberg>` , NA
+    binary,`Apache Iceberg <https://iceberg.apache.org/>`__, :ref:`read_iceberg<io.iceberg>` , :ref:`to_iceberg<io.iceberg>`
     binary,`ORC Format <https://orc.apache.org/>`__, :ref:`read_orc<io.orc>`, :ref:`to_orc<io.orc>`
     binary,`Stata <https://en.wikipedia.org/wiki/Stata>`__, :ref:`read_stata<io.stata_reader>`, :ref:`to_stata<io.stata_writer>`
     binary,`SAS <https://en.wikipedia.org/wiki/SAS_(software)>`__, :ref:`read_sas<io.sas_reader>` , NA
@@ -5417,7 +5417,7 @@ engines to safely work with the same tables at the same time.
 
 Iceberg support predicate pushdown and column pruning, which are available to pandas
 users via the ``row_filter`` and ``selected_fields`` parameters of the :func:`~pandas.read_iceberg`
-function. This is convenient to extract from large tables a subset that fits in memory asa
+function. This is convenient to extract from large tables a subset that fits in memory as a
 pandas ``DataFrame``.
 
 Internally, pandas uses PyIceberg_ to query Iceberg.
@@ -5497,6 +5497,29 @@ parameter:
 Reading a particular snapshot is also possible providing the snapshot ID as an argument to
 ``snapshot_id``.
 
+To save a ``DataFrame`` to Iceberg, it can be done with the :meth:`DataFrame.to_iceberg`
+method:
+
+.. code-block:: python
+
+    df.to_iceberg("my_table", catalog_name="my_catalog")
+
+To specify the catalog, it works in the same way as for :func:`read_iceberg` with the
+``catalog_name`` and ``catalog_properties`` parameters.
+
+The location of the table can be specified with the ``location`` parameter:
+
+.. code-block:: python
+
+    df.to_iceberg(
+        "my_table",
+        catalog_name="my_catalog",
+        location="s://my-data-lake/my-iceberg-tables",
+    )
+
+It is possible to add properties to the table snapshot by passing a dictionary to the
+``snapshot_properties`` parameter.
+
 More information about the Iceberg format can be found in the `Apache Iceberg official
 page <https://iceberg.apache.org/>`__.
 

doc/source/user_guide/reshaping.rst

@@ -395,7 +395,7 @@ variables and the values representing the presence of those variables per row.
    pd.get_dummies(df["key"])
    df["key"].str.get_dummies()
 
-``prefix`` adds a prefix to the the column names which is useful for merging the result
+``prefix`` adds a prefix to the column names which is useful for merging the result
 with the original :class:`DataFrame`:
 
 .. ipython:: python

doc/source/user_guide/user_defined_functions.rst

@@ -319,7 +319,7 @@ to the original data.
 
 In the example, the ``warm_up_all_days`` function computes the ``max`` like an aggregation, but instead
 of returning just the maximum value, it returns a ``DataFrame`` with the same shape as the original one
-with the values of each day replaced by the the maximum temperature of the city.
+with the values of each day replaced by the maximum temperature of the city.
 
 ``transform`` is also available for :meth:`SeriesGroupBy.transform`, :meth:`DataFrameGroupBy.transform` and
 :meth:`Resampler.transform`, where it's more common. You can read more about ``transform`` in groupby

doc/source/whatsnew/v1.1.0.rst

@@ -1039,7 +1039,7 @@ Missing
 ^^^^^^^
 - Calling :meth:`fillna` on an empty :class:`Series` now correctly returns a shallow copied object. The behaviour is now consistent with :class:`Index`, :class:`DataFrame` and a non-empty :class:`Series` (:issue:`32543`).
 - Bug in :meth:`Series.replace` when argument ``to_replace`` is of type dict/list and is used on a :class:`Series` containing ``<NA>`` was raising a ``TypeError``. The method now handles this by ignoring ``<NA>`` values when doing the comparison for the replacement (:issue:`32621`)
-- Bug in :meth:`~Series.any` and :meth:`~Series.all` incorrectly returning ``<NA>`` for all ``False`` or all ``True`` values using the nulllable Boolean dtype and with ``skipna=False`` (:issue:`33253`)
+- Bug in :meth:`~Series.any` and :meth:`~Series.all` incorrectly returning ``<NA>`` for all ``False`` or all ``True`` values using the nullable Boolean dtype and with ``skipna=False`` (:issue:`33253`)
 - Clarified documentation on interpolate with ``method=akima``. The ``der`` parameter must be scalar or ``None`` (:issue:`33426`)
 - :meth:`DataFrame.interpolate` uses the correct axis convention now. Previously interpolating along columns lead to interpolation along indices and vice versa. Furthermore interpolating with methods ``pad``, ``ffill``, ``bfill`` and ``backfill`` are identical to using these methods with :meth:`DataFrame.fillna` (:issue:`12918`, :issue:`29146`)
 - Bug in :meth:`DataFrame.interpolate` when called on a :class:`DataFrame` with column names of string type was throwing a ValueError. The method is now independent of the type of the column names (:issue:`33956`)

doc/source/whatsnew/v3.0.0.rst

@@ -79,7 +79,7 @@ Other enhancements
 - :py:class:`frozenset` elements in pandas objects are now natively printed (:issue:`60690`)
 - Add ``"delete_rows"`` option to ``if_exists`` argument in :meth:`DataFrame.to_sql` deleting all records of the table before inserting data (:issue:`37210`).
 - Added half-year offset classes :class:`HalfYearBegin`, :class:`HalfYearEnd`, :class:`BHalfYearBegin` and :class:`BHalfYearEnd` (:issue:`60928`)
-- Added support to read from Apache Iceberg tables with the new :func:`read_iceberg` function (:issue:`61383`)
+- Added support to read and write from and to Apache Iceberg tables with the new :func:`read_iceberg` and :meth:`DataFrame.to_iceberg` functions (:issue:`61383`)
 - Errors occurring during SQL I/O will now throw a generic :class:`.DatabaseError` instead of the raw Exception type from the underlying driver manager library (:issue:`60748`)
 - Implemented :meth:`Series.str.isascii` and :meth:`Series.str.isascii` (:issue:`59091`)
 - Improved deprecation message for offset aliases (:issue:`60820`)
@@ -712,6 +712,7 @@ Timezones
 Numeric
 ^^^^^^^
 - Bug in :meth:`DataFrame.corr` where numerical precision errors resulted in correlations above ``1.0`` (:issue:`61120`)
+- Bug in :meth:`DataFrame.cov` raises a ``TypeError`` instead of returning potentially incorrect results or other errors (:issue:`53115`)
 - Bug in :meth:`DataFrame.quantile` where the column type was not preserved when ``numeric_only=True`` with a list-like ``q`` produced an empty result (:issue:`59035`)
 - Bug in :meth:`Series.dot` returning ``object`` dtype for :class:`ArrowDtype` and nullable-dtype data (:issue:`61375`)
 - Bug in ``np.matmul`` with :class:`Index` inputs raising a ``TypeError`` (:issue:`57079`)
@@ -834,7 +835,7 @@ 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:`Series.resample` could raise when the the date range ended shortly before a non-existent time. (:issue:`58380`)
+- Bug in :meth:`Series.resample` could raise when the date range ended shortly before a non-existent time. (:issue:`58380`)
 
 Reshaping
 ^^^^^^^^^
@@ -852,6 +853,7 @@ Reshaping
 - Bug in :meth:`DataFrame.unstack` producing incorrect results when manipulating empty :class:`DataFrame` with an :class:`ExtentionDtype` (:issue:`59123`)
 - Bug in :meth:`concat` where concatenating DataFrame and Series with ``ignore_index = True`` drops the series name (:issue:`60723`, :issue:`56257`)
 - Bug in :func:`melt` where calling with duplicate column names in ``id_vars`` raised a misleading ``AttributeError`` (:issue:`61475`)
+- Bug in :meth:`DataFrame.merge` where user-provided suffixes could result in duplicate column names if the resulting names matched existing columns. Now raises a :class:`MergeError` in such cases. (:issue:`61402`)
 
 Sparse
 ^^^^^^

environment.yml

@@ -3,7 +3,7 @@ name: pandas-dev
 channels:
   - conda-forge
 dependencies:
-  - python=3.10
+  - python=3.11
   - pip
 
   # build dependencies

meson.build

@@ -57,6 +57,7 @@ if cy.version().version_compare('>=3.1.0')
         command: [
             cy,
             '-3',
+            '-Xfreethreading_compatible=true',
             '--fast-fail',
             '--generate-shared=' + meson.current_build_dir() / '_cyutility.c',
         ],