>> pd.Timedelta(1, \"us\").value\n+ 1000\n+ \"\"\"\n try:\n return convert_reso(self._value, self._creso, NPY_FR_ns, False)\n except OverflowError:\n@@ -1120,6 +1139,37 @@ cdef class _Timedelta(timedelta):\n def microseconds(self) -> int: # TODO(cython3): make cdef property\n # NB: using the python C-API PyDateTime_DELTA_GET_MICROSECONDS will fail\n # (or be incorrect)\n+ \"\"\"\n+ Return the number of microseconds (n), where 0 <= n < 1 millisecond.\n+\n+ Timedelta.microseconds = milliseconds * 1000 + microseconds.\n+\n+ Returns\n+ -------\n+ int\n+ Number of microseconds.\n+\n+ See Also\n+ --------\n+ Timedelta.components : Return all attributes with assigned values\n+ (i.e. days, hours, minutes, seconds, milliseconds, microseconds,\n+ nanoseconds).\n+\n+ Examples\n+ --------\n+ **Using string input**\n+\n+ >>> td = pd.Timedelta('1 days 2 min 3 us')\n+\n+ >>> td.microseconds\n+ 3\n+\n+ **Using integer input**\n+\n+ >>> td = pd.Timedelta(42, unit='us')\n+ >>> td.microseconds\n+ 42\n+ \"\"\"\n self._ensure_components()\n return self._ms * 1000 + self._us\n \n@@ -1141,6 +1191,26 @@ cdef class _Timedelta(timedelta):\n \n @property\n def unit(self) -> str:\n+ \"\"\"\n+ Return the unit of Timedelta object.\n+\n+ The unit of Timedelta object is nanosecond, i.e., 'ns' by default.\n+\n+ Returns\n+ -------\n+ str\n+\n+ See Also\n+ --------\n+ Timedelta.value : Return the value of Timedelta object in nanoseconds.\n+ Timedelta.as_unit : Convert the underlying int64 representation to\n+ the given unit.\n+\n+ Examples\n+ --------\n+ >>> td = pd.Timedelta(42, unit='us')\n+ 'ns'\n+ \"\"\"\n return npy_unit_to_abbrev(self._creso)\n \n def __hash__(_Timedelta self):\n"},"body":{"kind":"string","value":"- [x] xref #57443 \r\n- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57616"},"created_at":{"kind":"string","value":"2024-02-25T09:54:14Z"},"closed_at":{"kind":"string","value":"2024-02-28T17:34:29Z"},"merged_at":{"kind":"string","value":"2024-02-28T17:34:29Z"},"updated_at":{"kind":"string","value":"2024-02-28T17:34:36Z"}}},{"rowIdx":856,"cells":{"title":{"kind":"string","value":"Doc: fixing RT03 errors for pandas.DataFrame.expanding"},"diff":{"kind":"string","value":"diff --git a/pandas/core/window/expanding.py b/pandas/core/window/expanding.py\nindex c3ee53c1b4551..abe853a8aa259 100644\n--- a/pandas/core/window/expanding.py\n+++ b/pandas/core/window/expanding.py\n@@ -51,6 +51,9 @@ class Expanding(RollingAndExpandingMixin):\n \"\"\"\n Provide expanding window calculations.\n \n+ An expanding window yields the value of an aggregation statistic with all the data\n+ available up to that point in time.\n+\n Parameters\n ----------\n min_periods : int, default 1\n@@ -69,6 +72,8 @@ class Expanding(RollingAndExpandingMixin):\n Returns\n -------\n pandas.api.typing.Expanding\n+ An instance of Expanding for further expanding window calculations,\n+ e.g. using the ``sum`` method.\n \n See Also\n --------\n"},"body":{"kind":"string","value":"All RT03 Errors resolved in the following cases:\r\n\r\n1. scripts/validate_docstrings.py --format=actions --errors=RT03 pandas.DataFrame.expanding\r\n\r\n- [x] xref https://github.com/pandas-dev/pandas/issues/57416\r\n- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57615"},"created_at":{"kind":"string","value":"2024-02-25T09:31:13Z"},"closed_at":{"kind":"string","value":"2024-02-26T23:05:05Z"},"merged_at":{"kind":"string","value":"2024-02-26T23:05:05Z"},"updated_at":{"kind":"string","value":"2024-03-10T20:00:29Z"}}},{"rowIdx":857,"cells":{"title":{"kind":"string","value":"DOC: Add `DataFrame.isetitem` method"},"diff":{"kind":"string","value":"diff --git a/doc/source/reference/frame.rst b/doc/source/reference/frame.rst\nindex 31a1c6008bce8..7680c8b434866 100644\n--- a/doc/source/reference/frame.rst\n+++ b/doc/source/reference/frame.rst\n@@ -74,6 +74,7 @@ Indexing, iteration\n DataFrame.where\n DataFrame.mask\n DataFrame.query\n+ DataFrame.isetitem\n \n For more information on ``.at``, ``.iat``, ``.loc``, and\n ``.iloc``, see the :ref:`indexing documentation <indexing>`.\ndiff --git a/pandas/core/frame.py b/pandas/core/frame.py\nindex df413fda0255a..ad6d411ccb675 100644\n--- a/pandas/core/frame.py\n+++ b/pandas/core/frame.py\n@@ -4018,6 +4018,11 @@ def isetitem(self, loc, value) -> None:\n value : scalar or arraylike\n Value(s) for the column.\n \n+ See Also\n+ --------\n+ DataFrame.iloc : Purely integer-location based indexing for selection by\n+ position.\n+\n Notes\n -----\n ``frame.isetitem(loc, value)`` is an in-place method as it will\n@@ -4028,6 +4033,15 @@ def isetitem(self, loc, value) -> None:\n \n In cases where ``frame.columns`` is unique, this is equivalent to\n ``frame[frame.columns[i]] = value``.\n+\n+ Examples\n+ --------\n+ >>> df = pd.DataFrame({\"A\": [1, 2], \"B\": [3, 4]})\n+ >>> df.isetitem(1, [5, 6])\n+ >>> df\n+ A B\n+ 0 1 5\n+ 1 2 6\n \"\"\"\n if isinstance(value, DataFrame):\n if is_integer(loc):\n"},"body":{"kind":"string","value":"- [x] closes #57602 (Replace xxxx with the GitHub issue number)\r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57614"},"created_at":{"kind":"string","value":"2024-02-25T09:10:37Z"},"closed_at":{"kind":"string","value":"2024-02-27T16:52:07Z"},"merged_at":{"kind":"string","value":"2024-02-27T16:52:07Z"},"updated_at":{"kind":"string","value":"2024-02-28T03:23:23Z"}}},{"rowIdx":858,"cells":{"title":{"kind":"string","value":"fix SA01 error for pandas.ArrowDtype"},"diff":{"kind":"string","value":"diff --git a/ci/code_checks.sh b/ci/code_checks.sh\nindex 47a2cf93a4f89..7f5f2f2d406fc 100755\n--- a/ci/code_checks.sh\n+++ b/ci/code_checks.sh\n@@ -2152,7 +2152,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n \n MSG='Partially validate docstrings (SA01)' ; echo $MSG\n $BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=SA01 --ignore_functions \\\n- pandas.ArrowDtype\\\n pandas.BooleanDtype\\\n pandas.Categorical.__array__\\\n pandas.Categorical.as_ordered\\\ndiff --git a/pandas/core/dtypes/dtypes.py b/pandas/core/dtypes/dtypes.py\nindex 12dcd8b0d42af..02560f54e2960 100644\n--- a/pandas/core/dtypes/dtypes.py\n+++ b/pandas/core/dtypes/dtypes.py\n@@ -2076,6 +2076,10 @@ class ArrowDtype(StorageExtensionDtype):\n -------\n ArrowDtype\n \n+ See Also\n+ --------\n+ DataFrame.convert_dtypes : Convert columns to the best possible dtypes.\n+\n Examples\n --------\n >>> import pyarrow as pa\n"},"body":{"kind":"string","value":"All SA01 Errors resolved in the following cases:\r\n\r\n1. scripts/validate_docstrings.py --format=actions --errors=SA01 pandas.ArrowDtype\r\n\r\n- [x] xref https://github.com/pandas-dev/pandas/issues/57417\r\n- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57613"},"created_at":{"kind":"string","value":"2024-02-25T08:46:35Z"},"closed_at":{"kind":"string","value":"2024-02-26T18:11:03Z"},"merged_at":{"kind":"string","value":"2024-02-26T18:11:03Z"},"updated_at":{"kind":"string","value":"2024-02-26T18:23:47Z"}}},{"rowIdx":859,"cells":{"title":{"kind":"string","value":"Doc: Fix PR07 errors for pandas.DataFrame.align"},"diff":{"kind":"string","value":"diff --git a/ci/code_checks.sh b/ci/code_checks.sh\nindex 47a2cf93a4f89..bbfe67e2ae94c 100755\n--- a/ci/code_checks.sh\n+++ b/ci/code_checks.sh\n@@ -1766,7 +1766,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n \n MSG='Partially validate docstrings (PR07)' ; echo $MSG\n $BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=PR07 --ignore_functions \\\n- pandas.DataFrame.align\\\n pandas.DataFrame.get\\\n pandas.DataFrame.rolling\\\n pandas.DataFrame.to_hdf\\\n@@ -2170,7 +2169,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n pandas.CategoricalIndex.ordered\\\n pandas.DataFrame.__dataframe__\\\n pandas.DataFrame.__iter__\\\n- pandas.DataFrame.align\\\n pandas.DataFrame.assign\\\n pandas.DataFrame.axes\\\n pandas.DataFrame.backfill\\\ndiff --git a/pandas/core/generic.py b/pandas/core/generic.py\nindex 9424e421fd85f..866aae5bdd613 100644\n--- a/pandas/core/generic.py\n+++ b/pandas/core/generic.py\n@@ -9442,6 +9442,7 @@ def align(\n Parameters\n ----------\n other : DataFrame or Series\n+ The object to align with.\n join : {{'outer', 'inner', 'left', 'right'}}, default 'outer'\n Type of alignment to be performed.\n \n@@ -9482,6 +9483,11 @@ def align(\n tuple of ({klass}, type of other)\n Aligned objects.\n \n+ See Also\n+ --------\n+ Series.align : Align two objects on their axes with specified join method.\n+ DataFrame.align : Align two objects on their axes with specified join method.\n+\n Examples\n --------\n >>> df = pd.DataFrame(\n"},"body":{"kind":"string","value":"All PR07 Errors resolved in the following cases:\r\n\r\n1. scripts/validate_docstrings.py --format=actions --errors=PR07 pandas.DataFrame.align\r\n\r\n- [x] xref https://github.com/pandas-dev/pandas/issues/57420\r\n- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57612"},"created_at":{"kind":"string","value":"2024-02-25T08:14:36Z"},"closed_at":{"kind":"string","value":"2024-02-26T18:14:28Z"},"merged_at":{"kind":"string","value":"2024-02-26T18:14:28Z"},"updated_at":{"kind":"string","value":"2024-02-26T18:24:32Z"}}},{"rowIdx":860,"cells":{"title":{"kind":"string","value":"Doc: fix PR01 docstring errors for pandas.CategoricalIndex.equals and pandas.CategoricalIndex.map"},"diff":{"kind":"string","value":"diff --git a/ci/code_checks.sh b/ci/code_checks.sh\nindex 6de0a8c2ca325..e8e5056694f88 100755\n--- a/ci/code_checks.sh\n+++ b/ci/code_checks.sh\n@@ -415,8 +415,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n \n MSG='Partially validate docstrings (PR01)' ; echo $MSG\n $BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=PR01 --ignore_functions \\\n- pandas.CategoricalIndex.equals\\\n- pandas.CategoricalIndex.map\\\n pandas.DataFrame.at_time\\\n pandas.DataFrame.backfill\\\n pandas.DataFrame.get\\\n@@ -1118,7 +1116,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n pandas.CategoricalIndex.as_ordered\\\n pandas.CategoricalIndex.as_unordered\\\n pandas.CategoricalIndex.codes\\\n- pandas.CategoricalIndex.equals\\\n pandas.CategoricalIndex.ordered\\\n pandas.DataFrame.__dataframe__\\\n pandas.DataFrame.__iter__\\\ndiff --git a/pandas/core/indexes/category.py b/pandas/core/indexes/category.py\nindex 5e9d15812526f..3b04d95cb7cbd 100644\n--- a/pandas/core/indexes/category.py\n+++ b/pandas/core/indexes/category.py\n@@ -276,12 +276,24 @@ def equals(self, other: object) -> bool:\n \"\"\"\n Determine if two CategoricalIndex objects contain the same elements.\n \n+ The order and orderedness of elements matters. The categories matter,\n+ but the order of the categories matters only when ``ordered=True``.\n+\n+ Parameters\n+ ----------\n+ other : object\n+ The CategoricalIndex object to compare with.\n+\n Returns\n -------\n bool\n ``True`` if two :class:`pandas.CategoricalIndex` objects have equal\n elements, ``False`` otherwise.\n \n+ See Also\n+ --------\n+ Categorical.equals : Returns True if categorical arrays are equal.\n+\n Examples\n --------\n >>> ci = pd.CategoricalIndex([\"a\", \"b\", \"c\", \"a\", \"b\", \"c\"])\n@@ -446,6 +458,9 @@ def map(self, mapper, na_action: Literal[\"ignore\"] | None = None):\n ----------\n mapper : function, dict, or Series\n Mapping correspondence.\n+ na_action : {None, 'ignore'}, default 'ignore'\n+ If 'ignore', propagate NaN values, without passing them to\n+ the mapping correspondence.\n \n Returns\n -------\n"},"body":{"kind":"string","value":"All PR01 Errors resolved in the following cases:\r\n\r\n1. scripts/validate_docstrings.py --format=actions --errors=ES01 pandas.CategoricalIndex.equals\r\n2. scripts/validate_docstrings.py --format=actions --errors=ES01 pandas.CategoricalIndex.map\r\n\r\n- [x] xref https://github.com/pandas-dev/pandas/issues/57438\r\n- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57611"},"created_at":{"kind":"string","value":"2024-02-25T07:50:42Z"},"closed_at":{"kind":"string","value":"2024-02-26T23:05:32Z"},"merged_at":{"kind":"string","value":"2024-02-26T23:05:32Z"},"updated_at":{"kind":"string","value":"2024-03-11T00:19:59Z"}}},{"rowIdx":861,"cells":{"title":{"kind":"string","value":"Doc: fix ES01 for pandas.CategoricalDtype"},"diff":{"kind":"string","value":"diff --git a/ci/code_checks.sh b/ci/code_checks.sh\nindex 47a2cf93a4f89..e6c47250afaa4 100755\n--- a/ci/code_checks.sh\n+++ b/ci/code_checks.sh\n@@ -423,7 +423,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n pandas.Categorical.ordered\\\n pandas.Categorical.remove_unused_categories\\\n pandas.Categorical.rename_categories\\\n- pandas.CategoricalDtype\\\n pandas.CategoricalDtype.categories\\\n pandas.CategoricalDtype.ordered\\\n pandas.CategoricalIndex.as_ordered\\\ndiff --git a/pandas/core/dtypes/dtypes.py b/pandas/core/dtypes/dtypes.py\nindex 12dcd8b0d42af..10635edb5e244 100644\n--- a/pandas/core/dtypes/dtypes.py\n+++ b/pandas/core/dtypes/dtypes.py\n@@ -157,6 +157,17 @@ class CategoricalDtype(PandasExtensionDtype, ExtensionDtype):\n \"\"\"\n Type for categorical data with the categories and orderedness.\n \n+ A categorical's type is fully described by\n+ 1. categories: a sequence of unique values and no missing values\n+ 2. ordered: a boolean\n+ This information can be stored in a CategoricalDtype. The categories argument\n+ is optional, which implies that the actual categories should be inferred from\n+ whatever is present in the data when the pandas.Categorical is created.\n+ The categories are assumed to be unordered by default.\n+\n+ A CategoricalDtype can be used in any place pandas expects a dtype. For example\n+ pandas.read_csv(), pandas.DataFrame.astype(), or in the Series constructor.\n+\n Parameters\n ----------\n categories : sequence, optional\n"},"body":{"kind":"string","value":"All ES01 Errors resolved in the following cases:\r\n\r\n1. scripts/validate_docstrings.py --format=actions --errors=ES01 pandas.CategoricalDtype\r\n\r\n- [x] xref #57440\r\n- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57610"},"created_at":{"kind":"string","value":"2024-02-25T07:24:48Z"},"closed_at":{"kind":"string","value":"2024-02-26T17:59:11Z"},"merged_at":{"kind":"null"},"updated_at":{"kind":"string","value":"2024-02-26T18:23:35Z"}}},{"rowIdx":862,"cells":{"title":{"kind":"string","value":"Doc: resolve GL08 for pandas.core.groupby.SeriesGroupBy.value_counts"},"diff":{"kind":"string","value":"diff --git a/ci/code_checks.sh b/ci/code_checks.sh\nindex 6de0a8c2ca325..22c3a71812de7 100755\n--- a/ci/code_checks.sh\n+++ b/ci/code_checks.sh\n@@ -178,7 +178,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n pandas.Timestamp.tzinfo\\\n pandas.Timestamp.value\\\n pandas.Timestamp.year\\\n- pandas.core.groupby.SeriesGroupBy.value_counts\\\n pandas.tseries.offsets.BQuarterBegin.is_anchored\\\n pandas.tseries.offsets.BQuarterBegin.is_on_offset\\\n pandas.tseries.offsets.BQuarterBegin.n\\\ndiff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py\nindex 3b7963693bcae..a604283f3d078 100644\n--- a/pandas/core/groupby/generic.py\n+++ b/pandas/core/groupby/generic.py\n@@ -801,6 +801,85 @@ def value_counts(\n bins=None,\n dropna: bool = True,\n ) -> Series | DataFrame:\n+ \"\"\"\n+ Return a Series or DataFrame containing counts of unique rows.\n+\n+ .. versionadded:: 1.4.0\n+\n+ Parameters\n+ ----------\n+ normalize : bool, default False\n+ Return proportions rather than frequencies.\n+ sort : bool, default True\n+ Sort by frequencies.\n+ ascending : bool, default False\n+ Sort in ascending order.\n+ bins : int or list of ints, optional\n+ Rather than count values, group them into half-open bins,\n+ a convenience for pd.cut, only works with numeric data.\n+ dropna : bool, default True\n+ Don't include counts of rows that contain NA values.\n+\n+ Returns\n+ -------\n+ Series or DataFrame\n+ Series if the groupby ``as_index`` is True, otherwise DataFrame.\n+\n+ See Also\n+ --------\n+ Series.value_counts: Equivalent method on Series.\n+ DataFrame.value_counts: Equivalent method on DataFrame.\n+ DataFrameGroupBy.value_counts: Equivalent method on DataFrameGroupBy.\n+\n+ Notes\n+ -----\n+ - If the groupby ``as_index`` is True then the returned Series will have a\n+ MultiIndex with one level per input column.\n+ - If the groupby ``as_index`` is False then the returned DataFrame will have an\n+ additional column with the value_counts. The column is labelled 'count' or\n+ 'proportion', depending on the ``normalize`` parameter.\n+\n+ By default, rows that contain any NA values are omitted from\n+ the result.\n+\n+ By default, the result will be in descending order so that the\n+ first element of each group is the most frequently-occurring row.\n+\n+ Examples\n+ --------\n+ >>> s = pd.Series(\n+ ... [1, 1, 2, 3, 2, 3, 3, 1, 1, 3, 3, 3],\n+ ... index=[\"A\", \"A\", \"A\", \"A\", \"A\", \"A\", \"B\", \"B\", \"B\", \"B\", \"B\", \"B\"],\n+ ... )\n+ >>> s\n+ A 1\n+ A 1\n+ A 2\n+ A 3\n+ A 2\n+ A 3\n+ B 3\n+ B 1\n+ B 1\n+ B 3\n+ B 3\n+ B 3\n+ dtype: int64\n+ >>> g1 = s.groupby(s.index)\n+ >>> g1.value_counts(bins=2)\n+ A (0.997, 2.0] 4\n+ (2.0, 3.0] 2\n+ B (2.0, 3.0] 4\n+ (0.997, 2.0] 2\n+ Name: count, dtype: int64\n+ >>> g1.value_counts(normalize=True)\n+ A 1 0.333333\n+ 2 0.333333\n+ 3 0.333333\n+ B 3 0.666667\n+ 1 0.333333\n+ Name: proportion, dtype: float64\n+ \"\"\"\n name = \"proportion\" if normalize else \"count\"\n \n if bins is None:\n@@ -2303,7 +2382,7 @@ def value_counts(\n Returns\n -------\n Series or DataFrame\n- Series if the groupby as_index is True, otherwise DataFrame.\n+ Series if the groupby ``as_index`` is True, otherwise DataFrame.\n \n See Also\n --------\n@@ -2313,9 +2392,9 @@ def value_counts(\n \n Notes\n -----\n- - If the groupby as_index is True then the returned Series will have a\n+ - If the groupby ``as_index`` is True then the returned Series will have a\n MultiIndex with one level per input column.\n- - If the groupby as_index is False then the returned DataFrame will have an\n+ - If the groupby ``as_index`` is False then the returned DataFrame will have an\n additional column with the value_counts. The column is labelled 'count' or\n 'proportion', depending on the ``normalize`` parameter.\n \n"},"body":{"kind":"string","value":"All GL08 Errors resolved in the following cases:\r\n\r\n1. scripts/validate_docstrings.py --format=actions --errors=GL08 pandas.core.groupby.SeriesGroupBy.value_counts\r\n\r\n- [x] xref https://github.com/pandas-dev/pandas/issues/57443\r\n- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57609"},"created_at":{"kind":"string","value":"2024-02-25T06:31:48Z"},"closed_at":{"kind":"string","value":"2024-02-26T22:34:41Z"},"merged_at":{"kind":"string","value":"2024-02-26T22:34:41Z"},"updated_at":{"kind":"string","value":"2024-02-26T22:34:49Z"}}},{"rowIdx":863,"cells":{"title":{"kind":"string","value":"TYP: misc annotations"},"diff":{"kind":"string","value":"diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml\nindex 3253f9ab87363..e683fc50c1c5d 100644\n--- a/.pre-commit-config.yaml\n+++ b/.pre-commit-config.yaml\n@@ -127,7 +127,7 @@ repos:\n types: [python]\n stages: [manual]\n additional_dependencies: &pyright_dependencies\n- - pyright@1.1.350\n+ - pyright@1.1.351\n - id: pyright\n # note: assumes python env is setup and activated\n name: pyright reportGeneralTypeIssues\ndiff --git a/pandas/_libs/tslibs/nattype.pyi b/pandas/_libs/tslibs/nattype.pyi\nindex bd86a6fdc2174..f49e894a0bfec 100644\n--- a/pandas/_libs/tslibs/nattype.pyi\n+++ b/pandas/_libs/tslibs/nattype.pyi\n@@ -1,20 +1,30 @@\n from datetime import (\n+ date as date_,\n datetime,\n+ time as time_,\n timedelta,\n tzinfo as _tzinfo,\n )\n-import typing\n+from typing import (\n+ Literal,\n+ NoReturn,\n+ TypeAlias,\n+)\n \n import numpy as np\n \n from pandas._libs.tslibs.period import Period\n-from pandas._typing import Self\n+from pandas._typing import (\n+ Frequency,\n+ Self,\n+ TimestampNonexistent,\n+)\n \n NaT: NaTType\n iNaT: int\n nat_strings: set[str]\n \n-_NaTComparisonTypes: typing.TypeAlias = (\n+_NaTComparisonTypes: TypeAlias = (\n datetime | timedelta | Period | np.datetime64 | np.timedelta64\n )\n \n@@ -61,18 +71,38 @@ class NaTType:\n def week(self) -> float: ...\n @property\n def weekofyear(self) -> float: ...\n+ @property\n+ def fold(self) -> int: ...\n def day_name(self) -> float: ...\n def month_name(self) -> float: ...\n def weekday(self) -> float: ...\n def isoweekday(self) -> float: ...\n+ def isoformat(self, sep: str = ..., timespec: str = ...) -> str: ...\n+ def strftime(self, format: str) -> NoReturn: ...\n def total_seconds(self) -> float: ...\n def today(self, *args, **kwargs) -> NaTType: ...\n def now(self, *args, **kwargs) -> NaTType: ...\n def to_pydatetime(self) -> NaTType: ...\n def date(self) -> NaTType: ...\n- def round(self) -> NaTType: ...\n- def floor(self) -> NaTType: ...\n- def ceil(self) -> NaTType: ...\n+ def round(\n+ self,\n+ freq: Frequency,\n+ ambiguous: bool | Literal[\"raise\"] | NaTType = ...,\n+ nonexistent: TimestampNonexistent = ...,\n+ ) -> NaTType: ...\n+ def floor(\n+ self,\n+ freq: Frequency,\n+ ambiguous: bool | Literal[\"raise\"] | NaTType = ...,\n+ nonexistent: TimestampNonexistent = ...,\n+ ) -> NaTType: ...\n+ def ceil(\n+ self,\n+ freq: Frequency,\n+ ambiguous: bool | Literal[\"raise\"] | NaTType = ...,\n+ nonexistent: TimestampNonexistent = ...,\n+ ) -> NaTType: ...\n+ def combine(cls, date: date_, time: time_) -> NoReturn: ...\n @property\n def tzinfo(self) -> None: ...\n @property\n@@ -81,8 +111,8 @@ class NaTType:\n def tz_localize(\n self,\n tz: _tzinfo | str | None,\n- ambiguous: str = ...,\n- nonexistent: str = ...,\n+ ambiguous: bool | Literal[\"raise\"] | NaTType = ...,\n+ nonexistent: TimestampNonexistent = ...,\n ) -> NaTType: ...\n def replace(\n self,\n@@ -121,6 +151,8 @@ class NaTType:\n @property\n def days(self) -> float: ...\n @property\n+ def seconds(self) -> float: ...\n+ @property\n def microseconds(self) -> float: ...\n @property\n def nanoseconds(self) -> float: ...\ndiff --git a/pandas/_libs/tslibs/offsets.pyi b/pandas/_libs/tslibs/offsets.pyi\nindex 8f1e34522c026..791ebc0fbb245 100644\n--- a/pandas/_libs/tslibs/offsets.pyi\n+++ b/pandas/_libs/tslibs/offsets.pyi\n@@ -196,7 +196,10 @@ class WeekOfMonth(WeekOfMonthMixin):\n self, n: int = ..., normalize: bool = ..., week: int = ..., weekday: int = ...\n ) -> None: ...\n \n-class LastWeekOfMonth(WeekOfMonthMixin): ...\n+class LastWeekOfMonth(WeekOfMonthMixin):\n+ def __init__(\n+ self, n: int = ..., normalize: bool = ..., weekday: int = ...\n+ ) -> None: ...\n \n class FY5253Mixin(SingleConstructorOffset):\n def __init__(\ndiff --git a/pandas/_typing.py b/pandas/_typing.py\nindex 0bcf5284315d2..d7325fed93d62 100644\n--- a/pandas/_typing.py\n+++ b/pandas/_typing.py\n@@ -207,7 +207,7 @@ def __reversed__(self) -> Iterator[_T_co]:\n IndexLabel = Union[Hashable, Sequence[Hashable]]\n Level = Hashable\n Shape = tuple[int, ...]\n-Suffixes = tuple[Optional[str], Optional[str]]\n+Suffixes = Sequence[Optional[str]]\n Ordered = Optional[bool]\n JSONSerializable = Optional[Union[PythonScalar, list, dict]]\n Frequency = Union[str, \"BaseOffset\"]\n@@ -226,7 +226,7 @@ def __reversed__(self) -> Iterator[_T_co]:\n Dtype = Union[\"ExtensionDtype\", NpDtype]\n AstypeArg = Union[\"ExtensionDtype\", \"npt.DTypeLike\"]\n # DtypeArg specifies all allowable dtypes in a functions its dtype argument\n-DtypeArg = Union[Dtype, dict[Hashable, Dtype]]\n+DtypeArg = Union[Dtype, Mapping[Hashable, Dtype]]\n DtypeObj = Union[np.dtype, \"ExtensionDtype\"]\n \n # converters\ndiff --git a/pandas/core/dtypes/missing.py b/pandas/core/dtypes/missing.py\nindex cb751a2b44b59..ddfb7ea7f3696 100644\n--- a/pandas/core/dtypes/missing.py\n+++ b/pandas/core/dtypes/missing.py\n@@ -45,6 +45,8 @@\n if TYPE_CHECKING:\n from re import Pattern\n \n+ from pandas._libs.missing import NAType\n+ from pandas._libs.tslibs import NaTType\n from pandas._typing import (\n ArrayLike,\n DtypeObj,\n@@ -66,7 +68,7 @@\n \n \n @overload\n-def isna(obj: Scalar | Pattern) -> bool:\n+def isna(obj: Scalar | Pattern | NAType | NaTType) -> bool:\n ...\n \n \n@@ -283,7 +285,7 @@ def _isna_recarray_dtype(values: np.rec.recarray) -> npt.NDArray[np.bool_]:\n \n \n @overload\n-def notna(obj: Scalar) -> bool:\n+def notna(obj: Scalar | Pattern | NAType | NaTType) -> bool:\n ...\n \n \ndiff --git a/pandas/core/frame.py b/pandas/core/frame.py\nindex df413fda0255a..e5d424b15e69e 100644\n--- a/pandas/core/frame.py\n+++ b/pandas/core/frame.py\n@@ -4799,7 +4799,7 @@ def insert(\n self,\n loc: int,\n column: Hashable,\n- value: Scalar | AnyArrayLike,\n+ value: object,\n allow_duplicates: bool | lib.NoDefault = lib.no_default,\n ) -> None:\n \"\"\"\n@@ -6266,7 +6266,7 @@ def dropna(\n axis: Axis = 0,\n how: AnyAll | lib.NoDefault = lib.no_default,\n thresh: int | lib.NoDefault = lib.no_default,\n- subset: IndexLabel | None = None,\n+ subset: IndexLabel | AnyArrayLike | None = None,\n inplace: bool = False,\n ignore_index: bool = False,\n ) -> DataFrame | None:\n@@ -6390,7 +6390,7 @@ def dropna(\n if subset is not None:\n # subset needs to be list\n if not is_list_like(subset):\n- subset = [subset]\n+ subset = [cast(Hashable, subset)]\n ax = self._get_axis(agg_axis)\n indices = ax.get_indexer_for(subset)\n check = indices == -1\ndiff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py\nindex 3011fa235b22d..3b7963693bcae 100644\n--- a/pandas/core/groupby/generic.py\n+++ b/pandas/core/groupby/generic.py\n@@ -1326,7 +1326,7 @@ def hist(\n xrot: float | None = None,\n ylabelsize: int | None = None,\n yrot: float | None = None,\n- figsize: tuple[int, int] | None = None,\n+ figsize: tuple[float, float] | None = None,\n bins: int | Sequence[int] = 10,\n backend: str | None = None,\n legend: bool = False,\n@@ -2599,7 +2599,7 @@ def hist(\n ax=None,\n sharex: bool = False,\n sharey: bool = False,\n- figsize: tuple[int, int] | None = None,\n+ figsize: tuple[float, float] | None = None,\n layout: tuple[int, int] | None = None,\n bins: int | Sequence[int] = 10,\n backend: str | None = None,\ndiff --git a/pandas/core/reshape/merge.py b/pandas/core/reshape/merge.py\nindex 0494138d1e16f..d54bfec389a38 100644\n--- a/pandas/core/reshape/merge.py\n+++ b/pandas/core/reshape/merge.py\n@@ -445,7 +445,7 @@ def merge_asof(\n left_by=None,\n right_by=None,\n suffixes: Suffixes = (\"_x\", \"_y\"),\n- tolerance: int | Timedelta | None = None,\n+ tolerance: int | datetime.timedelta | None = None,\n allow_exact_matches: bool = True,\n direction: str = \"backward\",\n ) -> DataFrame:\n@@ -494,7 +494,7 @@ def merge_asof(\n suffixes : 2-length sequence (tuple, list, ...)\n Suffix to apply to overlapping column names in the left and right\n side, respectively.\n- tolerance : int or Timedelta, optional, default None\n+ tolerance : int or timedelta, optional, default None\n Select asof tolerance within this range; must be compatible\n with the merge index.\n allow_exact_matches : bool, default True\ndiff --git a/pandas/core/series.py b/pandas/core/series.py\nindex 5c9bc428e256f..bae95418c7641 100644\n--- a/pandas/core/series.py\n+++ b/pandas/core/series.py\n@@ -2891,7 +2891,7 @@ def autocorr(self, lag: int = 1) -> float:\n \"\"\"\n return self.corr(cast(Series, self.shift(lag)))\n \n- def dot(self, other: AnyArrayLike) -> Series | np.ndarray:\n+ def dot(self, other: AnyArrayLike | DataFrame) -> Series | np.ndarray:\n \"\"\"\n Compute the dot product between the Series and the columns of other.\n \n@@ -6346,7 +6346,7 @@ def mean(\n skipna: bool = True,\n numeric_only: bool = False,\n **kwargs,\n- ):\n+ ) -> Any:\n return NDFrame.mean(\n self, axis=axis, skipna=skipna, numeric_only=numeric_only, **kwargs\n )\n@@ -6358,7 +6358,7 @@ def median(\n skipna: bool = True,\n numeric_only: bool = False,\n **kwargs,\n- ):\n+ ) -> Any:\n return NDFrame.median(\n self, axis=axis, skipna=skipna, numeric_only=numeric_only, **kwargs\n )\ndiff --git a/pandas/io/excel/_base.py b/pandas/io/excel/_base.py\nindex cf9c3be97ee5c..f8d950db6642a 100644\n--- a/pandas/io/excel/_base.py\n+++ b/pandas/io/excel/_base.py\n@@ -76,6 +76,7 @@\n DtypeBackend,\n ExcelWriterIfSheetExists,\n FilePath,\n+ HashableT,\n IntStrT,\n ReadBuffer,\n Self,\n@@ -382,7 +383,7 @@ def read_excel(\n | str\n | Sequence[int]\n | Sequence[str]\n- | Callable[[str], bool]\n+ | Callable[[HashableT], bool]\n | None = ...,\n dtype: DtypeArg | None = ...,\n engine: Literal[\"xlrd\", \"openpyxl\", \"odf\", \"pyxlsb\", \"calamine\"] | None = ...,\n@@ -421,7 +422,7 @@ def read_excel(\n | str\n | Sequence[int]\n | Sequence[str]\n- | Callable[[str], bool]\n+ | Callable[[HashableT], bool]\n | None = ...,\n dtype: DtypeArg | None = ...,\n engine: Literal[\"xlrd\", \"openpyxl\", \"odf\", \"pyxlsb\", \"calamine\"] | None = ...,\n@@ -460,7 +461,7 @@ def read_excel(\n | str\n | Sequence[int]\n | Sequence[str]\n- | Callable[[str], bool]\n+ | Callable[[HashableT], bool]\n | None = None,\n dtype: DtypeArg | None = None,\n engine: Literal[\"xlrd\", \"openpyxl\", \"odf\", \"pyxlsb\", \"calamine\"] | None = None,\ndiff --git a/pandas/io/parsers/readers.py b/pandas/io/parsers/readers.py\nindex 2a42b4115d1a2..8995faa7ad346 100644\n--- a/pandas/io/parsers/readers.py\n+++ b/pandas/io/parsers/readers.py\n@@ -17,6 +17,7 @@\n TYPE_CHECKING,\n Any,\n Callable,\n+ Generic,\n Literal,\n NamedTuple,\n TypedDict,\n@@ -83,6 +84,7 @@\n DtypeArg,\n DtypeBackend,\n FilePath,\n+ HashableT,\n IndexLabel,\n ReadCsvBuffer,\n Self,\n@@ -90,6 +92,62 @@\n Unpack,\n UsecolsArgType,\n )\n+\n+ class _read_shared(TypedDict, Generic[HashableT], total=False):\n+ # annotations shared between read_csv/fwf/table's overloads\n+ # NOTE: Keep in sync with the annotations of the implementation\n+ sep: str | None | lib.NoDefault\n+ delimiter: str | None | lib.NoDefault\n+ header: int | Sequence[int] | None | Literal[\"infer\"]\n+ names: Sequence[Hashable] | None | lib.NoDefault\n+ index_col: IndexLabel | Literal[False] | None\n+ usecols: UsecolsArgType\n+ dtype: DtypeArg | None\n+ engine: CSVEngine | None\n+ converters: Mapping[HashableT, Callable] | None\n+ true_values: list | None\n+ false_values: list | None\n+ skipinitialspace: bool\n+ skiprows: list[int] | int | Callable[[Hashable], bool] | None\n+ skipfooter: int\n+ nrows: int | None\n+ na_values: Hashable | Iterable[Hashable] | Mapping[\n+ Hashable, Iterable[Hashable]\n+ ] | None\n+ keep_default_na: bool\n+ na_filter: bool\n+ verbose: bool | lib.NoDefault\n+ skip_blank_lines: bool\n+ parse_dates: bool | Sequence[Hashable] | None\n+ infer_datetime_format: bool | lib.NoDefault\n+ keep_date_col: bool | lib.NoDefault\n+ date_parser: Callable | lib.NoDefault\n+ date_format: str | dict[Hashable, str] | None\n+ dayfirst: bool\n+ cache_dates: bool\n+ compression: CompressionOptions\n+ thousands: str | None\n+ decimal: str\n+ lineterminator: str | None\n+ quotechar: str\n+ quoting: int\n+ doublequote: bool\n+ escapechar: str | None\n+ comment: str | None\n+ encoding: str | None\n+ encoding_errors: str | None\n+ dialect: str | csv.Dialect | None\n+ on_bad_lines: str\n+ delim_whitespace: bool | lib.NoDefault\n+ low_memory: bool\n+ memory_map: bool\n+ float_precision: Literal[\"high\", \"legacy\", \"round_trip\"] | None\n+ storage_options: StorageOptions | None\n+ dtype_backend: DtypeBackend | lib.NoDefault\n+else:\n+ _read_shared = dict\n+\n+\n _doc_read_csv_and_table = (\n r\"\"\"\n {summary}\n@@ -480,59 +538,6 @@ class _Fwf_Defaults(TypedDict):\n widths: None\n \n \n-class _read_shared(TypedDict, total=False):\n- # annotations shared between read_csv/fwf/table's overloads\n- # NOTE: Keep in sync with the annotations of the implementation\n- sep: str | None | lib.NoDefault\n- delimiter: str | None | lib.NoDefault\n- header: int | Sequence[int] | None | Literal[\"infer\"]\n- names: Sequence[Hashable] | None | lib.NoDefault\n- index_col: IndexLabel | Literal[False] | None\n- usecols: UsecolsArgType\n- dtype: DtypeArg | None\n- engine: CSVEngine | None\n- converters: Mapping[Hashable, Callable] | None\n- true_values: list | None\n- false_values: list | None\n- skipinitialspace: bool\n- skiprows: list[int] | int | Callable[[Hashable], bool] | None\n- skipfooter: int\n- nrows: int | None\n- na_values: Hashable | Iterable[Hashable] | Mapping[\n- Hashable, Iterable[Hashable]\n- ] | None\n- keep_default_na: bool\n- na_filter: bool\n- verbose: bool | lib.NoDefault\n- skip_blank_lines: bool\n- parse_dates: bool | Sequence[Hashable] | None\n- infer_datetime_format: bool | lib.NoDefault\n- keep_date_col: bool | lib.NoDefault\n- date_parser: Callable | lib.NoDefault\n- date_format: str | dict[Hashable, str] | None\n- dayfirst: bool\n- cache_dates: bool\n- compression: CompressionOptions\n- thousands: str | None\n- decimal: str\n- lineterminator: str | None\n- quotechar: str\n- quoting: int\n- doublequote: bool\n- escapechar: str | None\n- comment: str | None\n- encoding: str | None\n- encoding_errors: str | None\n- dialect: str | csv.Dialect | None\n- on_bad_lines: str\n- delim_whitespace: bool | lib.NoDefault\n- low_memory: bool\n- memory_map: bool\n- float_precision: Literal[\"high\", \"legacy\", \"round_trip\"] | None\n- storage_options: StorageOptions | None\n- dtype_backend: DtypeBackend | lib.NoDefault\n-\n-\n _fwf_defaults: _Fwf_Defaults = {\"colspecs\": \"infer\", \"infer_nrows\": 100, \"widths\": None}\n _c_unsupported = {\"skipfooter\"}\n _python_unsupported = {\"low_memory\", \"float_precision\"}\n@@ -685,7 +690,7 @@ def read_csv(\n *,\n iterator: Literal[True],\n chunksize: int | None = ...,\n- **kwds: Unpack[_read_shared],\n+ **kwds: Unpack[_read_shared[HashableT]],\n ) -> TextFileReader:\n ...\n \n@@ -696,7 +701,7 @@ def read_csv(\n *,\n iterator: bool = ...,\n chunksize: int,\n- **kwds: Unpack[_read_shared],\n+ **kwds: Unpack[_read_shared[HashableT]],\n ) -> TextFileReader:\n ...\n \n@@ -707,7 +712,7 @@ def read_csv(\n *,\n iterator: Literal[False] = ...,\n chunksize: None = ...,\n- **kwds: Unpack[_read_shared],\n+ **kwds: Unpack[_read_shared[HashableT]],\n ) -> DataFrame:\n ...\n \n@@ -718,7 +723,7 @@ def read_csv(\n *,\n iterator: bool = ...,\n chunksize: int | None = ...,\n- **kwds: Unpack[_read_shared],\n+ **kwds: Unpack[_read_shared[HashableT]],\n ) -> DataFrame | TextFileReader:\n ...\n \n@@ -748,7 +753,7 @@ def read_csv(\n # General Parsing Configuration\n dtype: DtypeArg | None = None,\n engine: CSVEngine | None = None,\n- converters: Mapping[Hashable, Callable] | None = None,\n+ converters: Mapping[HashableT, Callable] | None = None,\n true_values: list | None = None,\n false_values: list | None = None,\n skipinitialspace: bool = False,\n@@ -890,7 +895,7 @@ def read_table(\n *,\n iterator: Literal[True],\n chunksize: int | None = ...,\n- **kwds: Unpack[_read_shared],\n+ **kwds: Unpack[_read_shared[HashableT]],\n ) -> TextFileReader:\n ...\n \n@@ -901,7 +906,7 @@ def read_table(\n *,\n iterator: bool = ...,\n chunksize: int,\n- **kwds: Unpack[_read_shared],\n+ **kwds: Unpack[_read_shared[HashableT]],\n ) -> TextFileReader:\n ...\n \n@@ -912,7 +917,7 @@ def read_table(\n *,\n iterator: Literal[False] = ...,\n chunksize: None = ...,\n- **kwds: Unpack[_read_shared],\n+ **kwds: Unpack[_read_shared[HashableT]],\n ) -> DataFrame:\n ...\n \n@@ -923,7 +928,7 @@ def read_table(\n *,\n iterator: bool = ...,\n chunksize: int | None = ...,\n- **kwds: Unpack[_read_shared],\n+ **kwds: Unpack[_read_shared[HashableT]],\n ) -> DataFrame | TextFileReader:\n ...\n \n@@ -955,7 +960,7 @@ def read_table(\n # General Parsing Configuration\n dtype: DtypeArg | None = None,\n engine: CSVEngine | None = None,\n- converters: Mapping[Hashable, Callable] | None = None,\n+ converters: Mapping[HashableT, Callable] | None = None,\n true_values: list | None = None,\n false_values: list | None = None,\n skipinitialspace: bool = False,\n@@ -1091,7 +1096,7 @@ def read_fwf(\n infer_nrows: int = ...,\n iterator: Literal[True],\n chunksize: int | None = ...,\n- **kwds: Unpack[_read_shared],\n+ **kwds: Unpack[_read_shared[HashableT]],\n ) -> TextFileReader:\n ...\n \n@@ -1105,7 +1110,7 @@ def read_fwf(\n infer_nrows: int = ...,\n iterator: bool = ...,\n chunksize: int,\n- **kwds: Unpack[_read_shared],\n+ **kwds: Unpack[_read_shared[HashableT]],\n ) -> TextFileReader:\n ...\n \n@@ -1119,7 +1124,7 @@ def read_fwf(\n infer_nrows: int = ...,\n iterator: Literal[False] = ...,\n chunksize: None = ...,\n- **kwds: Unpack[_read_shared],\n+ **kwds: Unpack[_read_shared[HashableT]],\n ) -> DataFrame:\n ...\n \n@@ -1132,7 +1137,7 @@ def read_fwf(\n infer_nrows: int = 100,\n iterator: bool = False,\n chunksize: int | None = None,\n- **kwds: Unpack[_read_shared],\n+ **kwds: Unpack[_read_shared[HashableT]],\n ) -> DataFrame | TextFileReader:\n r\"\"\"\n Read a table of fixed-width formatted lines into DataFrame.\n"},"body":{"kind":"string","value":"to pass more of the pandas-stubs tests."},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57606"},"created_at":{"kind":"string","value":"2024-02-25T01:44:07Z"},"closed_at":{"kind":"string","value":"2024-02-26T18:28:44Z"},"merged_at":{"kind":"string","value":"2024-02-26T18:28:44Z"},"updated_at":{"kind":"string","value":"2024-04-07T10:59:14Z"}}},{"rowIdx":864,"cells":{"title":{"kind":"string","value":"DOC: fix RT03 for CategoricalIndex.set_categories, DataFrame.astype, DataFrame.at_time and DataFrame.ewm"},"diff":{"kind":"string","value":"diff --git a/ci/code_checks.sh b/ci/code_checks.sh\nindex 47a2cf93a4f89..e60e6cec9d89a 100755\n--- a/ci/code_checks.sh\n+++ b/ci/code_checks.sh\n@@ -1882,10 +1882,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n \n MSG='Partially validate docstrings (RT03)' ; echo $MSG\n $BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=RT03 --ignore_functions \\\n- pandas.CategoricalIndex.set_categories\\\n- pandas.DataFrame.astype\\\n- pandas.DataFrame.at_time\\\n- pandas.DataFrame.ewm\\\n pandas.DataFrame.expanding\\\n pandas.DataFrame.filter\\\n pandas.DataFrame.first_valid_index\\\ndiff --git a/pandas/core/generic.py b/pandas/core/generic.py\nindex 9424e421fd85f..f1af779e00232 100644\n--- a/pandas/core/generic.py\n+++ b/pandas/core/generic.py\n@@ -6197,6 +6197,7 @@ def astype(\n Returns\n -------\n same type as caller\n+ The pandas object casted to the specified ``dtype``.\n \n See Also\n --------\n@@ -8675,6 +8676,7 @@ def at_time(self, time, asof: bool = False, axis: Axis | None = None) -> Self:\n Returns\n -------\n Series or DataFrame\n+ The values with the specified time.\n \n Raises\n ------\ndiff --git a/pandas/core/window/ewm.py b/pandas/core/window/ewm.py\nindex 9b21a23b1aefe..b2855ff1f4048 100644\n--- a/pandas/core/window/ewm.py\n+++ b/pandas/core/window/ewm.py\n@@ -226,6 +226,8 @@ class ExponentialMovingWindow(BaseWindow):\n Returns\n -------\n pandas.api.typing.ExponentialMovingWindow\n+ An instance of ExponentialMovingWindow for further exponentially weighted (EW)\n+ calculations, e.g. using the ``mean`` method.\n \n See Also\n --------\n"},"body":{"kind":"string","value":"Resolve all RT03 errors for the following cases:\r\n\r\n1. scripts/validate_docstrings.py --format=actions --errors=RT03 pandas.CategoricalIndex.set_categories (already valid)\r\n2. scripts/validate_docstrings.py --format=actions --errors=RT03 pandas.DataFrame.astype\r\n3. scripts/validate_docstrings.py --format=actions --errors=RT03 pandas.DataFrame.at_time\r\n4. scripts/validate_docstrings.py --format=actions --errors=RT03 pandas.DataFrame.ewm\r\n\r\n- [ ] xref #57416 \r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57605"},"created_at":{"kind":"string","value":"2024-02-24T23:49:36Z"},"closed_at":{"kind":"string","value":"2024-02-26T18:29:43Z"},"merged_at":{"kind":"string","value":"2024-02-26T18:29:43Z"},"updated_at":{"kind":"string","value":"2024-02-26T18:29:49Z"}}},{"rowIdx":865,"cells":{"title":{"kind":"string","value":"DOC: ES01 fix for HDFS Methods"},"diff":{"kind":"string","value":"diff --git a/ci/code_checks.sh b/ci/code_checks.sh\nindex 47a2cf93a4f89..25bb691caed71 100755\n--- a/ci/code_checks.sh\n+++ b/ci/code_checks.sh\n@@ -521,10 +521,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n pandas.DatetimeIndex.year\\\n pandas.DatetimeTZDtype.tz\\\n pandas.DatetimeTZDtype.unit\\\n- pandas.HDFStore.get\\\n- pandas.HDFStore.info\\\n- pandas.HDFStore.keys\\\n- pandas.HDFStore.put\\\n pandas.Index.T\\\n pandas.Index.all\\\n pandas.Index.any\\\ndiff --git a/pandas/io/pytables.py b/pandas/io/pytables.py\nindex c7ee1cac2e14a..ccbf84e254940 100644\n--- a/pandas/io/pytables.py\n+++ b/pandas/io/pytables.py\n@@ -640,6 +640,12 @@ def keys(self, include: str = \"pandas\") -> list[str]:\n \"\"\"\n Return a list of keys corresponding to objects stored in HDFStore.\n \n+ The ``include`` parameter can be used to filter the returned\n+ list based on the type of objects to include. If ``include``\n+ is set to \"pandas\" (default), only pandas objects will\n+ be included in the list. If ``include`` is set to \"native\",\n+ only native HDF5 Table objects will be included in the list.\n+\n Parameters\n ----------\n \n@@ -776,6 +782,9 @@ def get(self, key: str):\n \"\"\"\n Retrieve pandas object stored in file.\n \n+ This method within the context of a Pandas HDFStore allows\n+ you to retrieve data that has been previously saved.\n+\n Parameters\n ----------\n key : str\n@@ -1107,6 +1116,10 @@ def put(\n \"\"\"\n Store object in HDFStore.\n \n+ It also offers options to control various aspects of the\n+ storage process, such as whether to write DataFrame index\n+ as a column, whether to remove missing values, etc.\n+\n Parameters\n ----------\n key : str\n@@ -1647,6 +1660,10 @@ def info(self) -> str:\n \"\"\"\n Print detailed information on the store.\n \n+ This method provides convenient ways to interact with data\n+ stored in HDFStore files, allowing users to easily access\n+ and inspect their content.\n+\n Returns\n -------\n str\n"},"body":{"kind":"string","value":"All ES01 Errors resolved in the following cases:\r\n\r\nscripts/validate_docstrings.py --format=actions --errors=ES01 pandas.HDFStore.put\r\nscripts/validate_docstrings.py --format=actions --errors=ES01 pandas.HDFStore.get\r\nscripts/validate_docstrings.py --format=actions --errors=ES01 pandas.HDFStore.info\r\nscripts/validate_docstrings.py --format=actions --errors=ES01 pandas.HDFStore.keys\r\n\r\n- [x] xref #57440 \r\n- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57604"},"created_at":{"kind":"string","value":"2024-02-24T19:30:39Z"},"closed_at":{"kind":"string","value":"2024-02-26T17:58:50Z"},"merged_at":{"kind":"null"},"updated_at":{"kind":"string","value":"2024-02-28T05:20:24Z"}}},{"rowIdx":866,"cells":{"title":{"kind":"string","value":"DOC: fix RT03 for pandas.Index.to_numpy and pandas.Categorial.set_categories "},"diff":{"kind":"string","value":"diff --git a/ci/code_checks.sh b/ci/code_checks.sh\nindex f1e7f6d477906..47a2cf93a4f89 100755\n--- a/ci/code_checks.sh\n+++ b/ci/code_checks.sh\n@@ -1882,8 +1882,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n \n MSG='Partially validate docstrings (RT03)' ; echo $MSG\n $BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=RT03 --ignore_functions \\\n- pandas.Index.to_numpy\\\n- pandas.Categorical.set_categories\\\n pandas.CategoricalIndex.set_categories\\\n pandas.DataFrame.astype\\\n pandas.DataFrame.at_time\\\ndiff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py\nindex 886fe4594c17b..49b8ba4c47811 100644\n--- a/pandas/core/arrays/categorical.py\n+++ b/pandas/core/arrays/categorical.py\n@@ -1064,14 +1064,14 @@ def set_categories(\n On the other hand this methods does not do checks (e.g., whether the\n old categories are included in the new categories on a reorder), which\n can result in surprising changes, for example when using special string\n- dtypes, which does not considers a S1 string equal to a single char\n+ dtypes, which do not consider a S1 string equal to a single char\n python string.\n \n Parameters\n ----------\n new_categories : Index-like\n The categories in new order.\n- ordered : bool, default False\n+ ordered : bool, default None\n Whether or not the categorical is treated as a ordered categorical.\n If not given, do not change the ordered information.\n rename : bool, default False\n@@ -1080,7 +1080,8 @@ def set_categories(\n \n Returns\n -------\n- Categorical with reordered categories.\n+ Categorical\n+ New categories to be used, with optional ordering changes.\n \n Raises\n ------\ndiff --git a/pandas/core/base.py b/pandas/core/base.py\nindex 7a3d6cb866ea5..4556b9ab4d4c9 100644\n--- a/pandas/core/base.py\n+++ b/pandas/core/base.py\n@@ -566,6 +566,8 @@ def to_numpy(\n Returns\n -------\n numpy.ndarray\n+ The NumPy ndarray holding the values from this Series or Index.\n+ The dtype of the array may differ. See Notes.\n \n See Also\n --------\n"},"body":{"kind":"string","value":"Resolve all errors for the following cases:\r\n\r\n1. scripts/validate_docstrings.py --format=actions --errors=RT03 pandas.Index.to_numpy\r\n2. scripts/validate_docstrings.py --format=actions --errors=RT03 pandas.Categorical.set_categories\r\n\r\nAlso fixes typos and wrong default value in docstring of pandas.Categorical.set_categories.\r\n\r\n- [ ] xref #57416 \r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57603"},"created_at":{"kind":"string","value":"2024-02-24T16:48:03Z"},"closed_at":{"kind":"string","value":"2024-02-24T18:34:28Z"},"merged_at":{"kind":"string","value":"2024-02-24T18:34:28Z"},"updated_at":{"kind":"string","value":"2024-02-24T23:16:57Z"}}},{"rowIdx":867,"cells":{"title":{"kind":"string","value":"DOC: Fixing GL08 errors for pandas.ExcelFile.sheet_names and pandas.MultiIndex.codes"},"diff":{"kind":"string","value":"diff --git a/ci/code_checks.sh b/ci/code_checks.sh\nindex 875e328110aaf..4a9e18fb33eaa 100755\n--- a/ci/code_checks.sh\n+++ b/ci/code_checks.sh\n@@ -145,7 +145,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n MSG='Partially validate docstrings (GL08)' ; echo $MSG\n $BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=GL08 --ignore_functions \\\n pandas.ExcelFile.book\\\n- pandas.ExcelFile.sheet_names\\\n pandas.Index.empty\\\n pandas.Index.names\\\n pandas.Index.view\\\n@@ -153,7 +152,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n pandas.IntervalIndex.length\\\n pandas.IntervalIndex.mid\\\n pandas.IntervalIndex.right\\\n- pandas.MultiIndex.codes\\\n pandas.Period.freq\\\n pandas.Period.ordinal\\\n pandas.PeriodIndex.freq\\\ndiff --git a/pandas/core/indexes/multi.py b/pandas/core/indexes/multi.py\nindex c59f756b4e146..119c86770af3e 100644\n--- a/pandas/core/indexes/multi.py\n+++ b/pandas/core/indexes/multi.py\n@@ -1078,6 +1078,29 @@ def levshape(self) -> Shape:\n \n @property\n def codes(self) -> tuple:\n+ \"\"\"\n+ Codes of the MultiIndex.\n+\n+ Codes are the position of the index value in the list of level values\n+ for each level.\n+\n+ Returns\n+ -------\n+ tuple of numpy.ndarray\n+ The codes of the MultiIndex. Each array in the tuple corresponds\n+ to a level in the MultiIndex.\n+\n+ See Also\n+ --------\n+ MultiIndex.set_codes : Set new codes on MultiIndex.\n+\n+ Examples\n+ --------\n+ >>> arrays = [[1, 1, 2, 2], [\"red\", \"blue\", \"red\", \"blue\"]]\n+ >>> mi = pd.MultiIndex.from_arrays(arrays, names=(\"number\", \"color\"))\n+ >>> mi.codes\n+ (array([0, 0, 1, 1], dtype=int8), array([1, 0, 1, 0], dtype=int8))\n+ \"\"\"\n return self._codes\n \n def _set_codes(\ndiff --git a/pandas/io/excel/_base.py b/pandas/io/excel/_base.py\nindex f8d950db6642a..6fa23ef94d200 100644\n--- a/pandas/io/excel/_base.py\n+++ b/pandas/io/excel/_base.py\n@@ -1630,6 +1630,29 @@ def book(self):\n \n @property\n def sheet_names(self):\n+ \"\"\"\n+ Names of the sheets in the document.\n+\n+ This is particularly useful for loading a specific sheet into a DataFrame when\n+ you do not know the sheet names beforehand.\n+\n+ Returns\n+ -------\n+ list of str\n+ List of sheet names in the document.\n+\n+ See Also\n+ --------\n+ ExcelFile.parse : Parse a sheet into a DataFrame.\n+ read_excel : Read an Excel file into a pandas DataFrame. If you know the sheet\n+ names, it may be easier to specify them directly to read_excel.\n+\n+ Examples\n+ --------\n+ >>> file = pd.ExcelFile(\"myfile.xlsx\") # doctest: +SKIP\n+ >>> file.sheet_names # doctest: +SKIP\n+ [\"Sheet1\", \"Sheet2\"]\n+ \"\"\"\n return self._reader.sheet_names\n \n def close(self) -> None:\n"},"body":{"kind":"string","value":"Resolved GL08 errors for the following:\r\n\r\n1. scripts/validate_docstrings.py --format=actions --errors=GL08 pandas.ExcelFile.sheet_names\r\n2. scripts/validate_docstrings.py --format=actions --errors=GL08 pandas.MultiIndex.codes\r\n\r\nRef: #57443 \r\n\r\n- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)\r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57601"},"created_at":{"kind":"string","value":"2024-02-24T14:19:18Z"},"closed_at":{"kind":"string","value":"2024-02-27T22:10:03Z"},"merged_at":{"kind":"string","value":"2024-02-27T22:10:03Z"},"updated_at":{"kind":"string","value":"2024-02-28T03:45:10Z"}}},{"rowIdx":868,"cells":{"title":{"kind":"string","value":"DOC: Whatsnew notable bugfix on groupby behavior with unobserved groups"},"diff":{"kind":"string","value":"diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst\nindex 1f9f5e85a6c4b..da03c8f50086a 100644\n--- a/doc/source/whatsnew/v3.0.0.rst\n+++ b/doc/source/whatsnew/v3.0.0.rst\n@@ -43,10 +43,63 @@ Notable bug fixes\n \n These are bug fixes that might have notable behavior changes.\n \n-.. _whatsnew_300.notable_bug_fixes.notable_bug_fix1:\n+.. _whatsnew_300.notable_bug_fixes.groupby_unobs_and_na:\n \n-notable_bug_fix1\n-^^^^^^^^^^^^^^^^\n+Improved behavior in groupby for ``observed=False``\n+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n+\n+A number of bugs have been fixed due to improved handling of unobserved groups (:issue:`55738`). All remarks in this section equally impact :class:`.SeriesGroupBy`.\n+\n+In previous versions of pandas, a single grouping with :meth:`.DataFrameGroupBy.apply` or :meth:`.DataFrameGroupBy.agg` would pass the unobserved groups to the provided function, resulting in ``0`` below.\n+\n+.. ipython:: python\n+\n+ df = pd.DataFrame(\n+ {\n+ \"key1\": pd.Categorical(list(\"aabb\"), categories=list(\"abc\")),\n+ \"key2\": [1, 1, 1, 2],\n+ \"values\": [1, 2, 3, 4],\n+ }\n+ )\n+ df\n+ gb = df.groupby(\"key1\", observed=False)\n+ gb[[\"values\"]].apply(lambda x: x.sum())\n+\n+However this was not the case when using multiple groupings, resulting in ``NaN`` below.\n+\n+.. code-block:: ipython\n+\n+ In [1]: gb = df.groupby([\"key1\", \"key2\"], observed=False)\n+ In [2]: gb[[\"values\"]].apply(lambda x: x.sum())\n+ Out[2]:\n+ values\n+ key1 key2\n+ a 1 3.0\n+ 2 NaN\n+ b 1 3.0\n+ 2 4.0\n+ c 1 NaN\n+ 2 NaN\n+\n+Now using multiple groupings will also pass the unobserved groups to the provided function.\n+\n+.. ipython:: python\n+\n+ gb = df.groupby([\"key1\", \"key2\"], observed=False)\n+ gb[[\"values\"]].apply(lambda x: x.sum())\n+\n+Similarly:\n+\n+ - In previous versions of pandas the method :meth:`.DataFrameGroupBy.sum` would result in ``0`` for unobserved groups, but :meth:`.DataFrameGroupBy.prod`, :meth:`.DataFrameGroupBy.all`, and :meth:`.DataFrameGroupBy.any` would all result in NA values. Now these methods result in ``1``, ``True``, and ``False`` respectively.\n+ - :meth:`.DataFrameGroupBy.groups` did not include unobserved groups and now does.\n+\n+These improvements also fixed certain bugs in groupby:\n+\n+ - :meth:`.DataFrameGroupBy.nunique` would fail when there are multiple groupings, unobserved groups, and ``as_index=False`` (:issue:`52848`)\n+ - :meth:`.DataFrameGroupBy.agg` would fail when there are multiple groupings, unobserved groups, and ``as_index=False`` (:issue:`36698`)\n+ - :meth:`.DataFrameGroupBy.sum` would have incorrect values when there are multiple groupings, unobserved groups, and non-numeric data (:issue:`43891`)\n+ - :meth:`.DataFrameGroupBy.groups` with ``sort=False`` would sort groups; they now occur in the order they are observed (:issue:`56966`)\n+ - :meth:`.DataFrameGroupBy.value_counts` would produce incorrect results when used with some categorical and some non-categorical groupings and ``observed=False`` (:issue:`56016`)\n \n .. _whatsnew_300.notable_bug_fixes.notable_bug_fix2:\n \n@@ -259,12 +312,9 @@ Plotting\n \n Groupby/resample/rolling\n ^^^^^^^^^^^^^^^^^^^^^^^^\n+- Bug in :meth:`.DataFrameGroupBy.groups` and :meth:`.SeriesGroupby.groups` that would not respect groupby argument ``dropna`` (:issue:`55919`)\n - Bug in :meth:`.DataFrameGroupBy.quantile` when ``interpolation=\"nearest\"`` is inconsistent with :meth:`DataFrame.quantile` (:issue:`47942`)\n - Bug in :meth:`DataFrame.ewm` and :meth:`Series.ewm` when passed ``times`` and aggregation functions other than mean (:issue:`51695`)\n-- Bug in :meth:`.DataFrameGroupBy.groups` and :meth:`.SeriesGroupby.groups` that would not respect groupby arguments ``dropna`` and ``sort`` (:issue:`55919`, :issue:`56966`, :issue:`56851`)\n-- Bug in :meth:`.DataFrameGroupBy.nunique` and :meth:`.SeriesGroupBy.nunique` would fail with multiple categorical groupings when ``as_index=False`` (:issue:`52848`)\n-- Bug in :meth:`.DataFrameGroupBy.prod`, :meth:`.DataFrameGroupBy.any`, and :meth:`.DataFrameGroupBy.all` would result in NA values on unobserved groups; they now result in ``1``, ``False``, and ``True`` respectively (:issue:`55783`)\n-- Bug in :meth:`.DataFrameGroupBy.value_counts` would produce incorrect results when used with some categorical and some non-categorical groupings and ``observed=False`` (:issue:`56016`)\n -\n \n Reshaping\n"},"body":{"kind":"string","value":"- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)\r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n\r\nRef: https://github.com/pandas-dev/pandas/pull/55738#issuecomment-1937085332\r\n\r\nI made the section just focus on the unobserved fixes, leaving the dropna bugfixes where they are (they are quite minor).\r\n\r\ncc @jorisvandenbossche "},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57600"},"created_at":{"kind":"string","value":"2024-02-24T13:02:58Z"},"closed_at":{"kind":"string","value":"2024-02-26T18:31:47Z"},"merged_at":{"kind":"string","value":"2024-02-26T18:31:47Z"},"updated_at":{"kind":"string","value":"2024-02-27T08:43:05Z"}}},{"rowIdx":869,"cells":{"title":{"kind":"string","value":"REF: Move compute to BinGrouper.result_index_and_ids"},"diff":{"kind":"string","value":"diff --git a/pandas/core/groupby/ops.py b/pandas/core/groupby/ops.py\nindex 46ef0f38706bc..738b4970b0924 100644\n--- a/pandas/core/groupby/ops.py\n+++ b/pandas/core/groupby/ops.py\n@@ -1113,23 +1113,7 @@ def indices(self):\n \n @cache_readonly\n def group_info(self) -> tuple[npt.NDArray[np.intp], int]:\n- ngroups = self.ngroups\n- rep = np.diff(np.r_[0, self.bins])\n-\n- rep = ensure_platform_int(rep)\n- if ngroups == len(self.bins):\n- comp_ids = np.repeat(np.arange(ngroups), rep)\n- else:\n- comp_ids = np.repeat(np.r_[-1, np.arange(ngroups)], rep)\n-\n- return (ensure_platform_int(comp_ids), ngroups)\n-\n- @cache_readonly\n- def result_index(self) -> Index:\n- if len(self.binlabels) != 0 and isna(self.binlabels[0]):\n- return self.binlabels[1:]\n-\n- return self.binlabels\n+ return self.ids, self.ngroups\n \n @cache_readonly\n def codes(self) -> list[npt.NDArray[np.intp]]:\n@@ -1137,7 +1121,21 @@ def codes(self) -> list[npt.NDArray[np.intp]]:\n \n @cache_readonly\n def result_index_and_ids(self):\n- return self.result_index, self.group_info[0]\n+ result_index = self.binlabels\n+ if len(self.binlabels) != 0 and isna(self.binlabels[0]):\n+ result_index = result_index[1:]\n+\n+ ngroups = len(result_index)\n+ rep = np.diff(np.r_[0, self.bins])\n+\n+ rep = ensure_platform_int(rep)\n+ if ngroups == len(self.bins):\n+ ids = np.repeat(np.arange(ngroups), rep)\n+ else:\n+ ids = np.repeat(np.r_[-1, np.arange(ngroups)], rep)\n+ ids = ensure_platform_int(ids)\n+\n+ return result_index, ids\n \n @property\n def levels(self) -> list[Index]:\n"},"body":{"kind":"string","value":"- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)\r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n\r\nBaseGrouper does the compute in `result_index_and_ids` and other methods utilize this result. This refactors so BinGrouper behaves the same."},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57599"},"created_at":{"kind":"string","value":"2024-02-24T11:59:24Z"},"closed_at":{"kind":"string","value":"2024-02-24T18:29:05Z"},"merged_at":{"kind":"string","value":"2024-02-24T18:29:05Z"},"updated_at":{"kind":"string","value":"2024-02-24T20:45:53Z"}}},{"rowIdx":870,"cells":{"title":{"kind":"string","value":"CLN: Use group_info less"},"diff":{"kind":"string","value":"diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py\nindex c90ae4d590b45..3011fa235b22d 100644\n--- a/pandas/core/groupby/generic.py\n+++ b/pandas/core/groupby/generic.py\n@@ -813,7 +813,7 @@ def value_counts(\n from pandas.core.reshape.merge import get_join_indexers\n from pandas.core.reshape.tile import cut\n \n- ids, _ = self._grouper.group_info\n+ ids = self._grouper.ids\n val = self.obj._values\n \n index_names = self._grouper.names + [self.obj.name]\ndiff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py\nindex 668c9863612d8..de7055e31e2e8 100644\n--- a/pandas/core/groupby/groupby.py\n+++ b/pandas/core/groupby/groupby.py\n@@ -1228,7 +1228,7 @@ def _concat_objects(\n \n ax = self._selected_obj.index\n if self.dropna:\n- labels = self._grouper.group_info[0]\n+ labels = self._grouper.ids\n mask = labels != -1\n ax = ax[mask]\n \n@@ -1423,7 +1423,7 @@ def _numba_agg_general(\n )\n # Pass group ids to kernel directly if it can handle it\n # (This is faster since it doesn't require a sort)\n- ids, _ = self._grouper.group_info\n+ ids = self._grouper.ids\n ngroups = self._grouper.ngroups\n \n res_mgr = df._mgr.apply(\n@@ -4163,7 +4163,7 @@ def _nth(\n if not dropna:\n mask = self._make_mask_from_positional_indexer(n)\n \n- ids, _ = self._grouper.group_info\n+ ids = self._grouper.ids\n \n # Drop NA values in grouping\n mask = mask & (ids != -1)\n@@ -4503,7 +4503,7 @@ def ngroup(self, ascending: bool = True):\n \"\"\"\n obj = self._obj_with_exclusions\n index = obj.index\n- comp_ids = self._grouper.group_info[0]\n+ comp_ids = self._grouper.ids\n \n dtype: type\n if self._grouper.has_dropped_na:\n@@ -5382,7 +5382,7 @@ def _mask_selected_obj(self, mask: npt.NDArray[np.bool_]) -> NDFrameT:\n Series or DataFrame\n Filtered _selected_obj.\n \"\"\"\n- ids = self._grouper.group_info[0]\n+ ids = self._grouper.ids\n mask = mask & (ids != -1)\n return self._selected_obj[mask]\n \ndiff --git a/pandas/core/groupby/ops.py b/pandas/core/groupby/ops.py\nindex 46ef0f38706bc..b5e7c44b149c5 100644\n--- a/pandas/core/groupby/ops.py\n+++ b/pandas/core/groupby/ops.py\n@@ -716,7 +716,7 @@ def groups(self) -> dict[Hashable, Index]:\n @cache_readonly\n def is_monotonic(self) -> bool:\n # return if my group orderings are monotonic\n- return Index(self.group_info[0]).is_monotonic_increasing\n+ return Index(self.ids).is_monotonic_increasing\n \n @final\n @cache_readonly\n@@ -735,8 +735,7 @@ def group_info(self) -> tuple[npt.NDArray[np.intp], int]:\n @cache_readonly\n def codes_info(self) -> npt.NDArray[np.intp]:\n # return the codes of items in original grouped axis\n- ids, _ = self.group_info\n- return ids\n+ return self.ids\n \n @final\n @cache_readonly\n@@ -933,9 +932,7 @@ def agg_series(\n def _aggregate_series_pure_python(\n self, obj: Series, func: Callable\n ) -> npt.NDArray[np.object_]:\n- _, ngroups = self.group_info\n-\n- result = np.empty(ngroups, dtype=\"O\")\n+ result = np.empty(self.ngroups, dtype=\"O\")\n initialized = False\n \n splitter = self._get_splitter(obj)\n@@ -1073,7 +1070,7 @@ def nkeys(self) -> int:\n @cache_readonly\n def codes_info(self) -> npt.NDArray[np.intp]:\n # return the codes of items in original grouped axis\n- ids, _ = self.group_info\n+ ids = self.ids\n if self.indexer is not None:\n sorter = np.lexsort((ids, self.indexer))\n ids = ids[sorter]\n@@ -1133,7 +1130,7 @@ def result_index(self) -> Index:\n \n @cache_readonly\n def codes(self) -> list[npt.NDArray[np.intp]]:\n- return [self.group_info[0]]\n+ return [self.ids]\n \n @cache_readonly\n def result_index_and_ids(self):\n@@ -1150,7 +1147,7 @@ def names(self) -> list[Hashable]:\n @property\n def groupings(self) -> list[grouper.Grouping]:\n lev = self.binlabels\n- codes = self.group_info[0]\n+ codes = self.ids\n labels = lev.take(codes)\n ping = grouper.Grouping(\n labels, labels, in_axis=False, level=None, uniques=lev._values\ndiff --git a/pandas/tests/groupby/test_grouping.py b/pandas/tests/groupby/test_grouping.py\nindex 27b4508feb314..8474d4c1d2d1c 100644\n--- a/pandas/tests/groupby/test_grouping.py\n+++ b/pandas/tests/groupby/test_grouping.py\n@@ -776,10 +776,10 @@ def test_groupby_empty(self):\n # check group properties\n assert len(gr._grouper.groupings) == 1\n tm.assert_numpy_array_equal(\n- gr._grouper.group_info[0], np.array([], dtype=np.dtype(np.intp))\n+ gr._grouper.ids, np.array([], dtype=np.dtype(np.intp))\n )\n \n- assert gr._grouper.group_info[1] == 0\n+ assert gr._grouper.ngroups == 0\n \n # check name\n gb = s.groupby(s)\n"},"body":{"kind":"string","value":"- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)\r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n\r\nMy goal is to remove redundant methods in BaseGrouper / Grouping - group_info seems like a good candidate."},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57598"},"created_at":{"kind":"string","value":"2024-02-24T11:47:58Z"},"closed_at":{"kind":"string","value":"2024-02-24T18:27:37Z"},"merged_at":{"kind":"string","value":"2024-02-24T18:27:37Z"},"updated_at":{"kind":"string","value":"2024-02-24T20:46:08Z"}}},{"rowIdx":871,"cells":{"title":{"kind":"string","value":"DOC: ES01 fix for to_csv method"},"diff":{"kind":"string","value":"diff --git a/ci/code_checks.sh b/ci/code_checks.sh\nindex f1e7f6d477906..11257a49761ad 100755\n--- a/ci/code_checks.sh\n+++ b/ci/code_checks.sh\n@@ -476,7 +476,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n pandas.DataFrame.sparse.from_spmatrix\\\n pandas.DataFrame.sparse.to_coo\\\n pandas.DataFrame.sparse.to_dense\\\n- pandas.DataFrame.to_csv\\\n pandas.DataFrame.to_feather\\\n pandas.DataFrame.to_html\\\n pandas.DataFrame.to_markdown\\\ndiff --git a/pandas/core/generic.py b/pandas/core/generic.py\nindex 0880e6730fd93..f9cbce12e9da9 100644\n--- a/pandas/core/generic.py\n+++ b/pandas/core/generic.py\n@@ -3670,7 +3670,18 @@ def to_csv(\n storage_options: StorageOptions | None = None,\n ) -> str | None:\n r\"\"\"\n- Write object to a comma-separated values (csv) file.\n+ Write object to a comma-separated values (CSV) file.\n+\n+ This method enables users to write object to comma-separated values (CSV) file\n+ with customizable options. These options include specifying the delimiter,\n+ handling missing data, formatting numbers, selecting columns, including\n+ headers and row names, defining file opening modes, setting encoding and\n+ compression options, controlling quoting and escaping characters, specifying\n+ newline characters, managing chunk sizes, formatting datetime objects, handling\n+ errors during encoding/decoding, and providing storage connection options.\n+\n+ The method returns None if ``path_or_buf`` is not specified;\n+ otherwise, it returns the resulting CSV format as a string.\n \n Parameters\n ----------\n"},"body":{"kind":"string","value":"All ES01 Errors resolved in the following cases:\r\n\r\nscripts/validate_docstrings.py --format=actions --errors=ES01 pandas.DataFrame.to_csv \r\n\r\n- [x] xref #57440 \r\n- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57597"},"created_at":{"kind":"string","value":"2024-02-24T11:26:06Z"},"closed_at":{"kind":"string","value":"2024-02-26T17:58:27Z"},"merged_at":{"kind":"null"},"updated_at":{"kind":"string","value":"2024-02-26T17:58:28Z"}}},{"rowIdx":872,"cells":{"title":{"kind":"string","value":"PERF: groupby(...).__len__"},"diff":{"kind":"string","value":"diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst\nindex d44824183f05f..35c88d544c985 100644\n--- a/doc/source/whatsnew/v3.0.0.rst\n+++ b/doc/source/whatsnew/v3.0.0.rst\n@@ -178,6 +178,7 @@ Performance improvements\n - Performance improvement in :meth:`RangeIndex.take` returning a :class:`RangeIndex` instead of a :class:`Index` when possible. (:issue:`57445`)\n - Performance improvement in indexing operations for string dtypes (:issue:`56997`)\n - :meth:`Series.str.extract` returns a :class:`RangeIndex` columns instead of an :class:`Index` column when possible (:issue:`?``)\n+- Performance improvement in ``DataFrameGroupBy.__len__`` and ``SeriesGroupBy.__len__`` (:issue:`57595`)\n \n .. ---------------------------------------------------------------------------\n .. _whatsnew_300.bug_fixes:\ndiff --git a/pandas/conftest.py b/pandas/conftest.py\nindex 3add32293ea06..730b84fdc6201 100644\n--- a/pandas/conftest.py\n+++ b/pandas/conftest.py\n@@ -271,7 +271,7 @@ def axis(request):\n return request.param\n \n \n-@pytest.fixture(params=[True, False, None])\n+@pytest.fixture(params=[True, False])\n def observed(request):\n \"\"\"\n Pass in the observed keyword to groupby for [True, False]\ndiff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py\nindex 668c9863612d8..9768a932f73f6 100644\n--- a/pandas/core/groupby/groupby.py\n+++ b/pandas/core/groupby/groupby.py\n@@ -596,7 +596,7 @@ class BaseGroupBy(PandasObject, SelectionMixin[NDFrameT], GroupByIndexingMixin):\n \n @final\n def __len__(self) -> int:\n- return len(self.groups)\n+ return self._grouper.ngroups\n \n @final\n def __repr__(self) -> str:\ndiff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py\nindex 46a307e2f28d9..d02e22c29159f 100644\n--- a/pandas/tests/groupby/test_groupby.py\n+++ b/pandas/tests/groupby/test_groupby.py\n@@ -149,6 +149,29 @@ def test_len_nan_group():\n assert len(df.groupby([\"a\", \"b\"])) == 0\n \n \n+@pytest.mark.parametrize(\"keys\", [[\"a\"], [\"a\", \"b\"]])\n+def test_len_categorical(dropna, observed, keys):\n+ # GH#57595\n+ df = DataFrame(\n+ {\n+ \"a\": Categorical([1, 1, 2, np.nan], categories=[1, 2, 3]),\n+ \"b\": Categorical([1, 1, 2, np.nan], categories=[1, 2, 3]),\n+ \"c\": 1,\n+ }\n+ )\n+ gb = df.groupby(keys, observed=observed, dropna=dropna)\n+ result = len(gb)\n+ if observed and dropna:\n+ expected = 2\n+ elif observed and not dropna:\n+ expected = 3\n+ elif len(keys) == 1:\n+ expected = 3 if dropna else 4\n+ else:\n+ expected = 9 if dropna else 16\n+ assert result == expected, f\"{result} vs {expected}\"\n+\n+\n def test_basic_regression():\n # regression\n result = Series([1.0 * x for x in list(range(1, 10)) * 10])\n"},"body":{"kind":"string","value":"- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)\r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n\r\nEnabled by #55738. Prior to that, `ngroups` was not reliable.\r\n\r\n```\r\nsize = 100_000\r\ndf = pd.DataFrame(\r\n {\r\n \"a\": np.random.randint(0, 100, size),\r\n \"b\": np.random.randint(0, 100, size),\r\n }\r\n)\r\n%timeit len(df.groupby([\"a\", \"b\"]))\r\n\r\n# 161 ms ± 962 µs per loop (mean ± std. dev. of 7 runs, 10 loops each) <-- main\r\n# 4.96 ms ± 229 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) <-- PR\r\n```\r\n\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57595"},"created_at":{"kind":"string","value":"2024-02-23T23:21:07Z"},"closed_at":{"kind":"string","value":"2024-02-24T00:10:17Z"},"merged_at":{"kind":"string","value":"2024-02-24T00:10:17Z"},"updated_at":{"kind":"string","value":"2024-02-24T00:24:42Z"}}},{"rowIdx":873,"cells":{"title":{"kind":"string","value":"CLN: groupby.first/last unused compat"},"diff":{"kind":"string","value":"diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py\nindex 668c9863612d8..711ed1a564868 100644\n--- a/pandas/core/groupby/groupby.py\n+++ b/pandas/core/groupby/groupby.py\n@@ -3250,27 +3250,10 @@ def first(\n 1 5.0 1\n 3 6.0 3\n \"\"\"\n-\n- def first_compat(obj: NDFrameT):\n- def first(x: Series):\n- \"\"\"Helper function for first item that isn't NA.\"\"\"\n- arr = x.array[notna(x.array)]\n- if not len(arr):\n- return x.array.dtype.na_value\n- return arr[0]\n-\n- if isinstance(obj, DataFrame):\n- return obj.apply(first)\n- elif isinstance(obj, Series):\n- return first(obj)\n- else: # pragma: no cover\n- raise TypeError(type(obj))\n-\n return self._agg_general(\n numeric_only=numeric_only,\n min_count=min_count,\n alias=\"first\",\n- npfunc=first_compat,\n skipna=skipna,\n )\n \n@@ -3319,27 +3302,10 @@ def last(\n 1 5.0 2\n 3 6.0 3\n \"\"\"\n-\n- def last_compat(obj: NDFrameT):\n- def last(x: Series):\n- \"\"\"Helper function for last item that isn't NA.\"\"\"\n- arr = x.array[notna(x.array)]\n- if not len(arr):\n- return x.array.dtype.na_value\n- return arr[-1]\n-\n- if isinstance(obj, DataFrame):\n- return obj.apply(last)\n- elif isinstance(obj, Series):\n- return last(obj)\n- else: # pragma: no cover\n- raise TypeError(type(obj))\n-\n return self._agg_general(\n numeric_only=numeric_only,\n min_count=min_count,\n alias=\"last\",\n- npfunc=last_compat,\n skipna=skipna,\n )\n \n"},"body":{"kind":"string","value":"- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)\r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n\r\nIt used to be that any op winding up in `_cython_agg_general` needed a fallback. This is no longer the case since `first` and `last` now handle `object` dtype in the Cython code and `axis=1` has been removed.\r\n\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57589"},"created_at":{"kind":"string","value":"2024-02-23T21:09:33Z"},"closed_at":{"kind":"string","value":"2024-02-23T21:54:30Z"},"merged_at":{"kind":"null"},"updated_at":{"kind":"string","value":"2024-02-28T22:43:09Z"}}},{"rowIdx":874,"cells":{"title":{"kind":"string","value":"PERF: Return a RangeIndex from __getitem__ with a bool mask when possible"},"diff":{"kind":"string","value":"diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst\nindex d6e3ac1ea48cc..d07f4f9f05708 100644\n--- a/doc/source/whatsnew/v3.0.0.rst\n+++ b/doc/source/whatsnew/v3.0.0.rst\n@@ -167,6 +167,7 @@ Removal of prior version deprecations/changes\n \n Performance improvements\n ~~~~~~~~~~~~~~~~~~~~~~~~\n+- :meth:`Series.str.extract` returns a :class:`RangeIndex` columns instead of an :class:`Index` column when possible (:issue:`57542`)\n - Performance improvement in :class:`DataFrame` when ``data`` is a ``dict`` and ``columns`` is specified (:issue:`24368`)\n - Performance improvement in :meth:`DataFrame.join` for sorted but non-unique indexes (:issue:`56941`)\n - Performance improvement in :meth:`DataFrame.join` when left and/or right are non-unique and ``how`` is ``\"left\"``, ``\"right\"``, or ``\"inner\"`` (:issue:`56817`)\n@@ -175,11 +176,11 @@ Performance improvements\n - Performance improvement in :meth:`Index.join` by propagating cached attributes in cases where the result matches one of the inputs (:issue:`57023`)\n - Performance improvement in :meth:`Index.take` when ``indices`` is a full range indexer from zero to length of index (:issue:`56806`)\n - Performance improvement in :meth:`MultiIndex.equals` for equal length indexes (:issue:`56990`)\n+- Performance improvement in :meth:`RangeIndex.__getitem__` with a boolean mask returning a :class:`RangeIndex` instead of a :class:`Index` when possible. (:issue:`57588`)\n - Performance improvement in :meth:`RangeIndex.append` when appending the same index (:issue:`57252`)\n - Performance improvement in :meth:`RangeIndex.take` returning a :class:`RangeIndex` instead of a :class:`Index` when possible. (:issue:`57445`)\n-- Performance improvement in indexing operations for string dtypes (:issue:`56997`)\n-- :meth:`Series.str.extract` returns a :class:`RangeIndex` columns instead of an :class:`Index` column when possible (:issue:`?``)\n - Performance improvement in ``DataFrameGroupBy.__len__`` and ``SeriesGroupBy.__len__`` (:issue:`57595`)\n+- Performance improvement in indexing operations for string dtypes (:issue:`56997`)\n \n .. ---------------------------------------------------------------------------\n .. _whatsnew_300.bug_fixes:\ndiff --git a/pandas/core/indexes/range.py b/pandas/core/indexes/range.py\nindex 8a2e3fbf500a4..c5036a2b32967 100644\n--- a/pandas/core/indexes/range.py\n+++ b/pandas/core/indexes/range.py\n@@ -29,6 +29,7 @@\n doc,\n )\n \n+from pandas.core.dtypes.base import ExtensionDtype\n from pandas.core.dtypes.common import (\n ensure_platform_int,\n ensure_python_int,\n@@ -42,6 +43,7 @@\n from pandas.core import ops\n import pandas.core.common as com\n from pandas.core.construction import extract_array\n+from pandas.core.indexers import check_array_indexer\n import pandas.core.indexes.base as ibase\n from pandas.core.indexes.base import (\n Index,\n@@ -1048,6 +1050,18 @@ def __getitem__(self, key):\n \"and integer or boolean \"\n \"arrays are valid indices\"\n )\n+ elif com.is_bool_indexer(key):\n+ if isinstance(getattr(key, \"dtype\", None), ExtensionDtype):\n+ np_key = key.to_numpy(dtype=bool, na_value=False)\n+ else:\n+ np_key = np.asarray(key, dtype=bool)\n+ check_array_indexer(self._range, np_key) # type: ignore[arg-type]\n+ # Short circuit potential _shallow_copy check\n+ if np_key.all():\n+ return self._simple_new(self._range, name=self.name)\n+ elif not np_key.any():\n+ return self._simple_new(_empty_range, name=self.name)\n+ return self.take(np.flatnonzero(np_key))\n return super().__getitem__(key)\n \n def _getitem_slice(self, slobj: slice) -> Self:\ndiff --git a/pandas/tests/indexes/ranges/test_range.py b/pandas/tests/indexes/ranges/test_range.py\nindex d500687763a1e..8b4b7a5d70ee4 100644\n--- a/pandas/tests/indexes/ranges/test_range.py\n+++ b/pandas/tests/indexes/ranges/test_range.py\n@@ -623,3 +623,41 @@ def test_append_one_nonempty_preserve_step():\n expected = RangeIndex(0, -1, -1)\n result = RangeIndex(0).append([expected])\n tm.assert_index_equal(result, expected, exact=True)\n+\n+\n+def test_getitem_boolmask_all_true():\n+ ri = RangeIndex(3, name=\"foo\")\n+ expected = ri.copy()\n+ result = ri[[True] * 3]\n+ tm.assert_index_equal(result, expected, exact=True)\n+\n+\n+def test_getitem_boolmask_all_false():\n+ ri = RangeIndex(3, name=\"foo\")\n+ result = ri[[False] * 3]\n+ expected = RangeIndex(0, name=\"foo\")\n+ tm.assert_index_equal(result, expected, exact=True)\n+\n+\n+def test_getitem_boolmask_returns_rangeindex():\n+ ri = RangeIndex(3, name=\"foo\")\n+ result = ri[[False, True, True]]\n+ expected = RangeIndex(1, 3, name=\"foo\")\n+ tm.assert_index_equal(result, expected, exact=True)\n+\n+ result = ri[[True, False, True]]\n+ expected = RangeIndex(0, 3, 2, name=\"foo\")\n+ tm.assert_index_equal(result, expected, exact=True)\n+\n+\n+def test_getitem_boolmask_returns_index():\n+ ri = RangeIndex(4, name=\"foo\")\n+ result = ri[[True, True, False, True]]\n+ expected = Index([0, 1, 3], name=\"foo\")\n+ tm.assert_index_equal(result, expected)\n+\n+\n+def test_getitem_boolmask_wrong_length():\n+ ri = RangeIndex(4, name=\"foo\")\n+ with pytest.raises(IndexError, match=\"Boolean index has wrong length\"):\n+ ri[[True]]\ndiff --git a/pandas/tests/io/pytables/test_append.py b/pandas/tests/io/pytables/test_append.py\nindex aff08e5ad3882..529d6d789596f 100644\n--- a/pandas/tests/io/pytables/test_append.py\n+++ b/pandas/tests/io/pytables/test_append.py\n@@ -132,6 +132,8 @@ def test_append_series(setup_path):\n \n # select on the index and values\n expected = ns[(ns > 70) & (ns.index < 90)]\n+ # Reading/writing RangeIndex info is not supported yet\n+ expected.index = Index(expected.index._data)\n result = store.select(\"ns\", \"foo>70 and index<90\")\n tm.assert_series_equal(result, expected, check_index_type=True)\n \n"},"body":{"kind":"string","value":"Discovered in https://github.com/pandas-dev/pandas/pull/57441\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57588"},"created_at":{"kind":"string","value":"2024-02-23T20:08:34Z"},"closed_at":{"kind":"string","value":"2024-03-02T02:24:32Z"},"merged_at":{"kind":"string","value":"2024-03-02T02:24:32Z"},"updated_at":{"kind":"string","value":"2024-03-02T02:24:35Z"}}},{"rowIdx":875,"cells":{"title":{"kind":"string","value":"DOC-#57585: Add `Use Modin` section on `Scaling to large datasets` page"},"diff":{"kind":"string","value":"diff --git a/doc/source/user_guide/scale.rst b/doc/source/user_guide/scale.rst\nindex b262de5d71439..080f8484ce969 100644\n--- a/doc/source/user_guide/scale.rst\n+++ b/doc/source/user_guide/scale.rst\n@@ -374,5 +374,33 @@ datasets.\n \n You see more dask examples at https://examples.dask.org.\n \n+Use Modin\n+---------\n+\n+Modin_ is a scalable dataframe library, which aims to be a drop-in replacement API for pandas and\n+provides the ability to scale pandas workflows across nodes and CPUs available. It is also able\n+to work with larger than memory datasets. To start working with Modin you just need\n+to replace a single line of code, namely, the import statement.\n+\n+.. code-block:: ipython\n+\n+ # import pandas as pd\n+ import modin.pandas as pd\n+\n+After you have changed the import statement, you can proceed using the well-known pandas API\n+to scale computation. Modin distributes computation across nodes and CPUs available utilizing\n+an execution engine it runs on. At the time of Modin 0.27.0 the following execution engines are supported\n+in Modin: Ray_, Dask_, `MPI through unidist`_, HDK_. The partitioning schema of a Modin DataFrame partitions it\n+along both columns and rows because it gives Modin flexibility and scalability in both the number of columns and\n+the number of rows.\n+\n+For more information refer to `Modin's documentation`_ or the `Modin's tutorials`_.\n+\n+.. _Modin: https://github.com/modin-project/modin\n+.. _`Modin's documentation`: https://modin.readthedocs.io/en/latest\n+.. _`Modin's tutorials`: https://github.com/modin-project/modin/tree/master/examples/tutorial/jupyter/execution\n+.. _Ray: https://github.com/ray-project/ray\n .. _Dask: https://dask.org\n+.. _`MPI through unidist`: https://github.com/modin-project/unidist\n+.. _HDK: https://github.com/intel-ai/hdk\n .. _dask.dataframe: https://docs.dask.org/en/latest/dataframe.html\n"},"body":{"kind":"string","value":"- [x] closes #57585 (Replace xxxx with the GitHub issue number)\r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57586"},"created_at":{"kind":"string","value":"2024-02-23T14:55:27Z"},"closed_at":{"kind":"string","value":"2024-03-07T17:17:03Z"},"merged_at":{"kind":"string","value":"2024-03-07T17:17:03Z"},"updated_at":{"kind":"string","value":"2024-03-07T17:17:43Z"}}},{"rowIdx":876,"cells":{"title":{"kind":"string","value":"Backport PR #57582 on branch 2.2.x (DOC: Add contributors for 2.2.1)"},"diff":{"kind":"string","value":"diff --git a/doc/source/whatsnew/v2.2.0.rst b/doc/source/whatsnew/v2.2.0.rst\nindex d9ab0452c8334..e015afb17dce5 100644\n--- a/doc/source/whatsnew/v2.2.0.rst\n+++ b/doc/source/whatsnew/v2.2.0.rst\n@@ -946,4 +946,4 @@ Other\n Contributors\n ~~~~~~~~~~~~\n \n-.. contributors:: v2.1.4..v2.2.0|HEAD\n+.. contributors:: v2.1.4..v2.2.0\ndiff --git a/doc/source/whatsnew/v2.2.1.rst b/doc/source/whatsnew/v2.2.1.rst\nindex f4ed594613349..310dd921e44f6 100644\n--- a/doc/source/whatsnew/v2.2.1.rst\n+++ b/doc/source/whatsnew/v2.2.1.rst\n@@ -86,3 +86,5 @@ Other\n \n Contributors\n ~~~~~~~~~~~~\n+\n+.. contributors:: v2.2.0..v2.2.1|HEAD\n"},"body":{"kind":"string","value":"Backport PR #57582: DOC: Add contributors for 2.2.1"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57583"},"created_at":{"kind":"string","value":"2024-02-23T14:21:06Z"},"closed_at":{"kind":"string","value":"2024-02-23T14:48:32Z"},"merged_at":{"kind":"string","value":"2024-02-23T14:48:32Z"},"updated_at":{"kind":"string","value":"2024-02-23T14:48:32Z"}}},{"rowIdx":877,"cells":{"title":{"kind":"string","value":"DOC: Add contributors for 2.2.1"},"diff":{"kind":"string","value":"diff --git a/doc/source/whatsnew/v2.2.0.rst b/doc/source/whatsnew/v2.2.0.rst\nindex 9d29044c27833..329ef2859f56f 100644\n--- a/doc/source/whatsnew/v2.2.0.rst\n+++ b/doc/source/whatsnew/v2.2.0.rst\n@@ -948,4 +948,4 @@ Other\n Contributors\n ~~~~~~~~~~~~\n \n-.. contributors:: v2.1.4..v2.2.0|HEAD\n+.. contributors:: v2.1.4..v2.2.0\ndiff --git a/doc/source/whatsnew/v2.2.1.rst b/doc/source/whatsnew/v2.2.1.rst\nindex f4ed594613349..310dd921e44f6 100644\n--- a/doc/source/whatsnew/v2.2.1.rst\n+++ b/doc/source/whatsnew/v2.2.1.rst\n@@ -86,3 +86,5 @@ Other\n \n Contributors\n ~~~~~~~~~~~~\n+\n+.. contributors:: v2.2.0..v2.2.1|HEAD\n"},"body":{"kind":"string","value":"- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)\r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57582"},"created_at":{"kind":"string","value":"2024-02-23T13:48:36Z"},"closed_at":{"kind":"string","value":"2024-02-23T14:20:56Z"},"merged_at":{"kind":"string","value":"2024-02-23T14:20:56Z"},"updated_at":{"kind":"string","value":"2024-02-23T14:20:57Z"}}},{"rowIdx":878,"cells":{"title":{"kind":"string","value":"Updating timeseries.offset_aliases links to use :ref: format"},"diff":{"kind":"string","value":"diff --git a/pandas/core/generic.py b/pandas/core/generic.py\nindex 668672ed05f72..0880e6730fd93 100644\n--- a/pandas/core/generic.py\n+++ b/pandas/core/generic.py\n@@ -8569,8 +8569,8 @@ def asfreq(\n \n Notes\n -----\n- To learn more about the frequency strings, please see `this link\n- <https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.\n+ To learn more about the frequency strings, please see\n+ :ref:`this link<timeseries.offset_aliases>`.\n \n Examples\n --------\ndiff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py\nindex 7c9fe0df9d022..668c9863612d8 100644\n--- a/pandas/core/groupby/groupby.py\n+++ b/pandas/core/groupby/groupby.py\n@@ -3643,8 +3643,8 @@ def rolling(\n If a timedelta, str, or offset, the time period of each window. Each\n window will be a variable sized based on the observations included in\n the time-period. This is only valid for datetimelike indexes.\n- To learn more about the offsets & frequency strings, please see `this link\n- <https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.\n+ To learn more about the offsets & frequency strings, please see\n+ :ref:`this link<timeseries.offset_aliases>`.\n \n If a BaseIndexer subclass, the window boundaries\n based on the defined ``get_window_bounds`` method. Additional rolling\ndiff --git a/pandas/core/groupby/grouper.py b/pandas/core/groupby/grouper.py\nindex 9179bec86f660..1578bde0781ef 100644\n--- a/pandas/core/groupby/grouper.py\n+++ b/pandas/core/groupby/grouper.py\n@@ -79,8 +79,7 @@ class Grouper:\n freq : str / frequency object, defaults to None\n This will groupby the specified frequency if the target selection\n (via key or level) is a datetime-like object. For full specification\n- of available frequencies, please see `here\n- <https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`_.\n+ of available frequencies, please see :ref:`here<timeseries.offset_aliases>`.\n sort : bool, default to False\n Whether to sort the resulting labels.\n closed : {'left' or 'right'}\ndiff --git a/pandas/core/indexes/datetimes.py b/pandas/core/indexes/datetimes.py\nindex 282a11122211b..b7d2437cbaa44 100644\n--- a/pandas/core/indexes/datetimes.py\n+++ b/pandas/core/indexes/datetimes.py\n@@ -246,8 +246,8 @@ class DatetimeIndex(DatetimeTimedeltaMixin):\n \n Notes\n -----\n- To learn more about the frequency strings, please see `this link\n- <https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.\n+ To learn more about the frequency strings, please see\n+ :ref:`this link<timeseries.offset_aliases>`.\n \n Examples\n --------\n@@ -896,8 +896,8 @@ def date_range(\n ``DatetimeIndex`` will have ``periods`` linearly spaced elements between\n ``start`` and ``end`` (closed on both sides).\n \n- To learn more about the frequency strings, please see `this link\n- <https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.\n+ To learn more about the frequency strings, please see\n+ :ref:`this link<timeseries.offset_aliases>`.\n \n Examples\n --------\n@@ -1083,8 +1083,8 @@ def bdate_range(\n for ``bdate_range``. Use ``date_range`` if specifying ``freq`` is not\n desired.\n \n- To learn more about the frequency strings, please see `this link\n- <https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.\n+ To learn more about the frequency strings, please see\n+ :ref:`this link<timeseries.offset_aliases>`.\n \n Examples\n --------\ndiff --git a/pandas/core/indexes/interval.py b/pandas/core/indexes/interval.py\nindex 7695193a15608..ea3e848356ab5 100644\n--- a/pandas/core/indexes/interval.py\n+++ b/pandas/core/indexes/interval.py\n@@ -1004,8 +1004,8 @@ def interval_range(\n ``IntervalIndex`` will have ``periods`` linearly spaced elements between\n ``start`` and ``end``, inclusively.\n \n- To learn more about datetime-like frequency strings, please see `this link\n- <https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.\n+ To learn more about datetime-like frequency strings, please see\n+ :ref:`this link<timeseries.offset_aliases>`.\n \n Examples\n --------\ndiff --git a/pandas/core/indexes/period.py b/pandas/core/indexes/period.py\nindex 4aee8293049f1..edd1fdd4da943 100644\n--- a/pandas/core/indexes/period.py\n+++ b/pandas/core/indexes/period.py\n@@ -551,8 +551,8 @@ def period_range(\n Of the three parameters: ``start``, ``end``, and ``periods``, exactly two\n must be specified.\n \n- To learn more about the frequency strings, please see `this link\n- <https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.\n+ To learn more about the frequency strings, please see\n+ :ref:`this link<timeseries.offset_aliases>`.\n \n Examples\n --------\ndiff --git a/pandas/core/indexes/timedeltas.py b/pandas/core/indexes/timedeltas.py\nindex 485c7a1ce08cd..a929687544876 100644\n--- a/pandas/core/indexes/timedeltas.py\n+++ b/pandas/core/indexes/timedeltas.py\n@@ -109,8 +109,8 @@ class TimedeltaIndex(DatetimeTimedeltaMixin):\n \n Notes\n -----\n- To learn more about the frequency strings, please see `this link\n- <https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.\n+ To learn more about the frequency strings, please see\n+ :ref:`this link<timeseries.offset_aliases>`.\n \n Examples\n --------\n@@ -311,8 +311,8 @@ def timedelta_range(\n ``TimedeltaIndex`` will have ``periods`` linearly spaced elements between\n ``start`` and ``end`` (closed on both sides).\n \n- To learn more about the frequency strings, please see `this link\n- <https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.\n+ To learn more about the frequency strings, please see\n+ :ref:`this link<timeseries.offset_aliases>`.\n \n Examples\n --------\ndiff --git a/pandas/core/window/rolling.py b/pandas/core/window/rolling.py\nindex aa55dd41f0997..ac2c10447dee9 100644\n--- a/pandas/core/window/rolling.py\n+++ b/pandas/core/window/rolling.py\n@@ -872,8 +872,8 @@ class Window(BaseWindow):\n If a timedelta, str, or offset, the time period of each window. Each\n window will be a variable sized based on the observations included in\n the time-period. This is only valid for datetimelike indexes.\n- To learn more about the offsets & frequency strings, please see `this link\n- <https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.\n+ To learn more about the offsets & frequency strings, please see\n+ :ref:`this link<timeseries.offset_aliases>`.\n \n If a BaseIndexer subclass, the window boundaries\n based on the defined ``get_window_bounds`` method. Additional rolling\n"},"body":{"kind":"string","value":"During code review on https://github.com/pandas-dev/pandas/pull/57562 it was suggested to update the links from this format\r\n\r\n`this link <https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.\r\n\r\nto this format \r\n\r\n:ref:`this link<timeseries.offset_aliases>`\r\n\r\nI found several places where this same link was using this old format, so opened this PR to update them all for consistency. \r\n\r\n- [x] xref https://github.com/pandas-dev/pandas/pull/57562\r\n- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57581"},"created_at":{"kind":"string","value":"2024-02-23T07:47:20Z"},"closed_at":{"kind":"string","value":"2024-02-23T09:55:27Z"},"merged_at":{"kind":"string","value":"2024-02-23T09:55:27Z"},"updated_at":{"kind":"string","value":"2024-02-23T17:04:21Z"}}},{"rowIdx":879,"cells":{"title":{"kind":"string","value":"Backport PR #57576 on branch 2.2.x (DOC: Add release date for 2.2.1)"},"diff":{"kind":"string","value":"diff --git a/doc/source/whatsnew/v2.2.1.rst b/doc/source/whatsnew/v2.2.1.rst\nindex fa5304c1c3b56..f4ed594613349 100644\n--- a/doc/source/whatsnew/v2.2.1.rst\n+++ b/doc/source/whatsnew/v2.2.1.rst\n@@ -1,6 +1,6 @@\n .. _whatsnew_221:\n \n-What's new in 2.2.1 (February XX, 2024)\n+What's new in 2.2.1 (February 22, 2024)\n ---------------------------------------\n \n These are the changes in pandas 2.2.1. See :ref:`release` for a full changelog\n"},"body":{"kind":"string","value":"Backport PR #57576: DOC: Add release date for 2.2.1"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57579"},"created_at":{"kind":"string","value":"2024-02-23T03:34:03Z"},"closed_at":{"kind":"string","value":"2024-02-23T04:47:35Z"},"merged_at":{"kind":"string","value":"2024-02-23T04:47:35Z"},"updated_at":{"kind":"string","value":"2024-02-23T04:47:35Z"}}},{"rowIdx":880,"cells":{"title":{"kind":"string","value":"DOC: Add release date for 2.2.1"},"diff":{"kind":"string","value":"diff --git a/doc/source/whatsnew/v2.2.1.rst b/doc/source/whatsnew/v2.2.1.rst\nindex fa5304c1c3b56..f4ed594613349 100644\n--- a/doc/source/whatsnew/v2.2.1.rst\n+++ b/doc/source/whatsnew/v2.2.1.rst\n@@ -1,6 +1,6 @@\n .. _whatsnew_221:\n \n-What's new in 2.2.1 (February XX, 2024)\n+What's new in 2.2.1 (February 22, 2024)\n ---------------------------------------\n \n These are the changes in pandas 2.2.1. See :ref:`release` for a full changelog\n"},"body":{"kind":"string","value":"- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)\r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57576"},"created_at":{"kind":"string","value":"2024-02-23T02:51:14Z"},"closed_at":{"kind":"string","value":"2024-02-23T03:33:51Z"},"merged_at":{"kind":"string","value":"2024-02-23T03:33:51Z"},"updated_at":{"kind":"string","value":"2024-02-23T03:33:51Z"}}},{"rowIdx":881,"cells":{"title":{"kind":"string","value":"CLN: Assorted khash-python cleanups"},"diff":{"kind":"string","value":"diff --git a/pandas/_libs/include/pandas/vendored/klib/khash_python.h b/pandas/_libs/include/pandas/vendored/klib/khash_python.h\nindex 5a933b45d9e21..8bb3f84369b0b 100644\n--- a/pandas/_libs/include/pandas/vendored/klib/khash_python.h\n+++ b/pandas/_libs/include/pandas/vendored/klib/khash_python.h\n@@ -1,6 +1,9 @@\n // Licence at LICENSES/KLIB_LICENSE\n \n+#pragma once\n+\n #include <Python.h>\n+#include <pymem.h>\n #include <string.h>\n \n typedef struct {\n@@ -12,20 +15,8 @@ typedef struct {\n double imag;\n } khcomplex128_t;\n \n-// khash should report usage to tracemalloc\n-#if PY_VERSION_HEX >= 0x03060000\n-#include <pymem.h>\n-#if PY_VERSION_HEX < 0x03070000\n-#define PyTraceMalloc_Track _PyTraceMalloc_Track\n-#define PyTraceMalloc_Untrack _PyTraceMalloc_Untrack\n-#endif\n-#else\n-#define PyTraceMalloc_Track(...)\n-#define PyTraceMalloc_Untrack(...)\n-#endif\n-\n static const int KHASH_TRACE_DOMAIN = 424242;\n-void *traced_malloc(size_t size) {\n+static inline void *traced_malloc(size_t size) {\n void *ptr = malloc(size);\n if (ptr != NULL) {\n PyTraceMalloc_Track(KHASH_TRACE_DOMAIN, (uintptr_t)ptr, size);\n@@ -33,7 +24,7 @@ void *traced_malloc(size_t size) {\n return ptr;\n }\n \n-void *traced_calloc(size_t num, size_t size) {\n+static inline void *traced_calloc(size_t num, size_t size) {\n void *ptr = calloc(num, size);\n if (ptr != NULL) {\n PyTraceMalloc_Track(KHASH_TRACE_DOMAIN, (uintptr_t)ptr, num * size);\n@@ -41,7 +32,7 @@ void *traced_calloc(size_t num, size_t size) {\n return ptr;\n }\n \n-void *traced_realloc(void *old_ptr, size_t size) {\n+static inline void *traced_realloc(void *old_ptr, size_t size) {\n void *ptr = realloc(old_ptr, size);\n if (ptr != NULL) {\n if (old_ptr != ptr) {\n@@ -52,7 +43,7 @@ void *traced_realloc(void *old_ptr, size_t size) {\n return ptr;\n }\n \n-void traced_free(void *ptr) {\n+static inline void traced_free(void *ptr) {\n if (ptr != NULL) {\n PyTraceMalloc_Untrack(KHASH_TRACE_DOMAIN, (uintptr_t)ptr);\n }\n"},"body":{"kind":"null"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57575"},"created_at":{"kind":"string","value":"2024-02-23T02:41:25Z"},"closed_at":{"kind":"string","value":"2024-02-23T17:09:33Z"},"merged_at":{"kind":"string","value":"2024-02-23T17:09:33Z"},"updated_at":{"kind":"string","value":"2024-02-23T17:20:54Z"}}},{"rowIdx":882,"cells":{"title":{"kind":"string","value":"CLN: Clean up unnecessary templating in hashtable"},"diff":{"kind":"string","value":"diff --git a/pandas/_libs/hashtable_class_helper.pxi.in b/pandas/_libs/hashtable_class_helper.pxi.in\nindex 26dcf0b6c4ce3..c4ed8a5ec30f9 100644\n--- a/pandas/_libs/hashtable_class_helper.pxi.in\n+++ b/pandas/_libs/hashtable_class_helper.pxi.in\n@@ -82,18 +82,6 @@ cimported_types = ['complex64',\n 'uint64']\n }}\n \n-{{for name in cimported_types}}\n-from pandas._libs.khash cimport (\n- kh_destroy_{{name}},\n- kh_exist_{{name}},\n- kh_get_{{name}},\n- kh_init_{{name}},\n- kh_put_{{name}},\n- kh_resize_{{name}},\n-)\n-\n-{{endfor}}\n-\n # ----------------------------------------------------------------------\n # VectorData\n # ----------------------------------------------------------------------\n@@ -398,9 +386,9 @@ dtypes = [('Complex128', 'complex128', 'khcomplex128_t', 'to_khcomplex128_t'),\n cdef class {{name}}HashTable(HashTable):\n \n def __cinit__(self, int64_t size_hint=1, bint uses_mask=False):\n- self.table = kh_init_{{dtype}}()\n+ self.table = kh_init({{dtype}})\n size_hint = min(kh_needed_n_buckets(size_hint), SIZE_HINT_LIMIT)\n- kh_resize_{{dtype}}(self.table, size_hint)\n+ kh_resize({{dtype}}, self.table, size_hint)\n \n self.uses_mask = uses_mask\n self.na_position = -1\n@@ -410,7 +398,7 @@ cdef class {{name}}HashTable(HashTable):\n \n def __dealloc__(self):\n if self.table is not NULL:\n- kh_destroy_{{dtype}}(self.table)\n+ kh_destroy({{dtype}}, self.table)\n self.table = NULL\n \n def __contains__(self, object key) -> bool:\n@@ -424,7 +412,7 @@ cdef class {{name}}HashTable(HashTable):\n return -1 != self.na_position\n \n ckey = {{to_c_type}}(key)\n- k = kh_get_{{dtype}}(self.table, ckey)\n+ k = kh_get({{dtype}}, self.table, ckey)\n return k != self.table.n_buckets\n \n def sizeof(self, deep: bool = False) -> int:\n@@ -464,7 +452,7 @@ cdef class {{name}}HashTable(HashTable):\n {{c_type}} cval\n \n cval = {{to_c_type}}(val)\n- k = kh_get_{{dtype}}(self.table, cval)\n+ k = kh_get({{dtype}}, self.table, cval)\n if k != self.table.n_buckets:\n return self.table.vals[k]\n else:\n@@ -494,8 +482,8 @@ cdef class {{name}}HashTable(HashTable):\n {{c_type}} ckey\n \n ckey = {{to_c_type}}(key)\n- k = kh_put_{{dtype}}(self.table, ckey, &ret)\n- if kh_exist_{{dtype}}(self.table, k):\n+ k = kh_put({{dtype}}, self.table, ckey, &ret)\n+ if kh_exist({{dtype}}, self.table, k):\n self.table.vals[k] = val\n else:\n raise KeyError(key)\n@@ -528,7 +516,7 @@ cdef class {{name}}HashTable(HashTable):\n with nogil:\n for i in range(n):\n key = {{to_c_type}}(keys[i])\n- k = kh_put_{{dtype}}(self.table, key, &ret)\n+ k = kh_put({{dtype}}, self.table, key, &ret)\n self.table.vals[k] = <Py_ssize_t>values[i]\n {{endif}}\n \n@@ -552,12 +540,12 @@ cdef class {{name}}HashTable(HashTable):\n na_position = i\n else:\n val= {{to_c_type}}(values[i])\n- k = kh_put_{{dtype}}(self.table, val, &ret)\n+ k = kh_put({{dtype}}, self.table, val, &ret)\n self.table.vals[k] = i\n else:\n for i in range(n):\n val= {{to_c_type}}(values[i])\n- k = kh_put_{{dtype}}(self.table, val, &ret)\n+ k = kh_put({{dtype}}, self.table, val, &ret)\n self.table.vals[k] = i\n self.na_position = na_position\n \n@@ -582,7 +570,7 @@ cdef class {{name}}HashTable(HashTable):\n locs[i] = na_position\n else:\n val = {{to_c_type}}(values[i])\n- k = kh_get_{{dtype}}(self.table, val)\n+ k = kh_get({{dtype}}, self.table, val)\n if k != self.table.n_buckets:\n locs[i] = self.table.vals[k]\n else:\n@@ -716,11 +704,11 @@ cdef class {{name}}HashTable(HashTable):\n append_data_uint8(rmd, 1)\n continue\n \n- k = kh_get_{{dtype}}(self.table, val)\n+ k = kh_get({{dtype}}, self.table, val)\n \n if k == self.table.n_buckets:\n # k hasn't been seen yet\n- k = kh_put_{{dtype}}(self.table, val, &ret)\n+ k = kh_put({{dtype}}, self.table, val, &ret)\n \n if needs_resize(ud):\n with gil:\n@@ -857,12 +845,12 @@ cdef class {{name}}HashTable(HashTable):\n labels[i] = -1\n continue\n \n- k = kh_get_{{dtype}}(self.table, val)\n+ k = kh_get({{dtype}}, self.table, val)\n if k != self.table.n_buckets:\n idx = self.table.vals[k]\n labels[i] = idx\n else:\n- k = kh_put_{{dtype}}(self.table, val, &ret)\n+ k = kh_put({{dtype}}, self.table, val, &ret)\n self.table.vals[k] = count\n \n if needs_resize(ud):\n"},"body":{"kind":"string","value":"khash already provides a macro for these which takes the type as the first argument - no need to import function names the way we do"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57574"},"created_at":{"kind":"string","value":"2024-02-23T02:00:18Z"},"closed_at":{"kind":"string","value":"2024-02-23T02:07:15Z"},"merged_at":{"kind":"null"},"updated_at":{"kind":"string","value":"2024-02-23T02:07:16Z"}}},{"rowIdx":883,"cells":{"title":{"kind":"string","value":"Backport PR #57314 on branch 2.2.x (BUG: Fix near-minimum timestamp handling)"},"diff":{"kind":"string","value":"diff --git a/doc/source/whatsnew/v2.2.1.rst b/doc/source/whatsnew/v2.2.1.rst\nindex 35d64c99f2002..fa5304c1c3b56 100644\n--- a/doc/source/whatsnew/v2.2.1.rst\n+++ b/doc/source/whatsnew/v2.2.1.rst\n@@ -21,6 +21,7 @@ Fixed regressions\n ~~~~~~~~~~~~~~~~~\n - Fixed memory leak in :func:`read_csv` (:issue:`57039`)\n - Fixed performance regression in :meth:`Series.combine_first` (:issue:`55845`)\n+- Fixed regression causing overflow for near-minimum timestamps (:issue:`57150`)\n - Fixed regression in :func:`concat` changing long-standing behavior that always sorted the non-concatenation axis when the axis was a :class:`DatetimeIndex` (:issue:`57006`)\n - Fixed regression in :func:`merge_ordered` raising ``TypeError`` for ``fill_method=\"ffill\"`` and ``how=\"left\"`` (:issue:`57010`)\n - Fixed regression in :func:`pandas.testing.assert_series_equal` defaulting to ``check_exact=True`` when checking the :class:`Index` (:issue:`57067`)\ndiff --git a/pandas/_libs/src/vendored/numpy/datetime/np_datetime.c b/pandas/_libs/src/vendored/numpy/datetime/np_datetime.c\nindex 06e3251db8315..277d01807f2f3 100644\n--- a/pandas/_libs/src/vendored/numpy/datetime/np_datetime.c\n+++ b/pandas/_libs/src/vendored/numpy/datetime/np_datetime.c\n@@ -482,10 +482,20 @@ npy_datetime npy_datetimestruct_to_datetime(NPY_DATETIMEUNIT base,\n \n if (base == NPY_FR_ns) {\n int64_t nanoseconds;\n- PD_CHECK_OVERFLOW(\n- scaleMicrosecondsToNanoseconds(microseconds, &nanoseconds));\n- PD_CHECK_OVERFLOW(\n- checked_int64_add(nanoseconds, dts->ps / 1000, &nanoseconds));\n+\n+ // Minimum valid timestamp in nanoseconds (1677-09-21 00:12:43.145224193).\n+ const int64_t min_nanoseconds = NPY_MIN_INT64 + 1;\n+ if (microseconds == min_nanoseconds / 1000 - 1) {\n+ // For values within one microsecond of min_nanoseconds, use it as base\n+ // and offset it with nanosecond delta to avoid overflow during scaling.\n+ PD_CHECK_OVERFLOW(checked_int64_add(\n+ min_nanoseconds, (dts->ps - _NS_MIN_DTS.ps) / 1000, &nanoseconds));\n+ } else {\n+ PD_CHECK_OVERFLOW(\n+ scaleMicrosecondsToNanoseconds(microseconds, &nanoseconds));\n+ PD_CHECK_OVERFLOW(\n+ checked_int64_add(nanoseconds, dts->ps / 1000, &nanoseconds));\n+ }\n \n return nanoseconds;\n }\ndiff --git a/pandas/tests/tslibs/test_array_to_datetime.py b/pandas/tests/tslibs/test_array_to_datetime.py\nindex 632d3b4cc3c84..82175c67764f8 100644\n--- a/pandas/tests/tslibs/test_array_to_datetime.py\n+++ b/pandas/tests/tslibs/test_array_to_datetime.py\n@@ -296,6 +296,23 @@ def test_to_datetime_barely_out_of_bounds():\n tslib.array_to_datetime(arr)\n \n \n+@pytest.mark.parametrize(\n+ \"timestamp\",\n+ [\n+ # Close enough to bounds that scaling micros to nanos overflows\n+ # but adding nanos would result in an in-bounds datetime.\n+ \"1677-09-21T00:12:43.145224193\",\n+ \"1677-09-21T00:12:43.145224999\",\n+ # this always worked\n+ \"1677-09-21T00:12:43.145225000\",\n+ ],\n+)\n+def test_to_datetime_barely_inside_bounds(timestamp):\n+ # see gh-57150\n+ result, _ = tslib.array_to_datetime(np.array([timestamp], dtype=object))\n+ tm.assert_numpy_array_equal(result, np.array([timestamp], dtype=\"M8[ns]\"))\n+\n+\n class SubDatetime(datetime):\n pass\n \n"},"body":{"kind":"string","value":"Backport PR #57314: BUG: Fix near-minimum timestamp handling"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57573"},"created_at":{"kind":"string","value":"2024-02-22T23:53:48Z"},"closed_at":{"kind":"string","value":"2024-02-23T00:38:10Z"},"merged_at":{"kind":"string","value":"2024-02-23T00:38:10Z"},"updated_at":{"kind":"string","value":"2024-02-23T00:38:10Z"}}},{"rowIdx":884,"cells":{"title":{"kind":"string","value":"TST: Clean contexts"},"diff":{"kind":"string","value":"diff --git a/doc/source/development/contributing_codebase.rst b/doc/source/development/contributing_codebase.rst\nindex 62559c4232b51..39e279fd5c917 100644\n--- a/doc/source/development/contributing_codebase.rst\n+++ b/doc/source/development/contributing_codebase.rst\n@@ -596,14 +596,15 @@ with the specific exception subclass (i.e. never use :py:class:`Exception`) and\n Testing involving files\n ^^^^^^^^^^^^^^^^^^^^^^^\n \n-The ``tm.ensure_clean`` context manager creates a temporary file for testing,\n-with a generated filename (or your filename if provided), that is automatically\n-deleted when the context block is exited.\n+The ``temp_file`` pytest fixture creates a temporary file :py:class:`Pathlib` object for testing:\n \n .. code-block:: python\n \n- with tm.ensure_clean('my_file_path') as path:\n- # do something with the path\n+ def test_something(temp_file):\n+ pd.DataFrame([1]).to_csv(str(temp_file))\n+\n+Please reference `pytest's documentation <https://docs.pytest.org/en/latest/how-to/tmp_path.html#the-default-base-temporary-directory>`_\n+for the file retension policy.\n \n Testing involving network connectivity\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\ndiff --git a/pandas/_testing/__init__.py b/pandas/_testing/__init__.py\nindex 5409c9b1fc0b9..ddd8d07c5f2eb 100644\n--- a/pandas/_testing/__init__.py\n+++ b/pandas/_testing/__init__.py\n@@ -76,7 +76,6 @@\n ensure_clean,\n raises_chained_assignment_error,\n set_timezone,\n- use_numexpr,\n with_csv_dialect,\n )\n from pandas.core.arrays import (\n@@ -628,7 +627,6 @@ def shares_memory(left, right) -> bool:\n \"to_array\",\n \"UNSIGNED_INT_EA_DTYPES\",\n \"UNSIGNED_INT_NUMPY_DTYPES\",\n- \"use_numexpr\",\n \"with_csv_dialect\",\n \"write_to_compressed\",\n ]\ndiff --git a/pandas/_testing/contexts.py b/pandas/_testing/contexts.py\nindex a04322cf97798..b986e03e25815 100644\n--- a/pandas/_testing/contexts.py\n+++ b/pandas/_testing/contexts.py\n@@ -16,8 +16,6 @@\n from pandas.compat import PYPY\n from pandas.errors import ChainedAssignmentError\n \n-from pandas import set_option\n-\n from pandas.io.common import get_handle\n \n if TYPE_CHECKING:\n@@ -95,9 +93,7 @@ def setTZ(tz) -> None:\n \n \n @contextmanager\n-def ensure_clean(\n- filename=None, return_filelike: bool = False, **kwargs: Any\n-) -> Generator[Any, None, None]:\n+def ensure_clean(filename=None) -> Generator[Any, None, None]:\n \"\"\"\n Gets a temporary path and agrees to remove on close.\n \n@@ -109,12 +105,6 @@ def ensure_clean(\n ----------\n filename : str (optional)\n suffix of the created file.\n- return_filelike : bool (default False)\n- if True, returns a file-like which is *always* cleaned. Necessary for\n- savefig and other functions which want to append extensions.\n- **kwargs\n- Additional keywords are passed to open().\n-\n \"\"\"\n folder = Path(tempfile.gettempdir())\n \n@@ -125,19 +115,11 @@ def ensure_clean(\n \n path.touch()\n \n- handle_or_str: str | IO = str(path)\n- encoding = kwargs.pop(\"encoding\", None)\n- if return_filelike:\n- kwargs.setdefault(\"mode\", \"w+b\")\n- if encoding is None and \"b\" not in kwargs[\"mode\"]:\n- encoding = \"utf-8\"\n- handle_or_str = open(path, encoding=encoding, **kwargs)\n+ handle_or_str = str(path)\n \n try:\n yield handle_or_str\n finally:\n- if not isinstance(handle_or_str, str):\n- handle_or_str.close()\n if path.is_file():\n path.unlink()\n \n@@ -176,24 +158,6 @@ def with_csv_dialect(name: str, **kwargs) -> Generator[None, None, None]:\n csv.unregister_dialect(name)\n \n \n-@contextmanager\n-def use_numexpr(use, min_elements=None) -> Generator[None, None, None]:\n- from pandas.core.computation import expressions as expr\n-\n- if min_elements is None:\n- min_elements = expr._MIN_ELEMENTS\n-\n- olduse = expr.USE_NUMEXPR\n- oldmin = expr._MIN_ELEMENTS\n- set_option(\"compute.use_numexpr\", use)\n- expr._MIN_ELEMENTS = min_elements\n- try:\n- yield\n- finally:\n- expr._MIN_ELEMENTS = oldmin\n- set_option(\"compute.use_numexpr\", olduse)\n-\n-\n def raises_chained_assignment_error(warn=True, extra_warnings=(), extra_match=()):\n from pandas._testing import assert_produces_warning\n \ndiff --git a/pandas/conftest.py b/pandas/conftest.py\nindex 8cba5b96ea9af..64a13164ff551 100644\n--- a/pandas/conftest.py\n+++ b/pandas/conftest.py\n@@ -35,6 +35,7 @@\n TYPE_CHECKING,\n Callable,\n )\n+import uuid\n \n from dateutil.tz import (\n tzlocal,\n@@ -2010,3 +2011,14 @@ def arrow_string_storage():\n Fixture that lists possible PyArrow values for StringDtype storage field.\n \"\"\"\n return (\"pyarrow\", \"pyarrow_numpy\")\n+\n+\n+@pytest.fixture\n+def temp_file(tmp_path):\n+ \"\"\"\n+ Generate a unique file for testing use. See link for removal policy.\n+ https://docs.pytest.org/en/7.1.x/how-to/tmp_path.html#the-default-base-temporary-directory\n+ \"\"\"\n+ file_path = tmp_path / str(uuid.uuid4())\n+ file_path.touch()\n+ return file_path\ndiff --git a/pandas/tests/frame/methods/test_to_csv.py b/pandas/tests/frame/methods/test_to_csv.py\nindex 250567eafc670..5b9ced8d47ed7 100644\n--- a/pandas/tests/frame/methods/test_to_csv.py\n+++ b/pandas/tests/frame/methods/test_to_csv.py\n@@ -33,125 +33,125 @@ def read_csv(self, path, **kwargs):\n \n return read_csv(path, **params)\n \n- def test_to_csv_from_csv1(self, float_frame, datetime_frame):\n- with tm.ensure_clean(\"__tmp_to_csv_from_csv1__\") as path:\n- float_frame.iloc[:5, float_frame.columns.get_loc(\"A\")] = np.nan\n-\n- float_frame.to_csv(path)\n- float_frame.to_csv(path, columns=[\"A\", \"B\"])\n- float_frame.to_csv(path, header=False)\n- float_frame.to_csv(path, index=False)\n-\n- # test roundtrip\n- # freq does not roundtrip\n- datetime_frame.index = datetime_frame.index._with_freq(None)\n- datetime_frame.to_csv(path)\n- recons = self.read_csv(path, parse_dates=True)\n- tm.assert_frame_equal(datetime_frame, recons)\n-\n- datetime_frame.to_csv(path, index_label=\"index\")\n- recons = self.read_csv(path, index_col=None, parse_dates=True)\n-\n- assert len(recons.columns) == len(datetime_frame.columns) + 1\n-\n- # no index\n- datetime_frame.to_csv(path, index=False)\n- recons = self.read_csv(path, index_col=None, parse_dates=True)\n- tm.assert_almost_equal(datetime_frame.values, recons.values)\n-\n- # corner case\n- dm = DataFrame(\n- {\n- \"s1\": Series(range(3), index=np.arange(3, dtype=np.int64)),\n- \"s2\": Series(range(2), index=np.arange(2, dtype=np.int64)),\n- }\n- )\n- dm.to_csv(path)\n+ def test_to_csv_from_csv1(self, temp_file, float_frame, datetime_frame):\n+ path = str(temp_file)\n+ float_frame.iloc[:5, float_frame.columns.get_loc(\"A\")] = np.nan\n+\n+ float_frame.to_csv(path)\n+ float_frame.to_csv(path, columns=[\"A\", \"B\"])\n+ float_frame.to_csv(path, header=False)\n+ float_frame.to_csv(path, index=False)\n+\n+ # test roundtrip\n+ # freq does not roundtrip\n+ datetime_frame.index = datetime_frame.index._with_freq(None)\n+ datetime_frame.to_csv(path)\n+ recons = self.read_csv(path, parse_dates=True)\n+ tm.assert_frame_equal(datetime_frame, recons)\n+\n+ datetime_frame.to_csv(path, index_label=\"index\")\n+ recons = self.read_csv(path, index_col=None, parse_dates=True)\n+\n+ assert len(recons.columns) == len(datetime_frame.columns) + 1\n+\n+ # no index\n+ datetime_frame.to_csv(path, index=False)\n+ recons = self.read_csv(path, index_col=None, parse_dates=True)\n+ tm.assert_almost_equal(datetime_frame.values, recons.values)\n+\n+ # corner case\n+ dm = DataFrame(\n+ {\n+ \"s1\": Series(range(3), index=np.arange(3, dtype=np.int64)),\n+ \"s2\": Series(range(2), index=np.arange(2, dtype=np.int64)),\n+ }\n+ )\n+ dm.to_csv(path)\n \n- recons = self.read_csv(path)\n- tm.assert_frame_equal(dm, recons)\n+ recons = self.read_csv(path)\n+ tm.assert_frame_equal(dm, recons)\n \n- def test_to_csv_from_csv2(self, float_frame):\n- with tm.ensure_clean(\"__tmp_to_csv_from_csv2__\") as path:\n- # duplicate index\n- df = DataFrame(\n- np.random.default_rng(2).standard_normal((3, 3)),\n- index=[\"a\", \"a\", \"b\"],\n- columns=[\"x\", \"y\", \"z\"],\n- )\n- df.to_csv(path)\n- result = self.read_csv(path)\n- tm.assert_frame_equal(result, df)\n+ def test_to_csv_from_csv2(self, temp_file, float_frame):\n+ path = str(temp_file)\n+ # duplicate index\n+ df = DataFrame(\n+ np.random.default_rng(2).standard_normal((3, 3)),\n+ index=[\"a\", \"a\", \"b\"],\n+ columns=[\"x\", \"y\", \"z\"],\n+ )\n+ df.to_csv(path)\n+ result = self.read_csv(path)\n+ tm.assert_frame_equal(result, df)\n \n- midx = MultiIndex.from_tuples([(\"A\", 1, 2), (\"A\", 1, 2), (\"B\", 1, 2)])\n- df = DataFrame(\n- np.random.default_rng(2).standard_normal((3, 3)),\n- index=midx,\n- columns=[\"x\", \"y\", \"z\"],\n- )\n+ midx = MultiIndex.from_tuples([(\"A\", 1, 2), (\"A\", 1, 2), (\"B\", 1, 2)])\n+ df = DataFrame(\n+ np.random.default_rng(2).standard_normal((3, 3)),\n+ index=midx,\n+ columns=[\"x\", \"y\", \"z\"],\n+ )\n \n- df.to_csv(path)\n- result = self.read_csv(path, index_col=[0, 1, 2], parse_dates=False)\n- tm.assert_frame_equal(result, df, check_names=False)\n-\n- # column aliases\n- col_aliases = Index([\"AA\", \"X\", \"Y\", \"Z\"])\n- float_frame.to_csv(path, header=col_aliases)\n-\n- rs = self.read_csv(path)\n- xp = float_frame.copy()\n- xp.columns = col_aliases\n- tm.assert_frame_equal(xp, rs)\n-\n- msg = \"Writing 4 cols but got 2 aliases\"\n- with pytest.raises(ValueError, match=msg):\n- float_frame.to_csv(path, header=[\"AA\", \"X\"])\n-\n- def test_to_csv_from_csv3(self):\n- with tm.ensure_clean(\"__tmp_to_csv_from_csv3__\") as path:\n- df1 = DataFrame(np.random.default_rng(2).standard_normal((3, 1)))\n- df2 = DataFrame(np.random.default_rng(2).standard_normal((3, 1)))\n-\n- df1.to_csv(path)\n- df2.to_csv(path, mode=\"a\", header=False)\n- xp = pd.concat([df1, df2])\n- rs = read_csv(path, index_col=0)\n- rs.columns = [int(label) for label in rs.columns]\n- xp.columns = [int(label) for label in xp.columns]\n- tm.assert_frame_equal(xp, rs)\n-\n- def test_to_csv_from_csv4(self):\n- with tm.ensure_clean(\"__tmp_to_csv_from_csv4__\") as path:\n- # GH 10833 (TimedeltaIndex formatting)\n- dt = pd.Timedelta(seconds=1)\n- df = DataFrame(\n- {\"dt_data\": [i * dt for i in range(3)]},\n- index=Index([i * dt for i in range(3)], name=\"dt_index\"),\n- )\n- df.to_csv(path)\n+ df.to_csv(path)\n+ result = self.read_csv(path, index_col=[0, 1, 2], parse_dates=False)\n+ tm.assert_frame_equal(result, df, check_names=False)\n+\n+ # column aliases\n+ col_aliases = Index([\"AA\", \"X\", \"Y\", \"Z\"])\n+ float_frame.to_csv(path, header=col_aliases)\n+\n+ rs = self.read_csv(path)\n+ xp = float_frame.copy()\n+ xp.columns = col_aliases\n+ tm.assert_frame_equal(xp, rs)\n+\n+ msg = \"Writing 4 cols but got 2 aliases\"\n+ with pytest.raises(ValueError, match=msg):\n+ float_frame.to_csv(path, header=[\"AA\", \"X\"])\n+\n+ def test_to_csv_from_csv3(self, temp_file):\n+ path = str(temp_file)\n+ df1 = DataFrame(np.random.default_rng(2).standard_normal((3, 1)))\n+ df2 = DataFrame(np.random.default_rng(2).standard_normal((3, 1)))\n+\n+ df1.to_csv(path)\n+ df2.to_csv(path, mode=\"a\", header=False)\n+ xp = pd.concat([df1, df2])\n+ rs = read_csv(path, index_col=0)\n+ rs.columns = [int(label) for label in rs.columns]\n+ xp.columns = [int(label) for label in xp.columns]\n+ tm.assert_frame_equal(xp, rs)\n+\n+ def test_to_csv_from_csv4(self, temp_file):\n+ path = str(temp_file)\n+ # GH 10833 (TimedeltaIndex formatting)\n+ dt = pd.Timedelta(seconds=1)\n+ df = DataFrame(\n+ {\"dt_data\": [i * dt for i in range(3)]},\n+ index=Index([i * dt for i in range(3)], name=\"dt_index\"),\n+ )\n+ df.to_csv(path)\n \n- result = read_csv(path, index_col=\"dt_index\")\n- result.index = pd.to_timedelta(result.index)\n- result[\"dt_data\"] = pd.to_timedelta(result[\"dt_data\"])\n+ result = read_csv(path, index_col=\"dt_index\")\n+ result.index = pd.to_timedelta(result.index)\n+ result[\"dt_data\"] = pd.to_timedelta(result[\"dt_data\"])\n \n- tm.assert_frame_equal(df, result, check_index_type=True)\n+ tm.assert_frame_equal(df, result, check_index_type=True)\n \n- def test_to_csv_from_csv5(self, timezone_frame):\n+ def test_to_csv_from_csv5(self, temp_file, timezone_frame):\n # tz, 8260\n- with tm.ensure_clean(\"__tmp_to_csv_from_csv5__\") as path:\n- timezone_frame.to_csv(path)\n- result = read_csv(path, index_col=0, parse_dates=[\"A\"])\n-\n- converter = (\n- lambda c: to_datetime(result[c])\n- .dt.tz_convert(\"UTC\")\n- .dt.tz_convert(timezone_frame[c].dt.tz)\n- )\n- result[\"B\"] = converter(\"B\")\n- result[\"C\"] = converter(\"C\")\n- tm.assert_frame_equal(result, timezone_frame)\n+ path = str(temp_file)\n+ timezone_frame.to_csv(path)\n+ result = read_csv(path, index_col=0, parse_dates=[\"A\"])\n+\n+ converter = (\n+ lambda c: to_datetime(result[c])\n+ .dt.tz_convert(\"UTC\")\n+ .dt.tz_convert(timezone_frame[c].dt.tz)\n+ )\n+ result[\"B\"] = converter(\"B\")\n+ result[\"C\"] = converter(\"C\")\n+ tm.assert_frame_equal(result, timezone_frame)\n \n- def test_to_csv_cols_reordering(self):\n+ def test_to_csv_cols_reordering(self, temp_file):\n # GH3454\n chunksize = 5\n N = int(chunksize * 2.5)\n@@ -164,14 +164,14 @@ def test_to_csv_cols_reordering(self):\n cs = df.columns\n cols = [cs[2], cs[0]]\n \n- with tm.ensure_clean() as path:\n- df.to_csv(path, columns=cols, chunksize=chunksize)\n- rs_c = read_csv(path, index_col=0)\n+ path = str(temp_file)\n+ df.to_csv(path, columns=cols, chunksize=chunksize)\n+ rs_c = read_csv(path, index_col=0)\n \n tm.assert_frame_equal(df[cols], rs_c, check_names=False)\n \n @pytest.mark.parametrize(\"cols\", [None, [\"b\", \"a\"]])\n- def test_to_csv_new_dupe_cols(self, cols):\n+ def test_to_csv_new_dupe_cols(self, temp_file, cols):\n chunksize = 5\n N = int(chunksize * 2.5)\n \n@@ -181,34 +181,34 @@ def test_to_csv_new_dupe_cols(self, cols):\n index=Index([f\"i-{i}\" for i in range(N)], name=\"a\"),\n columns=[\"a\", \"a\", \"b\"],\n )\n- with tm.ensure_clean() as path:\n- df.to_csv(path, columns=cols, chunksize=chunksize)\n- rs_c = read_csv(path, index_col=0)\n-\n- # we wrote them in a different order\n- # so compare them in that order\n- if cols is not None:\n- if df.columns.is_unique:\n- rs_c.columns = cols\n- else:\n- indexer, missing = df.columns.get_indexer_non_unique(cols)\n- rs_c.columns = df.columns.take(indexer)\n-\n- for c in cols:\n- obj_df = df[c]\n- obj_rs = rs_c[c]\n- if isinstance(obj_df, Series):\n- tm.assert_series_equal(obj_df, obj_rs)\n- else:\n- tm.assert_frame_equal(obj_df, obj_rs, check_names=False)\n-\n- # wrote in the same order\n+ path = str(temp_file)\n+ df.to_csv(path, columns=cols, chunksize=chunksize)\n+ rs_c = read_csv(path, index_col=0)\n+\n+ # we wrote them in a different order\n+ # so compare them in that order\n+ if cols is not None:\n+ if df.columns.is_unique:\n+ rs_c.columns = cols\n else:\n- rs_c.columns = df.columns\n- tm.assert_frame_equal(df, rs_c, check_names=False)\n+ indexer, missing = df.columns.get_indexer_non_unique(cols)\n+ rs_c.columns = df.columns.take(indexer)\n+\n+ for c in cols:\n+ obj_df = df[c]\n+ obj_rs = rs_c[c]\n+ if isinstance(obj_df, Series):\n+ tm.assert_series_equal(obj_df, obj_rs)\n+ else:\n+ tm.assert_frame_equal(obj_df, obj_rs, check_names=False)\n+\n+ # wrote in the same order\n+ else:\n+ rs_c.columns = df.columns\n+ tm.assert_frame_equal(df, rs_c, check_names=False)\n \n @pytest.mark.slow\n- def test_to_csv_dtnat(self):\n+ def test_to_csv_dtnat(self, temp_file):\n # GH3437\n def make_dtnat_arr(n, nnat=None):\n if nnat is None:\n@@ -226,12 +226,12 @@ def make_dtnat_arr(n, nnat=None):\n s1 = make_dtnat_arr(chunksize + 5)\n s2 = make_dtnat_arr(chunksize + 5, 0)\n \n- with tm.ensure_clean(\"1.csv\") as pth:\n- df = DataFrame({\"a\": s1, \"b\": s2})\n- df.to_csv(pth, chunksize=chunksize)\n+ path = str(temp_file)\n+ df = DataFrame({\"a\": s1, \"b\": s2})\n+ df.to_csv(path, chunksize=chunksize)\n \n- recons = self.read_csv(pth).apply(to_datetime)\n- tm.assert_frame_equal(df, recons, check_names=False)\n+ recons = self.read_csv(path).apply(to_datetime)\n+ tm.assert_frame_equal(df, recons, check_names=False)\n \n def _return_result_expected(\n self,\n@@ -465,42 +465,42 @@ def test_to_csv_params(self, nrows, df_params, func_params, ncols):\n result, expected = self._return_result_expected(df, 1000, **func_params)\n tm.assert_frame_equal(result, expected, check_names=False)\n \n- def test_to_csv_from_csv_w_some_infs(self, float_frame):\n+ def test_to_csv_from_csv_w_some_infs(self, temp_file, float_frame):\n # test roundtrip with inf, -inf, nan, as full columns and mix\n float_frame[\"G\"] = np.nan\n f = lambda x: [np.inf, np.nan][np.random.default_rng(2).random() < 0.5]\n float_frame[\"h\"] = float_frame.index.map(f)\n \n- with tm.ensure_clean() as path:\n- float_frame.to_csv(path)\n- recons = self.read_csv(path)\n+ path = str(temp_file)\n+ float_frame.to_csv(path)\n+ recons = self.read_csv(path)\n \n- tm.assert_frame_equal(float_frame, recons)\n- tm.assert_frame_equal(np.isinf(float_frame), np.isinf(recons))\n+ tm.assert_frame_equal(float_frame, recons)\n+ tm.assert_frame_equal(np.isinf(float_frame), np.isinf(recons))\n \n- def test_to_csv_from_csv_w_all_infs(self, float_frame):\n+ def test_to_csv_from_csv_w_all_infs(self, temp_file, float_frame):\n # test roundtrip with inf, -inf, nan, as full columns and mix\n float_frame[\"E\"] = np.inf\n float_frame[\"F\"] = -np.inf\n \n- with tm.ensure_clean() as path:\n- float_frame.to_csv(path)\n- recons = self.read_csv(path)\n+ path = str(temp_file)\n+ float_frame.to_csv(path)\n+ recons = self.read_csv(path)\n \n- tm.assert_frame_equal(float_frame, recons)\n- tm.assert_frame_equal(np.isinf(float_frame), np.isinf(recons))\n+ tm.assert_frame_equal(float_frame, recons)\n+ tm.assert_frame_equal(np.isinf(float_frame), np.isinf(recons))\n \n- def test_to_csv_no_index(self):\n+ def test_to_csv_no_index(self, temp_file):\n # GH 3624, after appending columns, to_csv fails\n- with tm.ensure_clean(\"__tmp_to_csv_no_index__\") as path:\n- df = DataFrame({\"c1\": [1, 2, 3], \"c2\": [4, 5, 6]})\n- df.to_csv(path, index=False)\n- result = read_csv(path)\n- tm.assert_frame_equal(df, result)\n- df[\"c3\"] = Series([7, 8, 9], dtype=\"int64\")\n- df.to_csv(path, index=False)\n- result = read_csv(path)\n- tm.assert_frame_equal(df, result)\n+ path = str(temp_file)\n+ df = DataFrame({\"c1\": [1, 2, 3], \"c2\": [4, 5, 6]})\n+ df.to_csv(path, index=False)\n+ result = read_csv(path)\n+ tm.assert_frame_equal(df, result)\n+ df[\"c3\"] = Series([7, 8, 9], dtype=\"int64\")\n+ df.to_csv(path, index=False)\n+ result = read_csv(path)\n+ tm.assert_frame_equal(df, result)\n \n def test_to_csv_with_mix_columns(self):\n # gh-11637: incorrect output when a mix of integer and string column\n@@ -510,74 +510,72 @@ def test_to_csv_with_mix_columns(self):\n df[\"test\"] = \"txt\"\n assert df.to_csv() == df.to_csv(columns=[0, 1, \"test\"])\n \n- def test_to_csv_headers(self):\n+ def test_to_csv_headers(self, temp_file):\n # GH6186, the presence or absence of `index` incorrectly\n # causes to_csv to have different header semantics.\n from_df = DataFrame([[1, 2], [3, 4]], columns=[\"A\", \"B\"])\n to_df = DataFrame([[1, 2], [3, 4]], columns=[\"X\", \"Y\"])\n- with tm.ensure_clean(\"__tmp_to_csv_headers__\") as path:\n- from_df.to_csv(path, header=[\"X\", \"Y\"])\n- recons = self.read_csv(path)\n+ path = str(temp_file)\n+ from_df.to_csv(path, header=[\"X\", \"Y\"])\n+ recons = self.read_csv(path)\n \n- tm.assert_frame_equal(to_df, recons)\n+ tm.assert_frame_equal(to_df, recons)\n \n- from_df.to_csv(path, index=False, header=[\"X\", \"Y\"])\n- recons = self.read_csv(path)\n+ from_df.to_csv(path, index=False, header=[\"X\", \"Y\"])\n+ recons = self.read_csv(path)\n \n- return_value = recons.reset_index(inplace=True)\n- assert return_value is None\n- tm.assert_frame_equal(to_df, recons)\n+ return_value = recons.reset_index(inplace=True)\n+ assert return_value is None\n+ tm.assert_frame_equal(to_df, recons)\n \n- def test_to_csv_multiindex(self, float_frame, datetime_frame):\n+ def test_to_csv_multiindex(self, temp_file, float_frame, datetime_frame):\n frame = float_frame\n old_index = frame.index\n arrays = np.arange(len(old_index) * 2, dtype=np.int64).reshape(2, -1)\n new_index = MultiIndex.from_arrays(arrays, names=[\"first\", \"second\"])\n frame.index = new_index\n \n- with tm.ensure_clean(\"__tmp_to_csv_multiindex__\") as path:\n- frame.to_csv(path, header=False)\n- frame.to_csv(path, columns=[\"A\", \"B\"])\n+ path = str(temp_file)\n+ frame.to_csv(path, header=False)\n+ frame.to_csv(path, columns=[\"A\", \"B\"])\n \n- # round trip\n- frame.to_csv(path)\n+ # round trip\n+ frame.to_csv(path)\n \n- df = self.read_csv(path, index_col=[0, 1], parse_dates=False)\n+ df = self.read_csv(path, index_col=[0, 1], parse_dates=False)\n \n- # TODO to_csv drops column name\n- tm.assert_frame_equal(frame, df, check_names=False)\n- assert frame.index.names == df.index.names\n+ # TODO to_csv drops column name\n+ tm.assert_frame_equal(frame, df, check_names=False)\n+ assert frame.index.names == df.index.names\n \n- # needed if setUp becomes a class method\n- float_frame.index = old_index\n+ # needed if setUp becomes a class method\n+ float_frame.index = old_index\n \n- # try multiindex with dates\n- tsframe = datetime_frame\n- old_index = tsframe.index\n- new_index = [old_index, np.arange(len(old_index), dtype=np.int64)]\n- tsframe.index = MultiIndex.from_arrays(new_index)\n+ # try multiindex with dates\n+ tsframe = datetime_frame\n+ old_index = tsframe.index\n+ new_index = [old_index, np.arange(len(old_index), dtype=np.int64)]\n+ tsframe.index = MultiIndex.from_arrays(new_index)\n \n- tsframe.to_csv(path, index_label=[\"time\", \"foo\"])\n- with tm.assert_produces_warning(\n- UserWarning, match=\"Could not infer format\"\n- ):\n- recons = self.read_csv(path, index_col=[0, 1], parse_dates=True)\n+ tsframe.to_csv(path, index_label=[\"time\", \"foo\"])\n+ with tm.assert_produces_warning(UserWarning, match=\"Could not infer format\"):\n+ recons = self.read_csv(path, index_col=[0, 1], parse_dates=True)\n \n- # TODO to_csv drops column name\n- tm.assert_frame_equal(tsframe, recons, check_names=False)\n+ # TODO to_csv drops column name\n+ tm.assert_frame_equal(tsframe, recons, check_names=False)\n \n- # do not load index\n- tsframe.to_csv(path)\n- recons = self.read_csv(path, index_col=None)\n- assert len(recons.columns) == len(tsframe.columns) + 2\n+ # do not load index\n+ tsframe.to_csv(path)\n+ recons = self.read_csv(path, index_col=None)\n+ assert len(recons.columns) == len(tsframe.columns) + 2\n \n- # no index\n- tsframe.to_csv(path, index=False)\n- recons = self.read_csv(path, index_col=None)\n- tm.assert_almost_equal(recons.values, datetime_frame.values)\n+ # no index\n+ tsframe.to_csv(path, index=False)\n+ recons = self.read_csv(path, index_col=None)\n+ tm.assert_almost_equal(recons.values, datetime_frame.values)\n \n- # needed if setUp becomes class method\n- datetime_frame.index = old_index\n+ # needed if setUp becomes class method\n+ datetime_frame.index = old_index\n \n with tm.ensure_clean(\"__tmp_to_csv_multiindex__\") as path:\n # GH3571, GH1651, GH3141\n@@ -682,46 +680,46 @@ def _make_frame(names=None):\n tm.assert_index_equal(recons.columns, exp.columns)\n assert len(recons) == 0\n \n- def test_to_csv_interval_index(self, using_infer_string):\n+ def test_to_csv_interval_index(self, temp_file, using_infer_string):\n # GH 28210\n df = DataFrame({\"A\": list(\"abc\"), \"B\": range(3)}, index=pd.interval_range(0, 3))\n \n- with tm.ensure_clean(\"__tmp_to_csv_interval_index__.csv\") as path:\n- df.to_csv(path)\n- result = self.read_csv(path, index_col=0)\n+ path = str(temp_file)\n+ df.to_csv(path)\n+ result = self.read_csv(path, index_col=0)\n \n- # can't roundtrip intervalindex via read_csv so check string repr (GH 23595)\n- expected = df.copy()\n- if using_infer_string:\n- expected.index = expected.index.astype(\"string[pyarrow_numpy]\")\n- else:\n- expected.index = expected.index.astype(str)\n+ # can't roundtrip intervalindex via read_csv so check string repr (GH 23595)\n+ expected = df.copy()\n+ if using_infer_string:\n+ expected.index = expected.index.astype(\"string[pyarrow_numpy]\")\n+ else:\n+ expected.index = expected.index.astype(str)\n \n- tm.assert_frame_equal(result, expected)\n+ tm.assert_frame_equal(result, expected)\n \n- def test_to_csv_float32_nanrep(self):\n+ def test_to_csv_float32_nanrep(self, temp_file):\n df = DataFrame(\n np.random.default_rng(2).standard_normal((1, 4)).astype(np.float32)\n )\n df[1] = np.nan\n \n- with tm.ensure_clean(\"__tmp_to_csv_float32_nanrep__.csv\") as path:\n- df.to_csv(path, na_rep=999)\n+ path = str(temp_file)\n+ df.to_csv(path, na_rep=999)\n \n- with open(path, encoding=\"utf-8\") as f:\n- lines = f.readlines()\n- assert lines[1].split(\",\")[2] == \"999\"\n+ with open(path, encoding=\"utf-8\") as f:\n+ lines = f.readlines()\n+ assert lines[1].split(\",\")[2] == \"999\"\n \n- def test_to_csv_withcommas(self):\n+ def test_to_csv_withcommas(self, temp_file):\n # Commas inside fields should be correctly escaped when saving as CSV.\n df = DataFrame({\"A\": [1, 2, 3], \"B\": [\"5,6\", \"7,8\", \"9,0\"]})\n \n- with tm.ensure_clean(\"__tmp_to_csv_withcommas__.csv\") as path:\n- df.to_csv(path)\n- df2 = self.read_csv(path)\n- tm.assert_frame_equal(df2, df)\n+ path = str(temp_file)\n+ df.to_csv(path)\n+ df2 = self.read_csv(path)\n+ tm.assert_frame_equal(df2, df)\n \n- def test_to_csv_mixed(self):\n+ def test_to_csv_mixed(self, temp_file):\n def create_cols(name):\n return [f\"{name}{i:03d}\" for i in range(5)]\n \n@@ -762,25 +760,23 @@ def create_cols(name):\n for c in create_cols(n):\n dtypes[c] = dtype\n \n- with tm.ensure_clean() as filename:\n- df.to_csv(filename)\n- rs = read_csv(\n- filename, index_col=0, dtype=dtypes, parse_dates=create_cols(\"date\")\n- )\n- tm.assert_frame_equal(rs, df)\n+ path = str(temp_file)\n+ df.to_csv(path)\n+ rs = read_csv(path, index_col=0, dtype=dtypes, parse_dates=create_cols(\"date\"))\n+ tm.assert_frame_equal(rs, df)\n \n- def test_to_csv_dups_cols(self):\n+ def test_to_csv_dups_cols(self, temp_file):\n df = DataFrame(\n np.random.default_rng(2).standard_normal((1000, 30)),\n columns=list(range(15)) + list(range(15)),\n dtype=\"float64\",\n )\n \n- with tm.ensure_clean() as filename:\n- df.to_csv(filename) # single dtype, fine\n- result = read_csv(filename, index_col=0)\n- result.columns = df.columns\n- tm.assert_frame_equal(result, df)\n+ path = str(temp_file)\n+ df.to_csv(path) # single dtype, fine\n+ result = read_csv(path, index_col=0)\n+ result.columns = df.columns\n+ tm.assert_frame_equal(result, df)\n \n df_float = DataFrame(\n np.random.default_rng(2).standard_normal((1000, 3)), dtype=\"float64\"\n@@ -810,7 +806,7 @@ def test_to_csv_dups_cols(self):\n result.columns = df.columns\n tm.assert_frame_equal(result, df)\n \n- def test_to_csv_dups_cols2(self):\n+ def test_to_csv_dups_cols2(self, temp_file):\n # GH3457\n df = DataFrame(\n np.ones((5, 3)),\n@@ -818,28 +814,28 @@ def test_to_csv_dups_cols2(self):\n columns=Index([\"a\", \"a\", \"b\"], dtype=object),\n )\n \n- with tm.ensure_clean() as filename:\n- df.to_csv(filename)\n+ path = str(temp_file)\n+ df.to_csv(path)\n \n- # read_csv will rename the dups columns\n- result = read_csv(filename, index_col=0)\n- result = result.rename(columns={\"a.1\": \"a\"})\n- tm.assert_frame_equal(result, df)\n+ # read_csv will rename the dups columns\n+ result = read_csv(path, index_col=0)\n+ result = result.rename(columns={\"a.1\": \"a\"})\n+ tm.assert_frame_equal(result, df)\n \n @pytest.mark.parametrize(\"chunksize\", [10000, 50000, 100000])\n- def test_to_csv_chunking(self, chunksize):\n+ def test_to_csv_chunking(self, chunksize, temp_file):\n aa = DataFrame({\"A\": range(100000)})\n aa[\"B\"] = aa.A + 1.0\n aa[\"C\"] = aa.A + 2.0\n aa[\"D\"] = aa.A + 3.0\n \n- with tm.ensure_clean() as filename:\n- aa.to_csv(filename, chunksize=chunksize)\n- rs = read_csv(filename, index_col=0)\n- tm.assert_frame_equal(rs, aa)\n+ path = str(temp_file)\n+ aa.to_csv(path, chunksize=chunksize)\n+ rs = read_csv(path, index_col=0)\n+ tm.assert_frame_equal(rs, aa)\n \n @pytest.mark.slow\n- def test_to_csv_wide_frame_formatting(self, monkeypatch):\n+ def test_to_csv_wide_frame_formatting(self, temp_file, monkeypatch):\n # Issue #8621\n chunksize = 100\n df = DataFrame(\n@@ -847,35 +843,35 @@ def test_to_csv_wide_frame_formatting(self, monkeypatch):\n columns=None,\n index=None,\n )\n- with tm.ensure_clean() as filename:\n- with monkeypatch.context() as m:\n- m.setattr(\"pandas.io.formats.csvs._DEFAULT_CHUNKSIZE_CELLS\", chunksize)\n- df.to_csv(filename, header=False, index=False)\n- rs = read_csv(filename, header=None)\n+ path = str(temp_file)\n+ with monkeypatch.context() as m:\n+ m.setattr(\"pandas.io.formats.csvs._DEFAULT_CHUNKSIZE_CELLS\", chunksize)\n+ df.to_csv(path, header=False, index=False)\n+ rs = read_csv(path, header=None)\n tm.assert_frame_equal(rs, df)\n \n- def test_to_csv_bug(self):\n+ def test_to_csv_bug(self, temp_file):\n f1 = StringIO(\"a,1.0\\nb,2.0\")\n df = self.read_csv(f1, header=None)\n newdf = DataFrame({\"t\": df[df.columns[0]]})\n \n- with tm.ensure_clean() as path:\n- newdf.to_csv(path)\n+ path = str(temp_file)\n+ newdf.to_csv(path)\n \n- recons = read_csv(path, index_col=0)\n- # don't check_names as t != 1\n- tm.assert_frame_equal(recons, newdf, check_names=False)\n+ recons = read_csv(path, index_col=0)\n+ # don't check_names as t != 1\n+ tm.assert_frame_equal(recons, newdf, check_names=False)\n \n- def test_to_csv_unicode(self):\n+ def test_to_csv_unicode(self, temp_file):\n df = DataFrame({\"c/\\u03c3\": [1, 2, 3]})\n- with tm.ensure_clean() as path:\n- df.to_csv(path, encoding=\"UTF-8\")\n- df2 = read_csv(path, index_col=0, encoding=\"UTF-8\")\n- tm.assert_frame_equal(df, df2)\n+ path = str(temp_file)\n+ df.to_csv(path, encoding=\"UTF-8\")\n+ df2 = read_csv(path, index_col=0, encoding=\"UTF-8\")\n+ tm.assert_frame_equal(df, df2)\n \n- df.to_csv(path, encoding=\"UTF-8\", index=False)\n- df2 = read_csv(path, index_col=None, encoding=\"UTF-8\")\n- tm.assert_frame_equal(df, df2)\n+ df.to_csv(path, encoding=\"UTF-8\", index=False)\n+ df2 = read_csv(path, index_col=None, encoding=\"UTF-8\")\n+ tm.assert_frame_equal(df, df2)\n \n def test_to_csv_unicode_index_col(self):\n buf = StringIO(\"\")\n@@ -898,23 +894,23 @@ def test_to_csv_stringio(self, float_frame):\n recons = read_csv(buf, index_col=0)\n tm.assert_frame_equal(recons, float_frame)\n \n- def test_to_csv_float_format(self):\n+ def test_to_csv_float_format(self, temp_file):\n df = DataFrame(\n [[0.123456, 0.234567, 0.567567], [12.32112, 123123.2, 321321.2]],\n index=[\"A\", \"B\"],\n columns=[\"X\", \"Y\", \"Z\"],\n )\n \n- with tm.ensure_clean() as filename:\n- df.to_csv(filename, float_format=\"%.2f\")\n+ path = str(temp_file)\n+ df.to_csv(path, float_format=\"%.2f\")\n \n- rs = read_csv(filename, index_col=0)\n- xp = DataFrame(\n- [[0.12, 0.23, 0.57], [12.32, 123123.20, 321321.20]],\n- index=[\"A\", \"B\"],\n- columns=[\"X\", \"Y\", \"Z\"],\n- )\n- tm.assert_frame_equal(rs, xp)\n+ rs = read_csv(path, index_col=0)\n+ xp = DataFrame(\n+ [[0.12, 0.23, 0.57], [12.32, 123123.20, 321321.20]],\n+ index=[\"A\", \"B\"],\n+ columns=[\"X\", \"Y\", \"Z\"],\n+ )\n+ tm.assert_frame_equal(rs, xp)\n \n def test_to_csv_float_format_over_decimal(self):\n # GH#47436\n@@ -961,43 +957,50 @@ def test_to_csv_index_no_leading_comma(self):\n expected = tm.convert_rows_list_to_csv_str(expected_rows)\n assert buf.getvalue() == expected\n \n- def test_to_csv_lineterminators(self):\n+ def test_to_csv_lineterminators(self, temp_file):\n # see gh-20353\n df = DataFrame({\"A\": [1, 2, 3], \"B\": [4, 5, 6]}, index=[\"one\", \"two\", \"three\"])\n \n- with tm.ensure_clean() as path:\n- # case 1: CRLF as line terminator\n- df.to_csv(path, lineterminator=\"\\r\\n\")\n- expected = b\",A,B\\r\\none,1,4\\r\\ntwo,2,5\\r\\nthree,3,6\\r\\n\"\n+ path = str(temp_file)\n+ # case 1: CRLF as line terminator\n+ df.to_csv(path, lineterminator=\"\\r\\n\")\n+ expected = b\",A,B\\r\\none,1,4\\r\\ntwo,2,5\\r\\nthree,3,6\\r\\n\"\n+\n+ with open(path, mode=\"rb\") as f:\n+ assert f.read() == expected\n \n- with open(path, mode=\"rb\") as f:\n- assert f.read() == expected\n+ def test_to_csv_lineterminators2(self, temp_file):\n+ # see gh-20353\n+ df = DataFrame({\"A\": [1, 2, 3], \"B\": [4, 5, 6]}, index=[\"one\", \"two\", \"three\"])\n \n- with tm.ensure_clean() as path:\n- # case 2: LF as line terminator\n- df.to_csv(path, lineterminator=\"\\n\")\n- expected = b\",A,B\\none,1,4\\ntwo,2,5\\nthree,3,6\\n\"\n+ path = str(temp_file)\n+ # case 2: LF as line terminator\n+ df.to_csv(path, lineterminator=\"\\n\")\n+ expected = b\",A,B\\none,1,4\\ntwo,2,5\\nthree,3,6\\n\"\n \n- with open(path, mode=\"rb\") as f:\n- assert f.read() == expected\n+ with open(path, mode=\"rb\") as f:\n+ assert f.read() == expected\n \n- with tm.ensure_clean() as path:\n- # case 3: The default line terminator(=os.linesep)(gh-21406)\n- df.to_csv(path)\n- os_linesep = os.linesep.encode(\"utf-8\")\n- expected = (\n- b\",A,B\"\n- + os_linesep\n- + b\"one,1,4\"\n- + os_linesep\n- + b\"two,2,5\"\n- + os_linesep\n- + b\"three,3,6\"\n- + os_linesep\n- )\n+ def test_to_csv_lineterminators3(self, temp_file):\n+ # see gh-20353\n+ df = DataFrame({\"A\": [1, 2, 3], \"B\": [4, 5, 6]}, index=[\"one\", \"two\", \"three\"])\n+ path = str(temp_file)\n+ # case 3: The default line terminator(=os.linesep)(gh-21406)\n+ df.to_csv(path)\n+ os_linesep = os.linesep.encode(\"utf-8\")\n+ expected = (\n+ b\",A,B\"\n+ + os_linesep\n+ + b\"one,1,4\"\n+ + os_linesep\n+ + b\"two,2,5\"\n+ + os_linesep\n+ + b\"three,3,6\"\n+ + os_linesep\n+ )\n \n- with open(path, mode=\"rb\") as f:\n- assert f.read() == expected\n+ with open(path, mode=\"rb\") as f:\n+ assert f.read() == expected\n \n def test_to_csv_from_csv_categorical(self):\n # CSV with categoricals should result in the same output\n@@ -1055,120 +1058,116 @@ def test_to_csv_path_is_none(self, float_frame):\n ),\n ],\n )\n- def test_to_csv_compression(self, df, encoding, compression):\n- with tm.ensure_clean() as filename:\n- df.to_csv(filename, compression=compression, encoding=encoding)\n- # test the round trip - to_csv -> read_csv\n- result = read_csv(\n- filename, compression=compression, index_col=0, encoding=encoding\n- )\n- tm.assert_frame_equal(df, result)\n-\n- # test the round trip using file handle - to_csv -> read_csv\n- with get_handle(\n- filename, \"w\", compression=compression, encoding=encoding\n- ) as handles:\n- df.to_csv(handles.handle, encoding=encoding)\n- assert not handles.handle.closed\n-\n- result = read_csv(\n- filename,\n- compression=compression,\n- encoding=encoding,\n- index_col=0,\n- ).squeeze(\"columns\")\n- tm.assert_frame_equal(df, result)\n-\n- # explicitly make sure file is compressed\n- with tm.decompress_file(filename, compression) as fh:\n- text = fh.read().decode(encoding or \"utf8\")\n- for col in df.columns:\n- assert col in text\n-\n- with tm.decompress_file(filename, compression) as fh:\n- tm.assert_frame_equal(df, read_csv(fh, index_col=0, encoding=encoding))\n-\n- def test_to_csv_date_format(self, datetime_frame):\n- with tm.ensure_clean(\"__tmp_to_csv_date_format__\") as path:\n- dt_index = datetime_frame.index\n- datetime_frame = DataFrame(\n- {\"A\": dt_index, \"B\": dt_index.shift(1)}, index=dt_index\n- )\n- datetime_frame.to_csv(path, date_format=\"%Y%m%d\")\n+ def test_to_csv_compression(self, temp_file, df, encoding, compression):\n+ path = str(temp_file)\n+ df.to_csv(path, compression=compression, encoding=encoding)\n+ # test the round trip - to_csv -> read_csv\n+ result = read_csv(path, compression=compression, index_col=0, encoding=encoding)\n+ tm.assert_frame_equal(df, result)\n+\n+ # test the round trip using file handle - to_csv -> read_csv\n+ with get_handle(\n+ path, \"w\", compression=compression, encoding=encoding\n+ ) as handles:\n+ df.to_csv(handles.handle, encoding=encoding)\n+ assert not handles.handle.closed\n+\n+ result = read_csv(\n+ path,\n+ compression=compression,\n+ encoding=encoding,\n+ index_col=0,\n+ ).squeeze(\"columns\")\n+ tm.assert_frame_equal(df, result)\n+\n+ # explicitly make sure file is compressed\n+ with tm.decompress_file(path, compression) as fh:\n+ text = fh.read().decode(encoding or \"utf8\")\n+ for col in df.columns:\n+ assert col in text\n+\n+ with tm.decompress_file(path, compression) as fh:\n+ tm.assert_frame_equal(df, read_csv(fh, index_col=0, encoding=encoding))\n+\n+ def test_to_csv_date_format(self, temp_file, datetime_frame):\n+ path = str(temp_file)\n+ dt_index = datetime_frame.index\n+ datetime_frame = DataFrame(\n+ {\"A\": dt_index, \"B\": dt_index.shift(1)}, index=dt_index\n+ )\n+ datetime_frame.to_csv(path, date_format=\"%Y%m%d\")\n \n- # Check that the data was put in the specified format\n- test = read_csv(path, index_col=0)\n+ # Check that the data was put in the specified format\n+ test = read_csv(path, index_col=0)\n \n- datetime_frame_int = datetime_frame.map(lambda x: int(x.strftime(\"%Y%m%d\")))\n- datetime_frame_int.index = datetime_frame_int.index.map(\n- lambda x: int(x.strftime(\"%Y%m%d\"))\n- )\n+ datetime_frame_int = datetime_frame.map(lambda x: int(x.strftime(\"%Y%m%d\")))\n+ datetime_frame_int.index = datetime_frame_int.index.map(\n+ lambda x: int(x.strftime(\"%Y%m%d\"))\n+ )\n \n- tm.assert_frame_equal(test, datetime_frame_int)\n+ tm.assert_frame_equal(test, datetime_frame_int)\n \n- datetime_frame.to_csv(path, date_format=\"%Y-%m-%d\")\n+ datetime_frame.to_csv(path, date_format=\"%Y-%m-%d\")\n \n- # Check that the data was put in the specified format\n- test = read_csv(path, index_col=0)\n- datetime_frame_str = datetime_frame.map(lambda x: x.strftime(\"%Y-%m-%d\"))\n- datetime_frame_str.index = datetime_frame_str.index.map(\n- lambda x: x.strftime(\"%Y-%m-%d\")\n- )\n+ # Check that the data was put in the specified format\n+ test = read_csv(path, index_col=0)\n+ datetime_frame_str = datetime_frame.map(lambda x: x.strftime(\"%Y-%m-%d\"))\n+ datetime_frame_str.index = datetime_frame_str.index.map(\n+ lambda x: x.strftime(\"%Y-%m-%d\")\n+ )\n \n- tm.assert_frame_equal(test, datetime_frame_str)\n+ tm.assert_frame_equal(test, datetime_frame_str)\n \n- # Check that columns get converted\n- datetime_frame_columns = datetime_frame.T\n- datetime_frame_columns.to_csv(path, date_format=\"%Y%m%d\")\n+ # Check that columns get converted\n+ datetime_frame_columns = datetime_frame.T\n+ datetime_frame_columns.to_csv(path, date_format=\"%Y%m%d\")\n \n- test = read_csv(path, index_col=0)\n+ test = read_csv(path, index_col=0)\n \n- datetime_frame_columns = datetime_frame_columns.map(\n- lambda x: int(x.strftime(\"%Y%m%d\"))\n- )\n- # Columns don't get converted to ints by read_csv\n- datetime_frame_columns.columns = datetime_frame_columns.columns.map(\n- lambda x: x.strftime(\"%Y%m%d\")\n- )\n+ datetime_frame_columns = datetime_frame_columns.map(\n+ lambda x: int(x.strftime(\"%Y%m%d\"))\n+ )\n+ # Columns don't get converted to ints by read_csv\n+ datetime_frame_columns.columns = datetime_frame_columns.columns.map(\n+ lambda x: x.strftime(\"%Y%m%d\")\n+ )\n \n- tm.assert_frame_equal(test, datetime_frame_columns)\n+ tm.assert_frame_equal(test, datetime_frame_columns)\n \n- # test NaTs\n- nat_index = to_datetime(\n- [\"NaT\"] * 10 + [\"2000-01-01\", \"2000-01-01\", \"2000-01-01\"]\n- )\n- nat_frame = DataFrame({\"A\": nat_index}, index=nat_index)\n- nat_frame.to_csv(path, date_format=\"%Y-%m-%d\")\n+ # test NaTs\n+ nat_index = to_datetime(\n+ [\"NaT\"] * 10 + [\"2000-01-01\", \"2000-01-01\", \"2000-01-01\"]\n+ )\n+ nat_frame = DataFrame({\"A\": nat_index}, index=nat_index)\n+ nat_frame.to_csv(path, date_format=\"%Y-%m-%d\")\n \n- test = read_csv(path, parse_dates=[0, 1], index_col=0)\n+ test = read_csv(path, parse_dates=[0, 1], index_col=0)\n \n- tm.assert_frame_equal(test, nat_frame)\n+ tm.assert_frame_equal(test, nat_frame)\n \n @pytest.mark.parametrize(\"td\", [pd.Timedelta(0), pd.Timedelta(\"10s\")])\n- def test_to_csv_with_dst_transitions(self, td):\n- with tm.ensure_clean(\"csv_date_format_with_dst\") as path:\n- # make sure we are not failing on transitions\n- times = date_range(\n- \"2013-10-26 23:00\",\n- \"2013-10-27 01:00\",\n- tz=\"Europe/London\",\n- freq=\"h\",\n- ambiguous=\"infer\",\n- )\n- i = times + td\n- i = i._with_freq(None) # freq is not preserved by read_csv\n- time_range = np.array(range(len(i)), dtype=\"int64\")\n- df = DataFrame({\"A\": time_range}, index=i)\n- df.to_csv(path, index=True)\n- # we have to reconvert the index as we\n- # don't parse the tz's\n- result = read_csv(path, index_col=0)\n- result.index = to_datetime(result.index, utc=True).tz_convert(\n- \"Europe/London\"\n- )\n- tm.assert_frame_equal(result, df)\n-\n- def test_to_csv_with_dst_transitions_with_pickle(self):\n+ def test_to_csv_with_dst_transitions(self, td, temp_file):\n+ path = str(temp_file)\n+ # make sure we are not failing on transitions\n+ times = date_range(\n+ \"2013-10-26 23:00\",\n+ \"2013-10-27 01:00\",\n+ tz=\"Europe/London\",\n+ freq=\"h\",\n+ ambiguous=\"infer\",\n+ )\n+ i = times + td\n+ i = i._with_freq(None) # freq is not preserved by read_csv\n+ time_range = np.array(range(len(i)), dtype=\"int64\")\n+ df = DataFrame({\"A\": time_range}, index=i)\n+ df.to_csv(path, index=True)\n+ # we have to reconvert the index as we\n+ # don't parse the tz's\n+ result = read_csv(path, index_col=0)\n+ result.index = to_datetime(result.index, utc=True).tz_convert(\"Europe/London\")\n+ tm.assert_frame_equal(result, df)\n+\n+ def test_to_csv_with_dst_transitions_with_pickle(self, temp_file):\n # GH11619\n idx = date_range(\"2015-01-01\", \"2015-12-31\", freq=\"h\", tz=\"Europe/Paris\")\n idx = idx._with_freq(None) # freq does not round-trip\n@@ -1188,10 +1187,10 @@ def test_to_csv_with_dst_transitions_with_pickle(self):\n # assert working\n df.astype(str)\n \n- with tm.ensure_clean(\"csv_date_format_with_dst\") as path:\n- df.to_pickle(path)\n- result = pd.read_pickle(path)\n- tm.assert_frame_equal(result, df)\n+ path = str(temp_file)\n+ df.to_pickle(path)\n+ result = pd.read_pickle(path)\n+ tm.assert_frame_equal(result, df)\n \n def test_to_csv_quoting(self):\n df = DataFrame(\n@@ -1344,15 +1343,17 @@ def test_to_csv_single_level_multi_index(self):\n result = df.to_csv(lineterminator=\"\\n\")\n tm.assert_almost_equal(result, expected)\n \n- def test_gz_lineend(self):\n+ def test_gz_lineend(self, tmp_path):\n # GH 25311\n df = DataFrame({\"a\": [1, 2]})\n expected_rows = [\"a\", \"1\", \"2\"]\n expected = tm.convert_rows_list_to_csv_str(expected_rows)\n- with tm.ensure_clean(\"__test_gz_lineend.csv.gz\") as path:\n- df.to_csv(path, index=False)\n- with tm.decompress_file(path, compression=\"gzip\") as f:\n- result = f.read().decode(\"utf-8\")\n+ file_path = tmp_path / \"__test_gz_lineend.csv.gz\"\n+ file_path.touch()\n+ path = str(file_path)\n+ df.to_csv(path, index=False)\n+ with tm.decompress_file(path, compression=\"gzip\") as f:\n+ result = f.read().decode(\"utf-8\")\n \n assert result == expected\n \ndiff --git a/pandas/tests/indexing/test_chaining_and_caching.py b/pandas/tests/indexing/test_chaining_and_caching.py\nindex c9e0aa2ffd77c..cfadf34823b0e 100644\n--- a/pandas/tests/indexing/test_chaining_and_caching.py\n+++ b/pandas/tests/indexing/test_chaining_and_caching.py\n@@ -221,15 +221,15 @@ def test_detect_chained_assignment_object_dtype(self):\n tm.assert_frame_equal(df, df_original)\n \n @pytest.mark.arm_slow\n- def test_detect_chained_assignment_is_copy_pickle(self):\n+ def test_detect_chained_assignment_is_copy_pickle(self, temp_file):\n # gh-5475: Make sure that is_copy is picked up reconstruction\n df = DataFrame({\"A\": [1, 2]})\n \n- with tm.ensure_clean(\"__tmp__pickle\") as path:\n- df.to_pickle(path)\n- df2 = pd.read_pickle(path)\n- df2[\"B\"] = df2[\"A\"]\n- df2[\"B\"] = df2[\"A\"]\n+ path = str(temp_file)\n+ df.to_pickle(path)\n+ df2 = pd.read_pickle(path)\n+ df2[\"B\"] = df2[\"A\"]\n+ df2[\"B\"] = df2[\"A\"]\n \n @pytest.mark.arm_slow\n def test_detect_chained_assignment_str(self):\ndiff --git a/pandas/tests/io/parser/common/test_file_buffer_url.py b/pandas/tests/io/parser/common/test_file_buffer_url.py\nindex 2f9e968dd1b71..b03e31c21fc81 100644\n--- a/pandas/tests/io/parser/common/test_file_buffer_url.py\n+++ b/pandas/tests/io/parser/common/test_file_buffer_url.py\n@@ -233,12 +233,12 @@ def test_eof_states(all_parsers, data, kwargs, expected, msg, request):\n tm.assert_frame_equal(result, expected)\n \n \n-def test_temporary_file(all_parsers):\n+def test_temporary_file(all_parsers, temp_file):\n # see gh-13398\n parser = all_parsers\n data = \"0 0\"\n \n- with tm.ensure_clean(mode=\"w+\", return_filelike=True) as new_file:\n+ with temp_file.open(mode=\"w+\", encoding=\"utf-8\") as new_file:\n new_file.write(data)\n new_file.flush()\n new_file.seek(0)\ndiff --git a/pandas/tests/io/parser/test_encoding.py b/pandas/tests/io/parser/test_encoding.py\nindex f2d5c77121467..31b7e9df1e0ec 100644\n--- a/pandas/tests/io/parser/test_encoding.py\n+++ b/pandas/tests/io/parser/test_encoding.py\n@@ -180,7 +180,9 @@ def test_binary_mode_file_buffers(all_parsers, file_path, encoding, datapath):\n \n \n @pytest.mark.parametrize(\"pass_encoding\", [True, False])\n-def test_encoding_temp_file(all_parsers, utf_value, encoding_fmt, pass_encoding):\n+def test_encoding_temp_file(\n+ all_parsers, utf_value, encoding_fmt, pass_encoding, temp_file\n+):\n # see gh-24130\n parser = all_parsers\n encoding = encoding_fmt.format(utf_value)\n@@ -191,7 +193,7 @@ def test_encoding_temp_file(all_parsers, utf_value, encoding_fmt, pass_encoding)\n \n expected = DataFrame({\"foo\": [\"bar\"]})\n \n- with tm.ensure_clean(mode=\"w+\", encoding=encoding, return_filelike=True) as f:\n+ with temp_file.open(mode=\"w+\", encoding=encoding) as f:\n f.write(\"foo\\nbar\")\n f.seek(0)\n \ndiff --git a/pandas/tests/plotting/frame/test_frame_subplots.py b/pandas/tests/plotting/frame/test_frame_subplots.py\nindex 4d8d8fa4cdee3..fb34592b288af 100644\n--- a/pandas/tests/plotting/frame/test_frame_subplots.py\n+++ b/pandas/tests/plotting/frame/test_frame_subplots.py\n@@ -544,7 +544,7 @@ def test_subplots_sharex_false(self):\n tm.assert_numpy_array_equal(axs[0].get_xticks(), expected_ax1)\n tm.assert_numpy_array_equal(axs[1].get_xticks(), expected_ax2)\n \n- def test_subplots_constrained_layout(self):\n+ def test_subplots_constrained_layout(self, temp_file):\n # GH 25261\n idx = date_range(start=\"now\", periods=10)\n df = DataFrame(np.random.default_rng(2).random((10, 3)), index=idx)\n@@ -554,7 +554,7 @@ def test_subplots_constrained_layout(self):\n _, axes = mpl.pyplot.subplots(2, **kwargs)\n with tm.assert_produces_warning(None):\n df.plot(ax=axes[0])\n- with tm.ensure_clean(return_filelike=True) as path:\n+ with temp_file.open(mode=\"wb\") as path:\n mpl.pyplot.savefig(path)\n \n @pytest.mark.parametrize(\ndiff --git a/pandas/tests/plotting/test_datetimelike.py b/pandas/tests/plotting/test_datetimelike.py\nindex 112172656b6ec..d478fbfb46b08 100644\n--- a/pandas/tests/plotting/test_datetimelike.py\n+++ b/pandas/tests/plotting/test_datetimelike.py\n@@ -42,6 +42,7 @@\n from pandas.tseries.offsets import WeekOfMonth\n \n mpl = pytest.importorskip(\"matplotlib\")\n+plt = pytest.importorskip(\"matplotlib.pyplot\")\n \n \n class TestTSPlot:\n@@ -1714,6 +1715,25 @@ def test_check_xticks_rot_sharex(self):\n axes = df.plot(x=\"x\", y=\"y\", subplots=True, sharex=False)\n _check_ticks_props(axes, xrot=0)\n \n+ @pytest.mark.parametrize(\n+ \"idx\",\n+ [\n+ date_range(\"2020-01-01\", periods=5),\n+ date_range(\"2020-01-01\", periods=5, tz=\"UTC\"),\n+ timedelta_range(\"1 day\", periods=5, freq=\"D\"),\n+ period_range(\"2020-01-01\", periods=5, freq=\"D\"),\n+ Index([date(2000, 1, i) for i in [1, 3, 6, 20, 22]], dtype=object),\n+ range(5),\n+ ],\n+ )\n+ def test_pickle_fig(self, temp_file, frame_or_series, idx):\n+ # GH18439, GH#24088, statsmodels#4772\n+ df = frame_or_series(range(5), index=idx)\n+ fig, ax = plt.subplots(1, 1)\n+ df.plot(ax=ax)\n+ with temp_file.open(mode=\"wb\") as path:\n+ pickle.dump(fig, path)\n+\n \n def _check_plot_works(f, freq=None, series=None, *args, **kwargs):\n import matplotlib.pyplot as plt\n@@ -1746,9 +1766,5 @@ def _check_plot_works(f, freq=None, series=None, *args, **kwargs):\n kwargs[\"ax\"] = ax\n ret = f(*args, **kwargs)\n assert ret is not None # TODO: do something more intelligent\n-\n- # GH18439, GH#24088, statsmodels#4772\n- with tm.ensure_clean(return_filelike=True) as path:\n- pickle.dump(fig, path)\n finally:\n plt.close(fig)\ndiff --git a/pandas/tests/test_expressions.py b/pandas/tests/test_expressions.py\nindex 838fee1db878c..68dcc1a18eda7 100644\n--- a/pandas/tests/test_expressions.py\n+++ b/pandas/tests/test_expressions.py\n@@ -320,7 +320,7 @@ def test_bool_ops_raise_on_arithmetic(self, op_str, opname):\n @pytest.mark.parametrize(\n \"op_str,opname\", [(\"+\", \"add\"), (\"*\", \"mul\"), (\"-\", \"sub\")]\n )\n- def test_bool_ops_warn_on_arithmetic(self, op_str, opname):\n+ def test_bool_ops_warn_on_arithmetic(self, op_str, opname, monkeypatch):\n n = 10\n df = DataFrame(\n {\n@@ -339,36 +339,38 @@ def test_bool_ops_warn_on_arithmetic(self, op_str, opname):\n # raises TypeError\n return\n \n- with tm.use_numexpr(True, min_elements=5):\n- with tm.assert_produces_warning():\n- r = f(df, df)\n- e = fe(df, df)\n- tm.assert_frame_equal(r, e)\n-\n- with tm.assert_produces_warning():\n- r = f(df.a, df.b)\n- e = fe(df.a, df.b)\n- tm.assert_series_equal(r, e)\n-\n- with tm.assert_produces_warning():\n- r = f(df.a, True)\n- e = fe(df.a, True)\n- tm.assert_series_equal(r, e)\n-\n- with tm.assert_produces_warning():\n- r = f(False, df.a)\n- e = fe(False, df.a)\n- tm.assert_series_equal(r, e)\n-\n- with tm.assert_produces_warning():\n- r = f(False, df)\n- e = fe(False, df)\n- tm.assert_frame_equal(r, e)\n-\n- with tm.assert_produces_warning():\n- r = f(df, True)\n- e = fe(df, True)\n- tm.assert_frame_equal(r, e)\n+ with monkeypatch.context() as m:\n+ m.setattr(expr, \"_MIN_ELEMENTS\", 5)\n+ with option_context(\"compute.use_numexpr\", True):\n+ with tm.assert_produces_warning():\n+ r = f(df, df)\n+ e = fe(df, df)\n+ tm.assert_frame_equal(r, e)\n+\n+ with tm.assert_produces_warning():\n+ r = f(df.a, df.b)\n+ e = fe(df.a, df.b)\n+ tm.assert_series_equal(r, e)\n+\n+ with tm.assert_produces_warning():\n+ r = f(df.a, True)\n+ e = fe(df.a, True)\n+ tm.assert_series_equal(r, e)\n+\n+ with tm.assert_produces_warning():\n+ r = f(False, df.a)\n+ e = fe(False, df.a)\n+ tm.assert_series_equal(r, e)\n+\n+ with tm.assert_produces_warning():\n+ r = f(False, df)\n+ e = fe(False, df)\n+ tm.assert_frame_equal(r, e)\n+\n+ with tm.assert_produces_warning():\n+ r = f(df, True)\n+ e = fe(df, True)\n+ tm.assert_frame_equal(r, e)\n \n @pytest.mark.parametrize(\n \"test_input,expected\",\n"},"body":{"kind":"string","value":"* Replaced only use of `use_numexpr`\r\n* Created pytest native `temp_file` fixture for use over `tm.ensure_clean`\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57571"},"created_at":{"kind":"string","value":"2024-02-22T20:25:42Z"},"closed_at":{"kind":"string","value":"2024-02-24T18:36:06Z"},"merged_at":{"kind":"string","value":"2024-02-24T18:36:05Z"},"updated_at":{"kind":"string","value":"2024-02-24T18:36:09Z"}}},{"rowIdx":885,"cells":{"title":{"kind":"string","value":"BUG: Interchange object data buffer has the wrong dtype / from_dataframe incorrect "},"diff":{"kind":"string","value":"diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml\nindex 375c74f29e63a..3253f9ab87363 100644\n--- a/.pre-commit-config.yaml\n+++ b/.pre-commit-config.yaml\n@@ -53,13 +53,11 @@ repos:\n - repo: https://github.com/pre-commit/pre-commit-hooks\n rev: v4.5.0\n hooks:\n- - id: check-ast\n - id: check-case-conflict\n - id: check-toml\n - id: check-xml\n - id: check-yaml\n exclude: ^ci/meta.yaml$\n- - id: debug-statements\n - id: end-of-file-fixer\n exclude: \\.txt$\n - id: mixed-line-ending\ndiff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst\nindex 3fdb4af52a8c0..a29b1991045a0 100644\n--- a/doc/source/whatsnew/v3.0.0.rst\n+++ b/doc/source/whatsnew/v3.0.0.rst\n@@ -291,6 +291,7 @@ Other\n - Bug in :func:`tseries.api.guess_datetime_format` would fail to infer time format when \"%Y\" == \"%H%M\" (:issue:`57452`)\n - Bug in :meth:`DataFrame.sort_index` when passing ``axis=\"columns\"`` and ``ignore_index=True`` and ``ascending=False`` not returning a :class:`RangeIndex` columns (:issue:`57293`)\n - Bug in :meth:`DataFrame.where` where using a non-bool type array in the function would return a ``ValueError`` instead of a ``TypeError`` (:issue:`56330`)\n+- Bug in Dataframe Interchange Protocol implementation was returning incorrect results for data buffers' associated dtype, for string and datetime columns (:issue:`54781`)\n \n .. ***DO NOT USE THIS SECTION***\n \ndiff --git a/pandas/core/interchange/column.py b/pandas/core/interchange/column.py\nindex 2e60b2a2138e3..7effc42d5ba28 100644\n--- a/pandas/core/interchange/column.py\n+++ b/pandas/core/interchange/column.py\n@@ -278,20 +278,28 @@ def _get_data_buffer(\n \"\"\"\n Return the buffer containing the data and the buffer's associated dtype.\n \"\"\"\n- if self.dtype[0] in (\n- DtypeKind.INT,\n- DtypeKind.UINT,\n- DtypeKind.FLOAT,\n- DtypeKind.BOOL,\n- DtypeKind.DATETIME,\n- ):\n+ if self.dtype[0] == DtypeKind.DATETIME:\n # self.dtype[2] is an ArrowCTypes.TIMESTAMP where the tz will make\n # it longer than 4 characters\n- if self.dtype[0] == DtypeKind.DATETIME and len(self.dtype[2]) > 4:\n+ if len(self.dtype[2]) > 4:\n np_arr = self._col.dt.tz_convert(None).to_numpy()\n else:\n np_arr = self._col.to_numpy()\n buffer = PandasBuffer(np_arr, allow_copy=self._allow_copy)\n+ dtype = (\n+ DtypeKind.INT,\n+ 64,\n+ ArrowCTypes.INT64,\n+ Endianness.NATIVE,\n+ )\n+ elif self.dtype[0] in (\n+ DtypeKind.INT,\n+ DtypeKind.UINT,\n+ DtypeKind.FLOAT,\n+ DtypeKind.BOOL,\n+ ):\n+ np_arr = self._col.to_numpy()\n+ buffer = PandasBuffer(np_arr, allow_copy=self._allow_copy)\n dtype = self.dtype\n elif self.dtype[0] == DtypeKind.CATEGORICAL:\n codes = self._col.values._codes\n@@ -314,7 +322,12 @@ def _get_data_buffer(\n # Define the dtype for the returned buffer\n # TODO: this will need correcting\n # https://github.com/pandas-dev/pandas/issues/54781\n- dtype = self.dtype\n+ dtype = (\n+ DtypeKind.UINT,\n+ 8,\n+ ArrowCTypes.UINT8,\n+ Endianness.NATIVE,\n+ ) # note: currently only support native endianness\n else:\n raise NotImplementedError(f\"Data type {self._col.dtype} not handled yet\")\n \ndiff --git a/pandas/tests/interchange/test_impl.py b/pandas/tests/interchange/test_impl.py\nindex 4933cca97462f..e4fa6e4451a4c 100644\n--- a/pandas/tests/interchange/test_impl.py\n+++ b/pandas/tests/interchange/test_impl.py\n@@ -435,3 +435,48 @@ def test_empty_dataframe():\n result = pd.api.interchange.from_dataframe(dfi, allow_copy=False)\n expected = pd.DataFrame({\"a\": []}, dtype=\"int8\")\n tm.assert_frame_equal(result, expected)\n+\n+\n+@pytest.mark.parametrize(\n+ (\"data\", \"expected_dtype\", \"expected_buffer_dtype\"),\n+ [\n+ (\n+ pd.Series([\"a\", \"b\", \"a\"], dtype=\"category\"),\n+ (DtypeKind.CATEGORICAL, 8, \"c\", \"=\"),\n+ (DtypeKind.INT, 8, \"c\", \"|\"),\n+ ),\n+ (\n+ pd.Series(\n+ [datetime(2022, 1, 1), datetime(2022, 1, 2), datetime(2022, 1, 3)]\n+ ),\n+ (DtypeKind.DATETIME, 64, \"tsn:\", \"=\"),\n+ (DtypeKind.INT, 64, ArrowCTypes.INT64, \"=\"),\n+ ),\n+ (\n+ pd.Series([\"a\", \"bc\", None]),\n+ (DtypeKind.STRING, 8, ArrowCTypes.STRING, \"=\"),\n+ (DtypeKind.UINT, 8, ArrowCTypes.UINT8, \"=\"),\n+ ),\n+ (\n+ pd.Series([1, 2, 3]),\n+ (DtypeKind.INT, 64, ArrowCTypes.INT64, \"=\"),\n+ (DtypeKind.INT, 64, ArrowCTypes.INT64, \"=\"),\n+ ),\n+ (\n+ pd.Series([1.5, 2, 3]),\n+ (DtypeKind.FLOAT, 64, ArrowCTypes.FLOAT64, \"=\"),\n+ (DtypeKind.FLOAT, 64, ArrowCTypes.FLOAT64, \"=\"),\n+ ),\n+ ],\n+)\n+def test_buffer_dtype_categorical(\n+ data: pd.Series,\n+ expected_dtype: tuple[DtypeKind, int, str, str],\n+ expected_buffer_dtype: tuple[DtypeKind, int, str, str],\n+) -> None:\n+ # https://github.com/pandas-dev/pandas/issues/54781\n+ df = pd.DataFrame({\"data\": data})\n+ dfi = df.__dataframe__()\n+ col = dfi.get_column_by_name(\"data\")\n+ assert col.dtype == expected_dtype\n+ assert col.get_buffers()[\"data\"][1] == expected_buffer_dtype\n"},"body":{"kind":"string","value":"- [ ] closes #54781 (Replace xxxx with the GitHub issue number)\r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57570"},"created_at":{"kind":"string","value":"2024-02-22T18:30:43Z"},"closed_at":{"kind":"string","value":"2024-02-23T17:12:43Z"},"merged_at":{"kind":"string","value":"2024-02-23T17:12:43Z"},"updated_at":{"kind":"string","value":"2024-02-23T17:12:56Z"}}},{"rowIdx":886,"cells":{"title":{"kind":"string","value":"Backport PR #57556 on branch 2.2.x (Remove PyArrow deprecation warning)"},"diff":{"kind":"string","value":"diff --git a/.github/workflows/unit-tests.yml b/.github/workflows/unit-tests.yml\nindex 4c7aa1e1e49ee..8736674bbf965 100644\n--- a/.github/workflows/unit-tests.yml\n+++ b/.github/workflows/unit-tests.yml\n@@ -92,10 +92,7 @@ jobs:\n - name: \"Numpy Dev\"\n env_file: actions-311-numpydev.yaml\n pattern: \"not slow and not network and not single_cpu\"\n- # Currently restricted the warnings that error to Deprecation Warnings from numpy\n- # done since pyarrow isn't compatible with numpydev always\n- # TODO: work with pyarrow to revert this?\n- test_args: \"-W error::DeprecationWarning:numpy -W error::FutureWarning:numpy\"\n+ test_args: \"-W error::DeprecationWarning -W error::FutureWarning\"\n - name: \"Pyarrow Nightly\"\n env_file: actions-311-pyarrownightly.yaml\n pattern: \"not slow and not network and not single_cpu\"\ndiff --git a/doc/source/whatsnew/v2.2.1.rst b/doc/source/whatsnew/v2.2.1.rst\nindex e381f9df16383..35d64c99f2002 100644\n--- a/doc/source/whatsnew/v2.2.1.rst\n+++ b/doc/source/whatsnew/v2.2.1.rst\n@@ -67,6 +67,16 @@ Bug fixes\n \n Other\n ~~~~~\n+\n+.. note::\n+\n+ The ``DeprecationWarning`` that was raised when pandas was imported without PyArrow being\n+ installed has been removed. This decision was made because the warning was too noisy for too\n+ many users and a lot of feedback was collected about the decision to make PyArrow a required\n+ dependency. Pandas is currently considering the decision whether or not PyArrow should be added\n+ as a hard dependency in 3.0. Interested users can follow the discussion\n+ `here <https://github.com/pandas-dev/pandas/issues/57073>`_.\n+\n - Added the argument ``skipna`` to :meth:`DataFrameGroupBy.first`, :meth:`DataFrameGroupBy.last`, :meth:`SeriesGroupBy.first`, and :meth:`SeriesGroupBy.last`; achieving ``skipna=False`` used to be available via :meth:`DataFrameGroupBy.nth`, but the behavior was changed in pandas 2.0.0 (:issue:`57019`)\n - Added the argument ``skipna`` to :meth:`Resampler.first`, :meth:`Resampler.last` (:issue:`57019`)\n \ndiff --git a/pandas/__init__.py b/pandas/__init__.py\nindex ed524c2bb3619..ca2eba2043292 100644\n--- a/pandas/__init__.py\n+++ b/pandas/__init__.py\n@@ -203,36 +203,7 @@\n stacklevel=2,\n )\n \n-# DeprecationWarning for missing pyarrow\n-from pandas.compat.pyarrow import pa_version_under10p1, pa_not_found\n-\n-if pa_version_under10p1:\n- # pyarrow is either too old or nonexistent, warn\n- from pandas.compat._optional import VERSIONS\n-\n- if pa_not_found:\n- pa_msg = \"was not found to be installed on your system.\"\n- else:\n- pa_msg = (\n- f\"was too old on your system - pyarrow {VERSIONS['pyarrow']} \"\n- \"is the current minimum supported version as of this release.\"\n- )\n-\n- warnings.warn(\n- f\"\"\"\n-Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),\n-(to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)\n-but {pa_msg}\n-If this would cause problems for you,\n-please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466\n- \"\"\", # noqa: E501\n- DeprecationWarning,\n- stacklevel=2,\n- )\n- del VERSIONS, pa_msg\n-\n-# Delete all unnecessary imported modules\n-del pa_version_under10p1, pa_not_found, warnings, os\n+del warnings, os\n \n # module level doc-string\n __doc__ = \"\"\"\ndiff --git a/pandas/compat/pyarrow.py b/pandas/compat/pyarrow.py\nindex 2e151123ef2c9..beb4814914101 100644\n--- a/pandas/compat/pyarrow.py\n+++ b/pandas/compat/pyarrow.py\n@@ -8,7 +8,6 @@\n import pyarrow as pa\n \n _palv = Version(Version(pa.__version__).base_version)\n- pa_not_found = False\n pa_version_under10p1 = _palv < Version(\"10.0.1\")\n pa_version_under11p0 = _palv < Version(\"11.0.0\")\n pa_version_under12p0 = _palv < Version(\"12.0.0\")\n@@ -17,7 +16,6 @@\n pa_version_under14p1 = _palv < Version(\"14.0.1\")\n pa_version_under15p0 = _palv < Version(\"15.0.0\")\n except ImportError:\n- pa_not_found = True\n pa_version_under10p1 = True\n pa_version_under11p0 = True\n pa_version_under12p0 = True\ndiff --git a/pandas/tests/test_common.py b/pandas/tests/test_common.py\nindex 4af71be11fe6b..e8a1c961c8cb6 100644\n--- a/pandas/tests/test_common.py\n+++ b/pandas/tests/test_common.py\n@@ -8,8 +8,6 @@\n import numpy as np\n import pytest\n \n-import pandas.util._test_decorators as td\n-\n import pandas as pd\n from pandas import Series\n import pandas._testing as tm\n@@ -267,26 +265,3 @@ def test_bz2_missing_import():\n code = textwrap.dedent(code)\n call = [sys.executable, \"-c\", code]\n subprocess.check_output(call)\n-\n-\n-@td.skip_if_installed(\"pyarrow\")\n-@pytest.mark.parametrize(\"module\", [\"pandas\", \"pandas.arrays\"])\n-def test_pyarrow_missing_warn(module):\n- # GH56896\n- response = subprocess.run(\n- [sys.executable, \"-c\", f\"import {module}\"],\n- capture_output=True,\n- check=True,\n- )\n- msg = \"\"\"\n-Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),\n-(to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)\n-but was not found to be installed on your system.\n-If this would cause problems for you,\n-please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466\n-\"\"\" # noqa: E501\n- stderr_msg = response.stderr.decode(\"utf-8\")\n- # Split by \\n to avoid \\r\\n vs \\n differences on Windows/Unix\n- # https://stackoverflow.com/questions/11989501/replacing-r-n-with-n\n- stderr_msg = \"\\n\".join(stderr_msg.splitlines())\n- assert msg in stderr_msg\n"},"body":{"kind":"string","value":"#57556"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57568"},"created_at":{"kind":"string","value":"2024-02-22T17:45:49Z"},"closed_at":{"kind":"string","value":"2024-02-22T18:45:36Z"},"merged_at":{"kind":"string","value":"2024-02-22T18:45:36Z"},"updated_at":{"kind":"string","value":"2024-02-22T18:45:40Z"}}},{"rowIdx":887,"cells":{"title":{"kind":"string","value":"DEPS: update numexpr to use not buggy numexpr 2.8.x anymore (update to 2.9.0) - fix critical CVE-2023-39631"},"diff":{"kind":"string","value":"diff --git a/pyproject.toml b/pyproject.toml\nindex 82a9d72c8cc74..43cf1274dc380 100644\n--- a/pyproject.toml\n+++ b/pyproject.toml\n@@ -64,7 +64,7 @@ matplotlib = \"pandas:plotting._matplotlib\"\n [project.optional-dependencies]\n test = ['hypothesis>=6.46.1', 'pytest>=7.3.2', 'pytest-xdist>=2.2.0']\n pyarrow = ['pyarrow>=10.0.1']\n-performance = ['bottleneck>=1.3.6', 'numba>=0.56.4', 'numexpr>=2.8.4']\n+performance = ['bottleneck>=1.3.6', 'numba>=0.56.4', 'numexpr>=2.9.0']\n computation = ['scipy>=1.10.0', 'xarray>=2022.12.0']\n fss = ['fsspec>=2022.11.0']\n aws = ['s3fs>=2022.11.0']\n@@ -100,7 +100,7 @@ all = ['adbc-driver-postgresql>=0.8.0',\n 'lxml>=4.9.2',\n 'matplotlib>=3.6.3',\n 'numba>=0.56.4',\n- 'numexpr>=2.8.4',\n+ 'numexpr>=2.9.0',\n 'odfpy>=1.4.1',\n 'openpyxl>=3.1.0',\n 'psycopg2>=2.9.6',\n"},"body":{"kind":"string","value":"update numexpr to 2.9.0 to fix CVE-2023-39631 findings\r\n\r\nHINT: come from other project (apache-superset) where panda is injecting this faulty numexpr inside the project as sub-dependency\r\n\r\n- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)\r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57567"},"created_at":{"kind":"string","value":"2024-02-22T14:22:22Z"},"closed_at":{"kind":"string","value":"2024-02-22T16:54:52Z"},"merged_at":{"kind":"null"},"updated_at":{"kind":"string","value":"2024-02-22T16:54:53Z"}}},{"rowIdx":888,"cells":{"title":{"kind":"string","value":"DOC: fix ES01 for pandas.Flags"},"diff":{"kind":"string","value":"diff --git a/ci/code_checks.sh b/ci/code_checks.sh\nindex 04c3ff3a42971..6469f39e7c332 100755\n--- a/ci/code_checks.sh\n+++ b/ci/code_checks.sh\n@@ -521,7 +521,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n pandas.DatetimeIndex.year\\\n pandas.DatetimeTZDtype.tz\\\n pandas.DatetimeTZDtype.unit\\\n- pandas.Flags\\\n pandas.HDFStore.get\\\n pandas.HDFStore.info\\\n pandas.HDFStore.keys\\\ndiff --git a/pandas/core/flags.py b/pandas/core/flags.py\nindex 8dcf49745bf2d..eceb86dc61d9f 100644\n--- a/pandas/core/flags.py\n+++ b/pandas/core/flags.py\n@@ -11,6 +11,10 @@ class Flags:\n \"\"\"\n Flags that apply to pandas objects.\n \n+ “Flags” differ from “metadata”. Flags reflect properties of the pandas\n+ object (the Series or DataFrame). Metadata refer to properties of the\n+ dataset, and should be stored in DataFrame.attrs.\n+\n Parameters\n ----------\n obj : Series or DataFrame\n@@ -30,6 +34,11 @@ class Flags:\n it is expected that every method taking or returning one or more\n DataFrame or Series objects will propagate ``allows_duplicate_labels``.\n \n+ See Also\n+ --------\n+ DataFrame.attrs : Dictionary of global attributes of this dataset.\n+ Series.attrs : Dictionary of global attributes of this dataset.\n+\n Examples\n --------\n Attributes can be set in two ways:\n"},"body":{"kind":"string","value":"All ES01 Errors resolved in the following cases:\r\n\r\n1. scripts/validate_docstrings.py --format=actions --errors=ES01 pandas.Flags\r\n\r\n- [x] xref https://github.com/pandas-dev/pandas/issues/57440\r\n- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57563"},"created_at":{"kind":"string","value":"2024-02-22T07:45:14Z"},"closed_at":{"kind":"string","value":"2024-02-22T17:00:31Z"},"merged_at":{"kind":"string","value":"2024-02-22T17:00:31Z"},"updated_at":{"kind":"string","value":"2024-02-23T02:36:10Z"}}},{"rowIdx":889,"cells":{"title":{"kind":"string","value":"DOC: fixing GL08 errors for pandas.DatetimeIndex.as_unit and pandas.DatetimeIndex.freq"},"diff":{"kind":"string","value":"diff --git a/ci/code_checks.sh b/ci/code_checks.sh\nindex 47a2cf93a4f89..d89c64700ffbb 100755\n--- a/ci/code_checks.sh\n+++ b/ci/code_checks.sh\n@@ -71,6 +71,7 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n \n MSG='Partially validate docstrings (PR02)' ; echo $MSG\n $BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=PR02 --ignore_functions \\\n+ pandas.Series.dt.as_unit\\\n pandas.Series.dt.to_period\\\n pandas.Series.dt.tz_localize\\\n pandas.Series.dt.tz_convert\\\n@@ -143,8 +144,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n \n MSG='Partially validate docstrings (GL08)' ; echo $MSG\n $BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=GL08 --ignore_functions \\\n- pandas.DatetimeIndex.as_unit\\\n- pandas.DatetimeIndex.freq\\\n pandas.ExcelFile.book\\\n pandas.ExcelFile.sheet_names\\\n pandas.Index.empty\\\n@@ -1496,6 +1495,7 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n pandas.Series.cat.rename_categories\\\n pandas.Series.cat.reorder_categories\\\n pandas.Series.cat.set_categories\\\n+ pandas.Series.dt.as_unit\\\n pandas.Series.dt.ceil\\\n pandas.Series.dt.day_name\\\n pandas.Series.dt.floor\\\ndiff --git a/pandas/core/arrays/datetimelike.py b/pandas/core/arrays/datetimelike.py\nindex 2aaf119c323a0..1805a86ee32ce 100644\n--- a/pandas/core/arrays/datetimelike.py\n+++ b/pandas/core/arrays/datetimelike.py\n@@ -2041,6 +2041,29 @@ def _validate_dtype(cls, values, dtype):\n def freq(self):\n \"\"\"\n Return the frequency object if it is set, otherwise None.\n+\n+ To learn more about the frequency strings, please see\n+ :ref:`this link<timeseries.offset_aliases>`.\n+\n+ See Also\n+ --------\n+ DatetimeIndex.freq : Return the frequency object if it is set, otherwise None.\n+ PeriodIndex.freq : Return the frequency object if it is set, otherwise None.\n+\n+ Examples\n+ --------\n+ >>> datetimeindex = pd.date_range(\n+ ... \"2022-02-22 02:22:22\", periods=10, tz=\"America/Chicago\", freq=\"h\"\n+ ... )\n+ >>> datetimeindex\n+ DatetimeIndex(['2022-02-22 02:22:22-06:00', '2022-02-22 03:22:22-06:00',\n+ '2022-02-22 04:22:22-06:00', '2022-02-22 05:22:22-06:00',\n+ '2022-02-22 06:22:22-06:00', '2022-02-22 07:22:22-06:00',\n+ '2022-02-22 08:22:22-06:00', '2022-02-22 09:22:22-06:00',\n+ '2022-02-22 10:22:22-06:00', '2022-02-22 11:22:22-06:00'],\n+ dtype='datetime64[ns, America/Chicago]', freq='h')\n+ >>> datetimeindex.freq\n+ <Hour>\n \"\"\"\n return self._freq\n \n@@ -2154,6 +2177,47 @@ def unit(self) -> str:\n return dtype_to_unit(self.dtype) # type: ignore[arg-type]\n \n def as_unit(self, unit: str, round_ok: bool = True) -> Self:\n+ \"\"\"\n+ Convert to a dtype with the given unit resolution.\n+\n+ The limits of timestamp representation depend on the chosen resolution.\n+ Different resolutions can be converted to each other through as_unit.\n+\n+ Parameters\n+ ----------\n+ unit : {'s', 'ms', 'us', 'ns'}\n+ round_ok : bool, default True\n+ If False and the conversion requires rounding, raise ValueError.\n+\n+ Returns\n+ -------\n+ same type as self\n+ Converted to the specified unit.\n+\n+ See Also\n+ --------\n+ Timestamp.as_unit : Convert to the given unit.\n+\n+ Examples\n+ --------\n+ For :class:`pandas.DatetimeIndex`:\n+\n+ >>> idx = pd.DatetimeIndex([\"2020-01-02 01:02:03.004005006\"])\n+ >>> idx\n+ DatetimeIndex(['2020-01-02 01:02:03.004005006'],\n+ dtype='datetime64[ns]', freq=None)\n+ >>> idx.as_unit(\"s\")\n+ DatetimeIndex(['2020-01-02 01:02:03'], dtype='datetime64[s]', freq=None)\n+\n+ For :class:`pandas.TimedeltaIndex`:\n+\n+ >>> tdelta_idx = pd.to_timedelta([\"1 day 3 min 2 us 42 ns\"])\n+ >>> tdelta_idx\n+ TimedeltaIndex(['1 days 00:03:00.000002042'],\n+ dtype='timedelta64[ns]', freq=None)\n+ >>> tdelta_idx.as_unit(\"s\")\n+ TimedeltaIndex(['1 days 00:03:00'], dtype='timedelta64[s]', freq=None)\n+ \"\"\"\n if unit not in [\"s\", \"ms\", \"us\", \"ns\"]:\n raise ValueError(\"Supported units are 's', 'ms', 'us', 'ns'\")\n \ndiff --git a/pandas/core/indexes/datetimelike.py b/pandas/core/indexes/datetimelike.py\nindex 8242dc49e6e0d..efaf1945c8534 100644\n--- a/pandas/core/indexes/datetimelike.py\n+++ b/pandas/core/indexes/datetimelike.py\n@@ -94,6 +94,32 @@ def mean(self, *, skipna: bool = True, axis: int | None = 0):\n \n @property\n def freq(self) -> BaseOffset | None:\n+ \"\"\"\n+ Return the frequency object if it is set, otherwise None.\n+\n+ To learn more about the frequency strings, please see\n+ :ref:`this link<timeseries.offset_aliases>`.\n+\n+ See Also\n+ --------\n+ DatetimeIndex.freq : Return the frequency object if it is set, otherwise None.\n+ PeriodIndex.freq : Return the frequency object if it is set, otherwise None.\n+\n+ Examples\n+ --------\n+ >>> datetimeindex = pd.date_range(\n+ ... \"2022-02-22 02:22:22\", periods=10, tz=\"America/Chicago\", freq=\"h\"\n+ ... )\n+ >>> datetimeindex\n+ DatetimeIndex(['2022-02-22 02:22:22-06:00', '2022-02-22 03:22:22-06:00',\n+ '2022-02-22 04:22:22-06:00', '2022-02-22 05:22:22-06:00',\n+ '2022-02-22 06:22:22-06:00', '2022-02-22 07:22:22-06:00',\n+ '2022-02-22 08:22:22-06:00', '2022-02-22 09:22:22-06:00',\n+ '2022-02-22 10:22:22-06:00', '2022-02-22 11:22:22-06:00'],\n+ dtype='datetime64[ns, America/Chicago]', freq='h')\n+ >>> datetimeindex.freq\n+ <Hour>\n+ \"\"\"\n return self._data.freq\n \n @freq.setter\n"},"body":{"kind":"string","value":"All GL08 Errors resolved in the following cases:\r\n\r\n1. scripts/validate_docstrings.py --format=actions --errors=GL08 pandas.DatetimeIndex.as_unit\r\n2. scripts/validate_docstrings.py --format=actions --errors=GL08 pandas.DatetimeIndex.freq\r\n\r\n_Note: [6232a2e](https://github.com/pandas-dev/pandas/pull/57562/commits/6232a2ed2590fb8d8b43658adc009688cb30dce2) commit message was a typo, this commit is for GL08 errors_\r\n\r\n- [x] xref https://github.com/pandas-dev/pandas/issues/57443\r\n- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57562"},"created_at":{"kind":"string","value":"2024-02-22T06:32:35Z"},"closed_at":{"kind":"string","value":"2024-02-26T18:12:56Z"},"merged_at":{"kind":"string","value":"2024-02-26T18:12:56Z"},"updated_at":{"kind":"string","value":"2024-02-26T18:24:00Z"}}},{"rowIdx":890,"cells":{"title":{"kind":"string","value":"DOC: fixing PR01 errors for pandas.Categorical and pandas.Categorical.__array__"},"diff":{"kind":"string","value":"diff --git a/ci/code_checks.sh b/ci/code_checks.sh\nindex 6469f39e7c332..f1e7f6d477906 100755\n--- a/ci/code_checks.sh\n+++ b/ci/code_checks.sh\n@@ -1458,8 +1458,6 @@ if [[ -z \"$CHECK\" || \"$CHECK\" == \"docstrings\" ]]; then\n \n MSG='Partially validate docstrings (PR01)' ; echo $MSG\n $BASE_DIR/scripts/validate_docstrings.py --format=actions --errors=PR01 --ignore_functions \\\n- pandas.Categorical\\\n- pandas.Categorical.__array__\\\n pandas.CategoricalIndex.equals\\\n pandas.CategoricalIndex.map\\\n pandas.DataFrame.at_time\\\ndiff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py\nindex d1dba024e85c5..886fe4594c17b 100644\n--- a/pandas/core/arrays/categorical.py\n+++ b/pandas/core/arrays/categorical.py\n@@ -276,6 +276,11 @@ class Categorical(NDArrayBackedExtensionArray, PandasObject, ObjectStringArrayMi\n provided).\n dtype : CategoricalDtype\n An instance of ``CategoricalDtype`` to use for this categorical.\n+ fastpath : bool\n+ The 'fastpath' keyword in Categorical is deprecated and will be\n+ removed in a future version. Use Categorical.from_codes instead.\n+ copy : bool, default True\n+ Whether to copy if the codes are unchanged.\n \n Attributes\n ----------\n@@ -1657,6 +1662,11 @@ def __array__(self, dtype: NpDtype | None = None) -> np.ndarray:\n \"\"\"\n The numpy array interface.\n \n+ Parameters\n+ ----------\n+ dtype : np.dtype or None\n+ Specifies the the dtype for the array.\n+\n Returns\n -------\n numpy.array\n"},"body":{"kind":"string","value":"All PR01 Errors resolved in the following cases:\r\n\r\n1. scripts/validate_docstrings.py --format=actions --errors=PR01 pandas.Categorical\r\n2. scripts/validate_docstrings.py --format=actions --errors=PR01 pandas.Categorical.__array__\r\n\r\n- [x] xref https://github.com/pandas-dev/pandas/issues/57438\r\n- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57561"},"created_at":{"kind":"string","value":"2024-02-22T05:43:38Z"},"closed_at":{"kind":"string","value":"2024-02-23T17:13:26Z"},"merged_at":{"kind":"string","value":"2024-02-23T17:13:26Z"},"updated_at":{"kind":"string","value":"2024-02-23T17:14:24Z"}}},{"rowIdx":891,"cells":{"title":{"kind":"string","value":"PERF: Switch conditions in RangeIndex._shallow_copy"},"diff":{"kind":"string","value":"diff --git a/pandas/core/indexes/range.py b/pandas/core/indexes/range.py\nindex 8552839b12d18..8a2e3fbf500a4 100644\n--- a/pandas/core/indexes/range.py\n+++ b/pandas/core/indexes/range.py\n@@ -474,8 +474,9 @@ def _shallow_copy(self, values, name: Hashable = no_default):\n diff = values[1] - values[0]\n if diff != 0:\n maybe_range_indexer, remainder = np.divmod(values - values[0], diff)\n- if not remainder.any() and lib.is_range_indexer(\n- maybe_range_indexer, len(maybe_range_indexer)\n+ if (\n+ lib.is_range_indexer(maybe_range_indexer, len(maybe_range_indexer))\n+ and not remainder.any()\n ):\n new_range = range(values[0], values[-1] + diff, diff)\n return type(self)._simple_new(new_range, name=name)\n"},"body":{"kind":"string","value":"xref https://github.com/pandas-dev/pandas/pull/57534#issuecomment-1957832841\r\n\r\n`is_range_indexer` lets us short circuit unlike checking the remainder\r\n\r\n```python\r\nIn [1]: from pandas import *; import numpy as np\r\n ...: np.random.seed(123)\r\n ...: size = 1_000_000\r\n ...: ngroups = 1000\r\n ...: data = Series(np.random.randint(0, ngroups, size=size))\r\n+ /opt/miniconda3/envs/pandas-dev/bin/ninja\r\n[1/1] Generating write_version_file with a custom command\r\n\r\nIn [2]: %timeit data.groupby(data).groups\r\n16.8 ms ± 183 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) # PR\r\n\r\nIn [3]: %timeit data.groupby(data).groups\r\n17.6 ms ± 114 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) # main\r\n```"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57560"},"created_at":{"kind":"string","value":"2024-02-21T23:28:26Z"},"closed_at":{"kind":"string","value":"2024-02-22T14:39:55Z"},"merged_at":{"kind":"string","value":"2024-02-22T14:39:55Z"},"updated_at":{"kind":"string","value":"2024-02-22T16:35:31Z"}}},{"rowIdx":892,"cells":{"title":{"kind":"string","value":"CLN: correct file names in a comment in _optional.py"},"diff":{"kind":"string","value":"diff --git a/pandas/compat/_optional.py b/pandas/compat/_optional.py\nindex ddd9b591d3e83..26beca6a0e4b6 100644\n--- a/pandas/compat/_optional.py\n+++ b/pandas/compat/_optional.py\n@@ -16,7 +16,8 @@\n if TYPE_CHECKING:\n import types\n \n-# Update install.rst & setup.cfg when updating versions!\n+# Update install.rst, actions-39-minimum_versions.yaml,\n+# deps_minimum.toml & pyproject.toml when updating versions!\n \n VERSIONS = {\n \"adbc-driver-postgresql\": \"0.8.0\",\n"},"body":{"kind":"string","value":"corrected file names in a comment in `pandas/compat/_optional.py`"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57558"},"created_at":{"kind":"string","value":"2024-02-21T22:49:11Z"},"closed_at":{"kind":"string","value":"2024-02-21T23:50:56Z"},"merged_at":{"kind":"string","value":"2024-02-21T23:50:56Z"},"updated_at":{"kind":"string","value":"2024-02-21T23:51:02Z"}}},{"rowIdx":893,"cells":{"title":{"kind":"string","value":"Backport PR #57551: BLD: Add pyarrow extra for pip installation"},"diff":{"kind":"string","value":"diff --git a/.github/workflows/package-checks.yml b/.github/workflows/package-checks.yml\nindex d59ddf272f705..7c1da5678a2aa 100644\n--- a/.github/workflows/package-checks.yml\n+++ b/.github/workflows/package-checks.yml\n@@ -24,7 +24,7 @@ jobs:\n runs-on: ubuntu-22.04\n strategy:\n matrix:\n- extra: [\"test\", \"performance\", \"computation\", \"fss\", \"aws\", \"gcp\", \"excel\", \"parquet\", \"feather\", \"hdf5\", \"spss\", \"postgresql\", \"mysql\", \"sql-other\", \"html\", \"xml\", \"plot\", \"output-formatting\", \"clipboard\", \"compression\", \"consortium-standard\", \"all\"]\n+ extra: [\"test\", \"pyarrow\", \"performance\", \"computation\", \"fss\", \"aws\", \"gcp\", \"excel\", \"parquet\", \"feather\", \"hdf5\", \"spss\", \"postgresql\", \"mysql\", \"sql-other\", \"html\", \"xml\", \"plot\", \"output-formatting\", \"clipboard\", \"compression\", \"consortium-standard\", \"all\"]\n fail-fast: false\n name: Install Extras - ${{ matrix.extra }}\n concurrency:\ndiff --git a/doc/source/whatsnew/v2.2.1.rst b/doc/source/whatsnew/v2.2.1.rst\nindex d81032fafa730..e381f9df16383 100644\n--- a/doc/source/whatsnew/v2.2.1.rst\n+++ b/doc/source/whatsnew/v2.2.1.rst\n@@ -9,6 +9,12 @@ including other versions of pandas.\n {{ header }}\n \n .. ---------------------------------------------------------------------------\n+.. _whatsnew_221.enhancements:\n+\n+Enhancements\n+~~~~~~~~~~~~\n+- Added ``pyarrow`` pip extra so users can install pandas and pyarrow with pip with ``pip install pandas[pyarrow]`` (:issue:`54466`)\n+\n .. _whatsnew_221.regressions:\n \n Fixed regressions\ndiff --git a/pyproject.toml b/pyproject.toml\nindex 8c9a79aa2b059..c225ed80dcb10 100644\n--- a/pyproject.toml\n+++ b/pyproject.toml\n@@ -64,6 +64,7 @@ matplotlib = \"pandas:plotting._matplotlib\"\n \n [project.optional-dependencies]\n test = ['hypothesis>=6.46.1', 'pytest>=7.3.2', 'pytest-xdist>=2.2.0']\n+pyarrow = ['pyarrow>=10.0.1']\n performance = ['bottleneck>=1.3.6', 'numba>=0.56.4', 'numexpr>=2.8.4']\n computation = ['scipy>=1.10.0', 'xarray>=2022.12.0']\n fss = ['fsspec>=2022.11.0']\n"},"body":{"kind":"null"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57557"},"created_at":{"kind":"string","value":"2024-02-21T22:28:47Z"},"closed_at":{"kind":"string","value":"2024-02-21T23:49:28Z"},"merged_at":{"kind":"string","value":"2024-02-21T23:49:28Z"},"updated_at":{"kind":"string","value":"2024-02-21T23:49:31Z"}}},{"rowIdx":894,"cells":{"title":{"kind":"string","value":"Remove PyArrow deprecation warning"},"diff":{"kind":"string","value":"diff --git a/.github/workflows/unit-tests.yml b/.github/workflows/unit-tests.yml\nindex 533b81013a264..855973a22886a 100644\n--- a/.github/workflows/unit-tests.yml\n+++ b/.github/workflows/unit-tests.yml\n@@ -64,10 +64,7 @@ jobs:\n - name: \"Numpy Dev\"\n env_file: actions-311-numpydev.yaml\n pattern: \"not slow and not network and not single_cpu\"\n- # Currently restricted the warnings that error to Deprecation Warnings from numpy\n- # done since pyarrow isn't compatible with numpydev always\n- # TODO: work with pyarrow to revert this?\n- test_args: \"-W error::DeprecationWarning:numpy -W error::FutureWarning:numpy\"\n+ test_args: \"-W error::DeprecationWarning -W error::FutureWarning\"\n - name: \"Pyarrow Nightly\"\n env_file: actions-311-pyarrownightly.yaml\n pattern: \"not slow and not network and not single_cpu\"\ndiff --git a/doc/source/whatsnew/v2.2.1.rst b/doc/source/whatsnew/v2.2.1.rst\nindex ab62a7c7598d5..b2a3869116799 100644\n--- a/doc/source/whatsnew/v2.2.1.rst\n+++ b/doc/source/whatsnew/v2.2.1.rst\n@@ -60,6 +60,16 @@ Bug fixes\n \n Other\n ~~~~~\n+\n+.. note::\n+\n+ The ``DeprecationWarning`` that was raised when pandas was imported without PyArrow being\n+ installed has been removed. This decision was made because the warning was too noisy for too\n+ many users and a lot of feedback was collected about the decision to make PyArrow a required\n+ dependency. Pandas is currently considering the decision whether or not PyArrow should be added\n+ as a hard dependency in 3.0. Interested users can follow the discussion\n+ `here <https://github.com/pandas-dev/pandas/issues/57073>`_.\n+\n - Added the argument ``skipna`` to :meth:`DataFrameGroupBy.first`, :meth:`DataFrameGroupBy.last`, :meth:`SeriesGroupBy.first`, and :meth:`SeriesGroupBy.last`; achieving ``skipna=False`` used to be available via :meth:`DataFrameGroupBy.nth`, but the behavior was changed in pandas 2.0.0 (:issue:`57019`)\n - Added the argument ``skipna`` to :meth:`Resampler.first`, :meth:`Resampler.last` (:issue:`57019`)\n \ndiff --git a/pandas/__init__.py b/pandas/__init__.py\nindex 7b5b00d92db1f..f7ae91dd847f7 100644\n--- a/pandas/__init__.py\n+++ b/pandas/__init__.py\n@@ -1,7 +1,5 @@\n from __future__ import annotations\n \n-import warnings\n-\n __docformat__ = \"restructuredtext\"\n \n # Let users know if they're missing any of our hard dependencies\n@@ -190,36 +188,6 @@\n __git_version__ = v.get(\"full-revisionid\")\n del get_versions, v\n \n-# DeprecationWarning for missing pyarrow\n-from pandas.compat.pyarrow import pa_version_under10p1, pa_not_found\n-\n-if pa_version_under10p1:\n- # pyarrow is either too old or nonexistent, warn\n- from pandas.compat._optional import VERSIONS\n-\n- if pa_not_found:\n- pa_msg = \"was not found to be installed on your system.\"\n- else:\n- pa_msg = (\n- f\"was too old on your system - pyarrow {VERSIONS['pyarrow']} \"\n- \"is the current minimum supported version as of this release.\"\n- )\n-\n- warnings.warn(\n- f\"\"\"\n-Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),\n-(to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)\n-but {pa_msg}\n-If this would cause problems for you,\n-please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466\n- \"\"\", # noqa: E501\n- DeprecationWarning,\n- stacklevel=2,\n- )\n- del VERSIONS, pa_msg\n-\n-# Delete all unnecessary imported modules\n-del pa_version_under10p1, pa_not_found, warnings\n \n # module level doc-string\n __doc__ = \"\"\"\ndiff --git a/pandas/compat/pyarrow.py b/pandas/compat/pyarrow.py\nindex 2e151123ef2c9..beb4814914101 100644\n--- a/pandas/compat/pyarrow.py\n+++ b/pandas/compat/pyarrow.py\n@@ -8,7 +8,6 @@\n import pyarrow as pa\n \n _palv = Version(Version(pa.__version__).base_version)\n- pa_not_found = False\n pa_version_under10p1 = _palv < Version(\"10.0.1\")\n pa_version_under11p0 = _palv < Version(\"11.0.0\")\n pa_version_under12p0 = _palv < Version(\"12.0.0\")\n@@ -17,7 +16,6 @@\n pa_version_under14p1 = _palv < Version(\"14.0.1\")\n pa_version_under15p0 = _palv < Version(\"15.0.0\")\n except ImportError:\n- pa_not_found = True\n pa_version_under10p1 = True\n pa_version_under11p0 = True\n pa_version_under12p0 = True\ndiff --git a/pandas/tests/test_common.py b/pandas/tests/test_common.py\nindex 94d7d5fead622..9c2b9a76bbb83 100644\n--- a/pandas/tests/test_common.py\n+++ b/pandas/tests/test_common.py\n@@ -8,8 +8,6 @@\n import numpy as np\n import pytest\n \n-import pandas.util._test_decorators as td\n-\n import pandas as pd\n from pandas import Series\n import pandas._testing as tm\n@@ -255,26 +253,3 @@ def test_bz2_missing_import():\n code = textwrap.dedent(code)\n call = [sys.executable, \"-c\", code]\n subprocess.check_output(call)\n-\n-\n-@td.skip_if_installed(\"pyarrow\")\n-@pytest.mark.parametrize(\"module\", [\"pandas\", \"pandas.arrays\"])\n-def test_pyarrow_missing_warn(module):\n- # GH56896\n- response = subprocess.run(\n- [sys.executable, \"-c\", f\"import {module}\"],\n- capture_output=True,\n- check=True,\n- )\n- msg = \"\"\"\n-Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),\n-(to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)\n-but was not found to be installed on your system.\n-If this would cause problems for you,\n-please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466\n-\"\"\" # noqa: E501\n- stderr_msg = response.stderr.decode(\"utf-8\")\n- # Split by \\n to avoid \\r\\n vs \\n differences on Windows/Unix\n- # https://stackoverflow.com/questions/11989501/replacing-r-n-with-n\n- stderr_msg = \"\\n\".join(stderr_msg.splitlines())\n- assert msg in stderr_msg\n"},"body":{"kind":"string","value":"- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)\r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57556"},"created_at":{"kind":"string","value":"2024-02-21T22:21:14Z"},"closed_at":{"kind":"string","value":"2024-02-22T17:43:15Z"},"merged_at":{"kind":"string","value":"2024-02-22T17:43:15Z"},"updated_at":{"kind":"string","value":"2024-02-22T17:48:22Z"}}},{"rowIdx":895,"cells":{"title":{"kind":"string","value":"CLN: Remove pickle support pre-pandas 1.0"},"diff":{"kind":"string","value":"diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst\nindex 3fdb4af52a8c0..575113434b531 100644\n--- a/doc/source/whatsnew/v3.0.0.rst\n+++ b/doc/source/whatsnew/v3.0.0.rst\n@@ -94,7 +94,7 @@ Other API changes\n - Made ``dtype`` a required argument in :meth:`ExtensionArray._from_sequence_of_strings` (:issue:`56519`)\n - Updated :meth:`DataFrame.to_excel` so that the output spreadsheet has no styling. Custom styling can still be done using :meth:`Styler.to_excel` (:issue:`54154`)\n - pickle and HDF (``.h5``) files created with Python 2 are no longer explicitly supported (:issue:`57387`)\n--\n+- pickled objects from pandas version less than ``1.0.0`` are no longer supported (:issue:`57155`)\n \n .. ---------------------------------------------------------------------------\n .. _whatsnew_300.deprecations:\ndiff --git a/pandas/_libs/tslibs/nattype.pyx b/pandas/_libs/tslibs/nattype.pyx\nindex cd5e6e521b79f..7a08e4ad4b260 100644\n--- a/pandas/_libs/tslibs/nattype.pyx\n+++ b/pandas/_libs/tslibs/nattype.pyx\n@@ -76,7 +76,7 @@ cdef _nat_rdivide_op(self, other):\n return NotImplemented\n \n \n-def __nat_unpickle(*args):\n+def _nat_unpickle(*args):\n # return constant defined in the module\n return c_NaT\n \n@@ -360,7 +360,7 @@ class NaTType(_NaT):\n return self.__reduce__()\n \n def __reduce__(self):\n- return (__nat_unpickle, (None, ))\n+ return (_nat_unpickle, (None, ))\n \n def __rtruediv__(self, other):\n return _nat_rdivide_op(self, other)\ndiff --git a/pandas/compat/pickle_compat.py b/pandas/compat/pickle_compat.py\nindex ff589ebba4cf6..f4698bee5cb02 100644\n--- a/pandas/compat/pickle_compat.py\n+++ b/pandas/compat/pickle_compat.py\n@@ -1,12 +1,11 @@\n \"\"\"\n-Support pre-0.12 series pickle compatibility.\n+Pickle compatibility to pandas version 1.0\n \"\"\"\n from __future__ import annotations\n \n import contextlib\n-import copy\n import io\n-import pickle as pkl\n+import pickle\n from typing import (\n TYPE_CHECKING,\n Any,\n@@ -17,7 +16,6 @@\n from pandas._libs.arrays import NDArrayBacked\n from pandas._libs.tslibs import BaseOffset\n \n-from pandas import Index\n from pandas.core.arrays import (\n DatetimeArray,\n PeriodArray,\n@@ -29,111 +27,20 @@\n from collections.abc import Generator\n \n \n-def load_reduce(self) -> None:\n- stack = self.stack\n- args = stack.pop()\n- func = stack[-1]\n-\n- try:\n- stack[-1] = func(*args)\n- return\n- except TypeError as err:\n- # If we have a deprecated function,\n- # try to replace and try again.\n-\n- msg = \"_reconstruct: First argument must be a sub-type of ndarray\"\n-\n- if msg in str(err):\n- try:\n- cls = args[0]\n- stack[-1] = object.__new__(cls)\n- return\n- except TypeError:\n- pass\n- elif args and isinstance(args[0], type) and issubclass(args[0], BaseOffset):\n- # TypeError: object.__new__(Day) is not safe, use Day.__new__()\n- cls = args[0]\n- stack[-1] = cls.__new__(*args)\n- return\n- elif args and issubclass(args[0], PeriodArray):\n- cls = args[0]\n- stack[-1] = NDArrayBacked.__new__(*args)\n- return\n-\n- raise\n-\n-\n # If classes are moved, provide compat here.\n _class_locations_map = {\n- (\"pandas.core.sparse.array\", \"SparseArray\"): (\"pandas.core.arrays\", \"SparseArray\"),\n- # 15477\n- (\"pandas.core.base\", \"FrozenNDArray\"): (\"numpy\", \"ndarray\"),\n # Re-routing unpickle block logic to go through _unpickle_block instead\n # for pandas <= 1.3.5\n (\"pandas.core.internals.blocks\", \"new_block\"): (\n \"pandas._libs.internals\",\n \"_unpickle_block\",\n ),\n- (\"pandas.core.indexes.frozen\", \"FrozenNDArray\"): (\"numpy\", \"ndarray\"),\n- (\"pandas.core.base\", \"FrozenList\"): (\"pandas.core.indexes.frozen\", \"FrozenList\"),\n- # 10890\n- (\"pandas.core.series\", \"TimeSeries\"): (\"pandas.core.series\", \"Series\"),\n- (\"pandas.sparse.series\", \"SparseTimeSeries\"): (\n- \"pandas.core.sparse.series\",\n- \"SparseSeries\",\n- ),\n- # 12588, extensions moving\n- (\"pandas._sparse\", \"BlockIndex\"): (\"pandas._libs.sparse\", \"BlockIndex\"),\n- (\"pandas.tslib\", \"Timestamp\"): (\"pandas._libs.tslib\", \"Timestamp\"),\n- # 18543 moving period\n- (\"pandas._period\", \"Period\"): (\"pandas._libs.tslibs.period\", \"Period\"),\n- (\"pandas._libs.period\", \"Period\"): (\"pandas._libs.tslibs.period\", \"Period\"),\n- # 18014 moved __nat_unpickle from _libs.tslib-->_libs.tslibs.nattype\n- (\"pandas.tslib\", \"__nat_unpickle\"): (\n- \"pandas._libs.tslibs.nattype\",\n- \"__nat_unpickle\",\n- ),\n- (\"pandas._libs.tslib\", \"__nat_unpickle\"): (\n+ # Avoid Cython's warning \"contradiction to to Python 'class private name' rules\"\n+ (\"pandas._libs.tslibs.nattype\", \"__nat_unpickle\"): (\n \"pandas._libs.tslibs.nattype\",\n- \"__nat_unpickle\",\n- ),\n- # 15998 top-level dirs moving\n- (\"pandas.sparse.array\", \"SparseArray\"): (\n- \"pandas.core.arrays.sparse\",\n- \"SparseArray\",\n- ),\n- (\"pandas.indexes.base\", \"_new_Index\"): (\"pandas.core.indexes.base\", \"_new_Index\"),\n- (\"pandas.indexes.base\", \"Index\"): (\"pandas.core.indexes.base\", \"Index\"),\n- (\"pandas.indexes.numeric\", \"Int64Index\"): (\n- \"pandas.core.indexes.base\",\n- \"Index\", # updated in 50775\n- ),\n- (\"pandas.indexes.range\", \"RangeIndex\"): (\"pandas.core.indexes.range\", \"RangeIndex\"),\n- (\"pandas.indexes.multi\", \"MultiIndex\"): (\"pandas.core.indexes.multi\", \"MultiIndex\"),\n- (\"pandas.tseries.index\", \"_new_DatetimeIndex\"): (\n- \"pandas.core.indexes.datetimes\",\n- \"_new_DatetimeIndex\",\n- ),\n- (\"pandas.tseries.index\", \"DatetimeIndex\"): (\n- \"pandas.core.indexes.datetimes\",\n- \"DatetimeIndex\",\n+ \"_nat_unpickle\",\n ),\n- (\"pandas.tseries.period\", \"PeriodIndex\"): (\n- \"pandas.core.indexes.period\",\n- \"PeriodIndex\",\n- ),\n- # 19269, arrays moving\n- (\"pandas.core.categorical\", \"Categorical\"): (\"pandas.core.arrays\", \"Categorical\"),\n- # 19939, add timedeltaindex, float64index compat from 15998 move\n- (\"pandas.tseries.tdi\", \"TimedeltaIndex\"): (\n- \"pandas.core.indexes.timedeltas\",\n- \"TimedeltaIndex\",\n- ),\n- (\"pandas.indexes.numeric\", \"Float64Index\"): (\n- \"pandas.core.indexes.base\",\n- \"Index\", # updated in 50775\n- ),\n- # 50775, remove Int64Index, UInt64Index & Float64Index from codabase\n+ # 50775, remove Int64Index, UInt64Index & Float64Index from codebase\n (\"pandas.core.indexes.numeric\", \"Int64Index\"): (\n \"pandas.core.indexes.base\",\n \"Index\",\n@@ -155,85 +62,55 @@ def load_reduce(self) -> None:\n \n # our Unpickler sub-class to override methods and some dispatcher\n # functions for compat and uses a non-public class of the pickle module.\n-\n-\n-class Unpickler(pkl._Unpickler):\n+class Unpickler(pickle._Unpickler):\n def find_class(self, module, name):\n- # override superclass\n key = (module, name)\n module, name = _class_locations_map.get(key, key)\n return super().find_class(module, name)\n \n+ dispatch = pickle._Unpickler.dispatch.copy()\n \n-Unpickler.dispatch = copy.copy(Unpickler.dispatch)\n-Unpickler.dispatch[pkl.REDUCE[0]] = load_reduce\n-\n-\n-def load_newobj(self) -> None:\n- args = self.stack.pop()\n- cls = self.stack[-1]\n-\n- # compat\n- if issubclass(cls, Index):\n- obj = object.__new__(cls)\n- elif issubclass(cls, DatetimeArray) and not args:\n- arr = np.array([], dtype=\"M8[ns]\")\n- obj = cls.__new__(cls, arr, arr.dtype)\n- elif issubclass(cls, TimedeltaArray) and not args:\n- arr = np.array([], dtype=\"m8[ns]\")\n- obj = cls.__new__(cls, arr, arr.dtype)\n- elif cls is BlockManager and not args:\n- obj = cls.__new__(cls, (), [], False)\n- else:\n- obj = cls.__new__(cls, *args)\n-\n- self.stack[-1] = obj\n-\n-\n-Unpickler.dispatch[pkl.NEWOBJ[0]] = load_newobj\n-\n-\n-def load_newobj_ex(self) -> None:\n- kwargs = self.stack.pop()\n- args = self.stack.pop()\n- cls = self.stack.pop()\n-\n- # compat\n- if issubclass(cls, Index):\n- obj = object.__new__(cls)\n- else:\n- obj = cls.__new__(cls, *args, **kwargs)\n- self.append(obj)\n-\n+ def load_reduce(self) -> None:\n+ stack = self.stack # type: ignore[attr-defined]\n+ args = stack.pop()\n+ func = stack[-1]\n \n-try:\n- Unpickler.dispatch[pkl.NEWOBJ_EX[0]] = load_newobj_ex\n-except (AttributeError, KeyError):\n- pass\n-\n-\n-def load(fh, encoding: str | None = None, is_verbose: bool = False) -> Any:\n- \"\"\"\n- Load a pickle, with a provided encoding,\n-\n- Parameters\n- ----------\n- fh : a filelike object\n- encoding : an optional encoding\n- is_verbose : show exception output\n- \"\"\"\n- try:\n- fh.seek(0)\n- if encoding is not None:\n- up = Unpickler(fh, encoding=encoding)\n+ try:\n+ stack[-1] = func(*args)\n+ except TypeError:\n+ # If we have a deprecated function,\n+ # try to replace and try again.\n+ if args and isinstance(args[0], type) and issubclass(args[0], BaseOffset):\n+ # TypeError: object.__new__(Day) is not safe, use Day.__new__()\n+ cls = args[0]\n+ stack[-1] = cls.__new__(*args)\n+ return\n+ elif args and issubclass(args[0], PeriodArray):\n+ cls = args[0]\n+ stack[-1] = NDArrayBacked.__new__(*args)\n+ return\n+ raise\n+\n+ dispatch[pickle.REDUCE[0]] = load_reduce # type: ignore[assignment]\n+\n+ def load_newobj(self) -> None:\n+ args = self.stack.pop() # type: ignore[attr-defined]\n+ cls = self.stack.pop() # type: ignore[attr-defined]\n+\n+ # compat\n+ if issubclass(cls, DatetimeArray) and not args:\n+ arr = np.array([], dtype=\"M8[ns]\")\n+ obj = cls.__new__(cls, arr, arr.dtype)\n+ elif issubclass(cls, TimedeltaArray) and not args:\n+ arr = np.array([], dtype=\"m8[ns]\")\n+ obj = cls.__new__(cls, arr, arr.dtype)\n+ elif cls is BlockManager and not args:\n+ obj = cls.__new__(cls, (), [], False)\n else:\n- up = Unpickler(fh)\n- # \"Unpickler\" has no attribute \"is_verbose\" [attr-defined]\n- up.is_verbose = is_verbose # type: ignore[attr-defined]\n+ obj = cls.__new__(cls, *args)\n+ self.append(obj) # type: ignore[attr-defined]\n \n- return up.load()\n- except (ValueError, TypeError):\n- raise\n+ dispatch[pickle.NEWOBJ[0]] = load_newobj # type: ignore[assignment]\n \n \n def loads(\n@@ -257,9 +134,9 @@ def patch_pickle() -> Generator[None, None, None]:\n \"\"\"\n Temporarily patch pickle to use our unpickler.\n \"\"\"\n- orig_loads = pkl.loads\n+ orig_loads = pickle.loads\n try:\n- setattr(pkl, \"loads\", loads)\n+ setattr(pickle, \"loads\", loads)\n yield\n finally:\n- setattr(pkl, \"loads\", orig_loads)\n+ setattr(pickle, \"loads\", orig_loads)\ndiff --git a/pandas/io/pickle.py b/pandas/io/pickle.py\nindex c565544075ecf..d37c77182d3fe 100644\n--- a/pandas/io/pickle.py\n+++ b/pandas/io/pickle.py\n@@ -8,7 +8,7 @@\n )\n import warnings\n \n-from pandas.compat import pickle_compat as pc\n+from pandas.compat import pickle_compat\n from pandas.util._decorators import doc\n \n from pandas.core.shared_docs import _shared_docs\n@@ -158,7 +158,7 @@ def read_pickle(\n \n Notes\n -----\n- read_pickle is only guaranteed to be backwards compatible to pandas 0.20.3\n+ read_pickle is only guaranteed to be backwards compatible to pandas 1.0\n provided the object was serialized with to_pickle.\n \n Examples\n@@ -195,7 +195,6 @@ def read_pickle(\n ) as handles:\n # 1) try standard library Pickle\n # 2) try pickle_compat (older pandas version) to handle subclass changes\n-\n try:\n with warnings.catch_warnings(record=True):\n # We want to silence any warnings about, e.g. moved modules.\n@@ -204,5 +203,6 @@ def read_pickle(\n except excs_to_catch:\n # e.g.\n # \"No module named 'pandas.core.sparse.series'\"\n- # \"Can't get attribute '__nat_unpickle' on <module 'pandas._libs.tslib\"\n- return pc.load(handles.handle, encoding=None)\n+ # \"Can't get attribute '_nat_unpickle' on <module 'pandas._libs.tslib\"\n+ handles.handle.seek(0)\n+ return pickle_compat.Unpickler(handles.handle).load()\n"},"body":{"kind":"string","value":"For a major pandas 3.0 release, I think it's reasonable that pickle support for pre-pandas 1.0 can be removed by now.\r\n\r\nRetry at https://github.com/pandas-dev/pandas/pull/57155\r\n"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57555"},"created_at":{"kind":"string","value":"2024-02-21T21:09:59Z"},"closed_at":{"kind":"string","value":"2024-02-22T22:43:58Z"},"merged_at":{"kind":"string","value":"2024-02-22T22:43:58Z"},"updated_at":{"kind":"string","value":"2024-02-22T22:44:01Z"}}},{"rowIdx":896,"cells":{"title":{"kind":"string","value":"Roadmap: remove ArrayManager"},"diff":{"kind":"string","value":"diff --git a/web/pandas/about/roadmap.md b/web/pandas/about/roadmap.md\nindex 4c12e3e786a32..aba95ec2c03fc 100644\n--- a/web/pandas/about/roadmap.md\n+++ b/web/pandas/about/roadmap.md\n@@ -90,33 +90,6 @@ data types within pandas. This will let us take advantage of its I/O\n capabilities and provide for better interoperability with other\n languages and libraries using Arrow.\n \n-### Block manager rewrite\n-\n-We'd like to replace pandas current internal data structures (a\n-collection of 1 or 2-D arrays) with a simpler collection of 1-D arrays.\n-\n-Pandas internal data model is quite complex. A DataFrame is made up of\n-one or more 2-dimensional \"blocks\", with one or more blocks per dtype.\n-This collection of 2-D arrays is managed by the BlockManager.\n-\n-The primary benefit of the BlockManager is improved performance on\n-certain operations (construction from a 2D array, binary operations,\n-reductions across the columns), especially for wide DataFrames. However,\n-the BlockManager substantially increases the complexity and maintenance\n-burden of pandas.\n-\n-By replacing the BlockManager we hope to achieve\n-\n-- Substantially simpler code\n-- Easier extensibility with new logical types\n-- Better user control over memory use and layout\n-- Improved micro-performance\n-- Option to provide a C / Cython API to pandas' internals\n-\n-See [these design\n-documents](https://dev.pandas.io/pandas2/internal-architecture.html#removal-of-blockmanager-new-dataframe-internals)\n-for more.\n-\n ### Decoupling of indexing and internals\n \n The code for getting and setting values in pandas' data structures\n"},"body":{"kind":"string","value":"- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)\r\n- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n\r\nThe deprecation of ArrayManager was recently enforced; this is no longer a Roadmap item."},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57554"},"created_at":{"kind":"string","value":"2024-02-21T20:29:46Z"},"closed_at":{"kind":"string","value":"2024-02-21T21:13:55Z"},"merged_at":{"kind":"string","value":"2024-02-21T21:13:55Z"},"updated_at":{"kind":"string","value":"2024-02-21T22:20:48Z"}}},{"rowIdx":897,"cells":{"title":{"kind":"string","value":"API: avoid passing Manager to subclass __init__"},"diff":{"kind":"string","value":"diff --git a/pandas/core/frame.py b/pandas/core/frame.py\nindex 8fd0cd8c66e3c..1be72c60783ec 100644\n--- a/pandas/core/frame.py\n+++ b/pandas/core/frame.py\n@@ -651,25 +651,36 @@ def _constructor(self) -> type[DataFrame]:\n return DataFrame\n \n def _constructor_from_mgr(self, mgr, axes) -> DataFrame:\n- if self._constructor is DataFrame:\n- # we are pandas.DataFrame (or a subclass that doesn't override _constructor)\n- return DataFrame._from_mgr(mgr, axes=axes)\n- else:\n- assert axes is mgr.axes\n+ df = DataFrame._from_mgr(mgr, axes=axes)\n+\n+ if type(self) is DataFrame:\n+ # This would also work `if self._constructor is DataFrame`, but\n+ # this check is slightly faster, benefiting the most-common case.\n+ return df\n+\n+ elif type(self).__name__ == \"GeoDataFrame\":\n+ # Shim until geopandas can override their _constructor_from_mgr\n+ # bc they have different behavior for Managers than for DataFrames\n return self._constructor(mgr)\n \n- _constructor_sliced: Callable[..., Series] = Series\n+ # We assume that the subclass __init__ knows how to handle a\n+ # pd.DataFrame object.\n+ return self._constructor(df)\n \n- def _sliced_from_mgr(self, mgr, axes) -> Series:\n- return Series._from_mgr(mgr, axes)\n+ _constructor_sliced: Callable[..., Series] = Series\n \n def _constructor_sliced_from_mgr(self, mgr, axes) -> Series:\n- if self._constructor_sliced is Series:\n- ser = self._sliced_from_mgr(mgr, axes)\n- ser._name = None # caller is responsible for setting real name\n+ ser = Series._from_mgr(mgr, axes)\n+ ser._name = None # caller is responsible for setting real name\n+\n+ if type(self) is DataFrame:\n+ # This would also work `if self._constructor_sliced is Series`, but\n+ # this check is slightly faster, benefiting the most-common case.\n return ser\n- assert axes is mgr.axes\n- return self._constructor_sliced(mgr)\n+\n+ # We assume that the subclass __init__ knows how to handle a\n+ # pd.Series object.\n+ return self._constructor_sliced(ser)\n \n # ----------------------------------------------------------------------\n # Constructors\ndiff --git a/pandas/core/generic.py b/pandas/core/generic.py\nindex c9e6ffe1d7dc6..8d2fa91edc81c 100644\n--- a/pandas/core/generic.py\n+++ b/pandas/core/generic.py\n@@ -288,6 +288,7 @@ def _init_mgr(\n mgr = mgr.astype(dtype=dtype)\n return mgr\n \n+ @final\n @classmethod\n def _from_mgr(cls, mgr: Manager, axes: list[Index]) -> Self:\n \"\"\"\ndiff --git a/pandas/core/series.py b/pandas/core/series.py\nindex 08e56cb4925b3..9dad4191975fa 100644\n--- a/pandas/core/series.py\n+++ b/pandas/core/series.py\n@@ -576,14 +576,17 @@ def _constructor(self) -> type[Series]:\n return Series\n \n def _constructor_from_mgr(self, mgr, axes):\n- if self._constructor is Series:\n- # we are pandas.Series (or a subclass that doesn't override _constructor)\n- ser = Series._from_mgr(mgr, axes=axes)\n- ser._name = None # caller is responsible for setting real name\n+ ser = Series._from_mgr(mgr, axes=axes)\n+ ser._name = None # caller is responsible for setting real name\n+\n+ if type(self) is Series:\n+ # This would also work `if self._constructor is Series`, but\n+ # this check is slightly faster, benefiting the most-common case.\n return ser\n- else:\n- assert axes is mgr.axes\n- return self._constructor(mgr)\n+\n+ # We assume that the subclass __init__ knows how to handle a\n+ # pd.Series object.\n+ return self._constructor(ser)\n \n @property\n def _constructor_expanddim(self) -> Callable[..., DataFrame]:\n@@ -595,18 +598,19 @@ def _constructor_expanddim(self) -> Callable[..., DataFrame]:\n \n return DataFrame\n \n- def _expanddim_from_mgr(self, mgr, axes) -> DataFrame:\n+ def _constructor_expanddim_from_mgr(self, mgr, axes):\n from pandas.core.frame import DataFrame\n \n- return DataFrame._from_mgr(mgr, axes=mgr.axes)\n+ df = DataFrame._from_mgr(mgr, axes=mgr.axes)\n \n- def _constructor_expanddim_from_mgr(self, mgr, axes):\n- from pandas.core.frame import DataFrame\n+ if type(self) is Series:\n+ # This would also work `if self._constructor_expanddim is DataFrame`,\n+ # but this check is slightly faster, benefiting the most-common case.\n+ return df\n \n- if self._constructor_expanddim is DataFrame:\n- return self._expanddim_from_mgr(mgr, axes)\n- assert axes is mgr.axes\n- return self._constructor_expanddim(mgr)\n+ # We assume that the subclass __init__ knows how to handle a\n+ # pd.DataFrame object.\n+ return self._constructor_expanddim(df)\n \n # types\n @property\ndiff --git a/pandas/tests/frame/test_subclass.py b/pandas/tests/frame/test_subclass.py\nindex 316216e69a587..355953eac9d51 100644\n--- a/pandas/tests/frame/test_subclass.py\n+++ b/pandas/tests/frame/test_subclass.py\n@@ -16,6 +16,17 @@\n \n \n class TestDataFrameSubclassing:\n+ def test_no_warning_on_mgr(self):\n+ # GH#57032\n+ df = tm.SubclassedDataFrame(\n+ {\"X\": [1, 2, 3], \"Y\": [1, 2, 3]}, index=[\"a\", \"b\", \"c\"]\n+ )\n+ with tm.assert_produces_warning(None):\n+ # df.isna() goes through _constructor_from_mgr, which we want to\n+ # *not* pass a Manager do __init__\n+ df.isna()\n+ df[\"X\"].isna()\n+\n def test_frame_subclassing_and_slicing(self):\n # Subclass frame and ensure it returns the right class on slicing it\n # In reference to PR 9632\n"},"body":{"kind":"string","value":"- [x] closes #57032 (Replace xxxx with the GitHub issue number)\r\n- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature\r\n- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).\r\n- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.\r\n- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.\r\n\r\nMany subclasses have `__init__` methods that call `super().__init__`, which in the relevant cases with a Manager object is deprecated. The solution in this PR is to construct the pd.DataFrame/Series and pass that to the subclass's `_constructor`.\r\n\r\nThis removes _sliced_from_mgr and _expanddim_from_mgr, as they are not really necessary, simplifying things a bit. Also makes _from_mgr `@final`. Can separate these simplifications into their own PR on request. xref #56681.\r\n\r\nFor subclasses that currently have special handling for Manager objects in their `__init__`, they will need to move that special handling to the appropriate `_constructor(_foo)?_from_mgr` method. The only package I'm aware of that does this is geopandas, so this includes a shim special-casing GeoDataFrame intended to maintain the current behavior until they have time to move that logic. cc @jorisvandenbossche ATM the shim is only in _constructor_from_mgr, pls advise on whether something analogous is needed in constructor_sliced_from_mgr and _constructor_expanddim_from_mgr."},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57553"},"created_at":{"kind":"string","value":"2024-02-21T20:21:57Z"},"closed_at":{"kind":"string","value":"2024-03-26T01:40:18Z"},"merged_at":{"kind":"string","value":"2024-03-26T01:40:18Z"},"updated_at":{"kind":"string","value":"2024-04-10T12:08:36Z"}}},{"rowIdx":898,"cells":{"title":{"kind":"string","value":"Backport PR #57439 on branch 2.2.x (BUG: read_json returning Index instead of RangeIndex)"},"diff":{"kind":"string","value":"diff --git a/doc/source/whatsnew/v2.2.1.rst b/doc/source/whatsnew/v2.2.1.rst\nindex ab62a7c7598d5..d81032fafa730 100644\n--- a/doc/source/whatsnew/v2.2.1.rst\n+++ b/doc/source/whatsnew/v2.2.1.rst\n@@ -18,6 +18,7 @@ Fixed regressions\n - Fixed regression in :func:`concat` changing long-standing behavior that always sorted the non-concatenation axis when the axis was a :class:`DatetimeIndex` (:issue:`57006`)\n - Fixed regression in :func:`merge_ordered` raising ``TypeError`` for ``fill_method=\"ffill\"`` and ``how=\"left\"`` (:issue:`57010`)\n - Fixed regression in :func:`pandas.testing.assert_series_equal` defaulting to ``check_exact=True`` when checking the :class:`Index` (:issue:`57067`)\n+- Fixed regression in :func:`read_json` where an :class:`Index` would be returned instead of a :class:`RangeIndex` (:issue:`57429`)\n - Fixed regression in :func:`wide_to_long` raising an ``AttributeError`` for string columns (:issue:`57066`)\n - Fixed regression in :meth:`.DataFrameGroupBy.idxmin`, :meth:`.DataFrameGroupBy.idxmax`, :meth:`.SeriesGroupBy.idxmin`, :meth:`.SeriesGroupBy.idxmax` ignoring the ``skipna`` argument (:issue:`57040`)\n - Fixed regression in :meth:`.DataFrameGroupBy.idxmin`, :meth:`.DataFrameGroupBy.idxmax`, :meth:`.SeriesGroupBy.idxmin`, :meth:`.SeriesGroupBy.idxmax` where values containing the minimum or maximum value for the dtype could produce incorrect results (:issue:`57040`)\ndiff --git a/pandas/io/json/_json.py b/pandas/io/json/_json.py\nindex 4c490c6b2cda2..9414f45215029 100644\n--- a/pandas/io/json/_json.py\n+++ b/pandas/io/json/_json.py\n@@ -1266,6 +1266,7 @@ def _try_convert_data(\n if result:\n return new_data, True\n \n+ converted = False\n if self.dtype_backend is not lib.no_default and not is_axis:\n # Fall through for conversion later on\n return data, True\n@@ -1273,16 +1274,17 @@ def _try_convert_data(\n # try float\n try:\n data = data.astype(\"float64\")\n+ converted = True\n except (TypeError, ValueError):\n pass\n \n- if data.dtype.kind == \"f\":\n- if data.dtype != \"float64\":\n- # coerce floats to 64\n- try:\n- data = data.astype(\"float64\")\n- except (TypeError, ValueError):\n- pass\n+ if data.dtype.kind == \"f\" and data.dtype != \"float64\":\n+ # coerce floats to 64\n+ try:\n+ data = data.astype(\"float64\")\n+ converted = True\n+ except (TypeError, ValueError):\n+ pass\n \n # don't coerce 0-len data\n if len(data) and data.dtype in (\"float\", \"object\"):\n@@ -1291,14 +1293,15 @@ def _try_convert_data(\n new_data = data.astype(\"int64\")\n if (new_data == data).all():\n data = new_data\n+ converted = True\n except (TypeError, ValueError, OverflowError):\n pass\n \n- # coerce ints to 64\n- if data.dtype == \"int\":\n- # coerce floats to 64\n+ if data.dtype == \"int\" and data.dtype != \"int64\":\n+ # coerce ints to 64\n try:\n data = data.astype(\"int64\")\n+ converted = True\n except (TypeError, ValueError):\n pass\n \n@@ -1307,7 +1310,7 @@ def _try_convert_data(\n if self.orient == \"split\":\n return data, False\n \n- return data, True\n+ return data, converted\n \n @final\n def _try_convert_to_date(self, data: Series) -> tuple[Series, bool]:\ndiff --git a/pandas/tests/io/json/test_pandas.py b/pandas/tests/io/json/test_pandas.py\nindex caa25841d3596..5279f3f1cdfbe 100644\n--- a/pandas/tests/io/json/test_pandas.py\n+++ b/pandas/tests/io/json/test_pandas.py\n@@ -24,6 +24,7 @@\n DataFrame,\n DatetimeIndex,\n Index,\n+ RangeIndex,\n Series,\n Timestamp,\n date_range,\n@@ -493,12 +494,12 @@ def test_frame_mixedtype_orient(self): # GH10289\n left = read_json(inp, orient=orient, convert_axes=False)\n tm.assert_frame_equal(left, right)\n \n- right.index = pd.RangeIndex(len(df))\n+ right.index = RangeIndex(len(df))\n inp = StringIO(df.to_json(orient=\"records\"))\n left = read_json(inp, orient=\"records\", convert_axes=False)\n tm.assert_frame_equal(left, right)\n \n- right.columns = pd.RangeIndex(df.shape[1])\n+ right.columns = RangeIndex(df.shape[1])\n inp = StringIO(df.to_json(orient=\"values\"))\n left = read_json(inp, orient=\"values\", convert_axes=False)\n tm.assert_frame_equal(left, right)\n@@ -2188,3 +2189,14 @@ def test_to_json_ea_null():\n {\"a\":null,\"b\":null}\n \"\"\"\n assert result == expected\n+\n+\n+def test_read_json_lines_rangeindex():\n+ # GH 57429\n+ data = \"\"\"\n+{\"a\": 1, \"b\": 2}\n+{\"a\": 3, \"b\": 4}\n+\"\"\"\n+ result = read_json(StringIO(data), lines=True).index\n+ expected = RangeIndex(2)\n+ tm.assert_index_equal(result, expected, exact=True)\n"},"body":{"kind":"string","value":"Backport PR #57439: BUG: read_json returning Index instead of RangeIndex"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57552"},"created_at":{"kind":"string","value":"2024-02-21T19:41:37Z"},"closed_at":{"kind":"string","value":"2024-02-21T20:46:10Z"},"merged_at":{"kind":"string","value":"2024-02-21T20:46:10Z"},"updated_at":{"kind":"string","value":"2024-02-21T20:46:10Z"}}},{"rowIdx":899,"cells":{"title":{"kind":"string","value":"BLD: Add pyarrow extra for pip installation"},"diff":{"kind":"string","value":"diff --git a/.github/workflows/package-checks.yml b/.github/workflows/package-checks.yml\nindex 28c56ec7ff03b..2de1649d42dfd 100644\n--- a/.github/workflows/package-checks.yml\n+++ b/.github/workflows/package-checks.yml\n@@ -24,7 +24,7 @@ jobs:\n runs-on: ubuntu-22.04\n strategy:\n matrix:\n- extra: [\"test\", \"performance\", \"computation\", \"fss\", \"aws\", \"gcp\", \"excel\", \"parquet\", \"feather\", \"hdf5\", \"spss\", \"postgresql\", \"mysql\", \"sql-other\", \"html\", \"xml\", \"plot\", \"output-formatting\", \"clipboard\", \"compression\", \"all\"]\n+ extra: [\"test\", \"pyarrow\", \"performance\", \"computation\", \"fss\", \"aws\", \"gcp\", \"excel\", \"parquet\", \"feather\", \"hdf5\", \"spss\", \"postgresql\", \"mysql\", \"sql-other\", \"html\", \"xml\", \"plot\", \"output-formatting\", \"clipboard\", \"compression\", \"all\"]\n fail-fast: false\n name: Install Extras - ${{ matrix.extra }}\n concurrency:\ndiff --git a/doc/source/whatsnew/v2.2.1.rst b/doc/source/whatsnew/v2.2.1.rst\nindex ab62a7c7598d5..936fedc376e61 100644\n--- a/doc/source/whatsnew/v2.2.1.rst\n+++ b/doc/source/whatsnew/v2.2.1.rst\n@@ -9,6 +9,12 @@ including other versions of pandas.\n {{ header }}\n \n .. ---------------------------------------------------------------------------\n+.. _whatsnew_221.enhancements:\n+\n+Enhancements\n+~~~~~~~~~~~~\n+- Added ``pyarrow`` pip extra so users can install pandas and pyarrow with pip with ``pip install pandas[pyarrow]`` (:issue:`54466`)\n+\n .. _whatsnew_221.regressions:\n \n Fixed regressions\ndiff --git a/pyproject.toml b/pyproject.toml\nindex 823619dff5b52..82a9d72c8cc74 100644\n--- a/pyproject.toml\n+++ b/pyproject.toml\n@@ -63,6 +63,7 @@ matplotlib = \"pandas:plotting._matplotlib\"\n \n [project.optional-dependencies]\n test = ['hypothesis>=6.46.1', 'pytest>=7.3.2', 'pytest-xdist>=2.2.0']\n+pyarrow = ['pyarrow>=10.0.1']\n performance = ['bottleneck>=1.3.6', 'numba>=0.56.4', 'numexpr>=2.8.4']\n computation = ['scipy>=1.10.0', 'xarray>=2022.12.0']\n fss = ['fsspec>=2022.11.0']\n"},"body":{"kind":"string","value":"Partial feedback from #54466"},"url":{"kind":"string","value":"https://api.github.com/repos/pandas-dev/pandas/pulls/57551"},"created_at":{"kind":"string","value":"2024-02-21T18:15:16Z"},"closed_at":{"kind":"string","value":"2024-02-21T20:13:44Z"},"merged_at":{"kind":"string","value":"2024-02-21T20:13:44Z"},"updated_at":{"kind":"string","value":"2024-02-21T22:29:11Z"}}}],"truncated":false,"partial":false},"paginationData":{"pageIndex":8,"numItemsPerPage":100,"numTotalItems":56742,"offset":800,"length":100}},"jwt":"eyJhbGciOiJFZERTQSJ9.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc3NjQ1MjY1Miwic3ViIjoiL2RhdGFzZXRzL1NhbW9lZC9QUkdlbiIsImV4cCI6MTc3NjQ1NjI1MiwiaXNzIjoiaHR0cHM6Ly9odWdnaW5nZmFjZS5jbyJ9.70kaxjl6UOZI3eT5QvLu8U3pSljukNAjXlIohS-RrX8ChGfoaE0waoOzgyLTPmwAb04GcxQWldSSzzRyPo1uCQ","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"validation","numRows":56742,"numBytesParquet":285004812}]},"discussionsStats":{"closed":0,"open":1,"total":1},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
title stringlengths 1 185 | diff stringlengths 0 32.2M | body stringlengths 0 123k ⌀ | url stringlengths 57 58 | created_at stringlengths 20 20 | closed_at stringlengths 20 20 | merged_at stringlengths 20 20 ⌀ | updated_at stringlengths 20 20 |
|---|---|---|---|---|---|---|---|
[pre-commit.ci] pre-commit autoupdate | diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index e683fc50c1c5d..e7c14b6400a0c 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -19,7 +19,7 @@ ci:
skip: [pylint, pyright, mypy]
repos:
- repo: https://github.com/astral-sh/ruff-pre-commit
- rev: v0.1.13
+ rev: v0.3.0... | <!--pre-commit.ci start-->
updates:
- [github.com/astral-sh/ruff-pre-commit: v0.1.13 → v0.3.0](https://github.com/astral-sh/ruff-pre-commit/compare/v0.1.13...v0.3.0)
- [github.com/jendrikseipp/vulture: v2.10 → v2.11](https://github.com/jendrikseipp/vulture/compare/v2.10...v2.11)
- [github.com/pylint-dev/pylint: v3.0.1 ... | https://api.github.com/repos/pandas-dev/pandas/pulls/57725 | 2024-03-04T16:49:11Z | 2024-03-07T22:57:32Z | null | 2024-03-07T22:57:36Z |
update from 2022 to 2024 image | diff --git a/.circleci/config.yml b/.circleci/config.yml
index 90afb1ce29684..ea93575ac9430 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -3,7 +3,7 @@ version: 2.1
jobs:
test-arm:
machine:
- image: ubuntu-2004:2022.04.1
+ image: default
resource_class: arm.large
envi... | - [x] closes #57719
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.
| https://api.github.com/repos/pandas-dev/pandas/pulls/57721 | 2024-03-04T13:29:47Z | 2024-03-04T21:44:35Z | 2024-03-04T21:44:35Z | 2024-03-29T07:59:02Z |
DOC: Remove references to `bfill`, `ffill`, `pad`, and `backfill` in `limit_direction` | diff --git a/pandas/core/resample.py b/pandas/core/resample.py
index 4a5feb92c02f9..4c87af9ff14c7 100644
--- a/pandas/core/resample.py
+++ b/pandas/core/resample.py
@@ -819,20 +819,6 @@ def interpolate(
limit_direction : {{'forward', 'backward', 'both'}}, Optional
Consecutive NaNs will be filled i... | Picked up issue #57092. This removes references to `bfill`, `ffill`, `pad`, `backfill` from `limit_direction` as they aren't supported. Also references `bfill` and `ffill` in the "See Also" section. Up to date with latest commit.
- [X] closes #57092
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-d... | https://api.github.com/repos/pandas-dev/pandas/pulls/57720 | 2024-03-04T13:23:07Z | 2024-03-05T02:50:35Z | 2024-03-05T02:50:35Z | 2024-03-05T02:50:41Z |
CLN: remove references to `is_anchored` from ci/code_checks.sh | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 998e48d96d6b3..5bbad800b7aa9 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -173,14 +173,12 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.Timestamp.tzinfo\
pandas.Timestamp.value\
pandas.Timestamp.year\
- ... | xref# #57473
removed references to removed method `is_anchored` from `ci/code_checks.sh` | https://api.github.com/repos/pandas-dev/pandas/pulls/57715 | 2024-03-03T22:29:12Z | 2024-03-04T18:25:51Z | 2024-03-04T18:25:51Z | 2024-03-04T18:25:52Z |
#48188 FIX: iloc works with namedtuple | diff --git a/pandas/core/indexing.py b/pandas/core/indexing.py
index c7a938dbc4449..356eaf74c759f 100644
--- a/pandas/core/indexing.py
+++ b/pandas/core/indexing.py
@@ -1734,6 +1734,9 @@ def _getitem_axis(self, key, axis: AxisInt):
if isinstance(key, list):
key = np.asarray(key)
+ if type... | - unit test for added for test_iloc.py that verifies that all four uses of iloc given in the reproducible example now works
- [x] closes #48188
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature | https://api.github.com/repos/pandas-dev/pandas/pulls/57714 | 2024-03-03T16:55:55Z | 2024-03-04T20:10:21Z | null | 2024-03-04T20:10:21Z |
BUG: Line plots aligned from start #57594 | diff --git a/pandas/plotting/_matplotlib/timeseries.py b/pandas/plotting/_matplotlib/timeseries.py
index d4587a6ccf90a..da395197737b7 100644
--- a/pandas/plotting/_matplotlib/timeseries.py
+++ b/pandas/plotting/_matplotlib/timeseries.py
@@ -310,7 +310,7 @@ def maybe_convert_index(ax: Axes, data: NDFrameT) -> NDFrameT:
... | #57594 BUG: df.plot makes a shift to the right if frequency multiplies to n > 1
The cause of this bug is that by default all elements are generated to align to the end of
a period instead of at the start and the period technically does not end at the start of
the last period but rather just before the period subse... | https://api.github.com/repos/pandas-dev/pandas/pulls/57713 | 2024-03-03T15:34:23Z | 2024-04-15T17:24:18Z | null | 2024-04-15T17:24:19Z |
TST: Add test for `grouby` after `dropna` agg `nunique` and `unique` | diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index d02e22c29159f..686279f25939a 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -2945,3 +2945,23 @@ def test_decimal_na_sort(test_series):
result = gb._grouper.result_index
... | - [x] closes #42016 (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/co... | https://api.github.com/repos/pandas-dev/pandas/pulls/57711 | 2024-03-03T02:43:59Z | 2024-03-05T00:47:10Z | 2024-03-05T00:47:10Z | 2024-03-05T01:09:48Z |
REF: Remove dynamic docstrings from option methods | diff --git a/pandas/_config/config.py b/pandas/_config/config.py
index 8ad1da732a449..9decc7eecf033 100644
--- a/pandas/_config/config.py
+++ b/pandas/_config/config.py
@@ -50,17 +50,12 @@
from __future__ import annotations
-from contextlib import (
- ContextDecorator,
- contextmanager,
-)
-from inspect impo... | xref https://github.com/pandas-dev/pandas/issues/57578#issuecomment-1960937283
These methods have complex docstrings in an attempt to display all option within the docstring. This makes these docstrings hard to automatically validate and [renders the internal implementation](https://pandas.pydata.org/pandas-docs/sta... | https://api.github.com/repos/pandas-dev/pandas/pulls/57710 | 2024-03-02T23:09:36Z | 2024-03-06T22:00:53Z | 2024-03-06T22:00:52Z | 2024-03-06T22:00:56Z |
REF: Avoid importing xlrd | diff --git a/pandas/io/excel/_base.py b/pandas/io/excel/_base.py
index 8a287beac7afd..c38ced573531e 100644
--- a/pandas/io/excel/_base.py
+++ b/pandas/io/excel/_base.py
@@ -43,6 +43,7 @@
from pandas.core.dtypes.common import (
is_bool,
+ is_file_like,
is_float,
is_integer,
is_list_like,
@@ -15... | - [x] closes #56692 (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/co... | https://api.github.com/repos/pandas-dev/pandas/pulls/57708 | 2024-03-02T20:12:22Z | 2024-03-05T00:29:17Z | 2024-03-05T00:29:17Z | 2024-03-05T00:32:15Z |
Backport PR #57668 on branch 2.2.x (CLN: More numpy 2 stuff) | diff --git a/pandas/_libs/src/vendored/ujson/python/objToJSON.c b/pandas/_libs/src/vendored/ujson/python/objToJSON.c
index 74ca8ead3d936..fa91db5fe34e3 100644
--- a/pandas/_libs/src/vendored/ujson/python/objToJSON.c
+++ b/pandas/_libs/src/vendored/ujson/python/objToJSON.c
@@ -74,7 +74,6 @@ typedef struct __NpyArrContex... | Backport PR #57668: CLN: More numpy 2 stuff | https://api.github.com/repos/pandas-dev/pandas/pulls/57707 | 2024-03-02T19:52:37Z | 2024-03-03T12:54:00Z | 2024-03-03T12:54:00Z | 2024-03-03T12:54:00Z |
Cython guard against [c|m|re]alloc failures | diff --git a/pandas/_libs/algos.pyx b/pandas/_libs/algos.pyx
index e70ac26a2c28e..e2e93c5242b24 100644
--- a/pandas/_libs/algos.pyx
+++ b/pandas/_libs/algos.pyx
@@ -180,6 +180,8 @@ def is_lexsorted(list_of_arrays: list) -> bool:
n = len(list_of_arrays[0])
cdef int64_t **vecs = <int64_t**>malloc(nlevels * si... | Not sure if these are testable but in the case of the system being exhausted for resources these should explicitly throw a MemoryError instead of allow undefined behavior
@MarcoGorelli don't know how difficult it would be but would be cool to have the cython linter catch uses of any low-level allocation function and... | https://api.github.com/repos/pandas-dev/pandas/pulls/57705 | 2024-03-02T17:42:22Z | 2024-03-20T17:00:00Z | 2024-03-20T17:00:00Z | 2024-03-21T23:20:55Z |
CLN: Hashtable rename struct members | diff --git a/pandas/_libs/hashtable.pxd b/pandas/_libs/hashtable.pxd
index 22b923580c491..29ace4a339ced 100644
--- a/pandas/_libs/hashtable.pxd
+++ b/pandas/_libs/hashtable.pxd
@@ -174,7 +174,7 @@ cdef class StringHashTable(HashTable):
cdef struct Int64VectorData:
int64_t *data
- Py_ssize_t n, m
+ Py_ssiz... | Should help with readability | https://api.github.com/repos/pandas-dev/pandas/pulls/57704 | 2024-03-02T17:34:06Z | 2024-03-20T17:48:17Z | 2024-03-20T17:48:17Z | 2024-03-20T17:52:49Z |
Nanosecond fixed precision of DatetimeIndex with time zone information, Fix #53473 | diff --git a/pandas/_libs/src/datetime/pd_datetime.c b/pandas/_libs/src/datetime/pd_datetime.c
index 19de51be6e1b2..1a45c6883fa9d 100644
--- a/pandas/_libs/src/datetime/pd_datetime.c
+++ b/pandas/_libs/src/datetime/pd_datetime.c
@@ -71,7 +71,9 @@ static int convert_pydatetime_to_datetimestruct(PyObject *dtobj,
out->... | The expected behaviour is now correct from issue #53473 The out->picoseond value wasn't set which ended with a Json error regarding the ns calculations.
- [x] closes #53473
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug ... | https://api.github.com/repos/pandas-dev/pandas/pulls/57703 | 2024-03-02T16:45:54Z | 2024-04-15T17:25:25Z | null | 2024-04-15T17:25:26Z |
Less Heap Usage in Hashtable | diff --git a/pandas/_libs/hashtable.pxd b/pandas/_libs/hashtable.pxd
index eaec9e8462450..22b923580c491 100644
--- a/pandas/_libs/hashtable.pxd
+++ b/pandas/_libs/hashtable.pxd
@@ -180,7 +180,7 @@ cdef class Vector:
cdef bint external_view_exists
cdef class Int64Vector(Vector):
- cdef Int64VectorData *data
+... | null | https://api.github.com/repos/pandas-dev/pandas/pulls/57701 | 2024-03-01T22:43:53Z | 2024-03-05T00:45:30Z | 2024-03-05T00:45:30Z | 2024-03-12T02:31:20Z |
DEPR: remove deprecated freqs/abbrevs 'A', 'A-DEC', 'A-JAN', etc. | diff --git a/doc/source/user_guide/timeseries.rst b/doc/source/user_guide/timeseries.rst
index 0f0e6271d8329..0f38d90e18616 100644
--- a/doc/source/user_guide/timeseries.rst
+++ b/doc/source/user_guide/timeseries.rst
@@ -1327,8 +1327,8 @@ frequencies. We will refer to these aliases as *period aliases*.
.. deprecated... | xref #55252
remove deprecated string 'A', 'A-DEC', etc. denoting timedelta abbreviations and timeseries frequencies
| https://api.github.com/repos/pandas-dev/pandas/pulls/57699 | 2024-03-01T22:26:56Z | 2024-03-08T18:30:25Z | 2024-03-08T18:30:25Z | 2024-03-08T18:30:33Z |
BUG: Fix empty MultiIndex DataFrame xlsx export | diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index a95f0485abd5f..6b412f5427811 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -324,6 +324,7 @@ MultiIndex
I/O
^^^
+- Bug in :meth:`DataFrame.to_excel` when writing empty :class:`DataFrame` with :cla... | Fix Excel xlsx export of empty (zero rows) DataFrame with MultiIndex on both axes.
- [x] closes #57696
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas... | https://api.github.com/repos/pandas-dev/pandas/pulls/57697 | 2024-03-01T19:46:53Z | 2024-03-02T12:04:19Z | 2024-03-02T12:04:19Z | 2024-03-02T12:37:32Z |
Use memcpy / realloc more effectively in hashtable | diff --git a/pandas/_libs/hashtable.pxd b/pandas/_libs/hashtable.pxd
index 29ace4a339ced..a5a3edad63403 100644
--- a/pandas/_libs/hashtable.pxd
+++ b/pandas/_libs/hashtable.pxd
@@ -183,7 +183,7 @@ cdef class Int64Vector(Vector):
cdef Int64VectorData data
cdef ndarray ao
- cdef resize(self)
+ cdef resi... | null | https://api.github.com/repos/pandas-dev/pandas/pulls/57695 | 2024-03-01T18:25:14Z | 2024-03-21T18:29:27Z | 2024-03-21T18:29:27Z | 2024-03-21T18:29:30Z |
Backport PR #57689 on branch 2.2.x (CI: fix ci (calamine typing)) | diff --git a/pandas/io/excel/_calamine.py b/pandas/io/excel/_calamine.py
index 4f65acf1aa40e..5259469f7a569 100644
--- a/pandas/io/excel/_calamine.py
+++ b/pandas/io/excel/_calamine.py
@@ -74,9 +74,7 @@ def load_workbook(
) -> CalamineWorkbook:
from python_calamine import load_workbook
- return l... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57692 | 2024-03-01T13:47:28Z | 2024-03-01T15:36:48Z | 2024-03-01T15:36:48Z | 2024-03-01T15:36:48Z |
CI: fix ci (calamine typing) | diff --git a/pandas/io/excel/_calamine.py b/pandas/io/excel/_calamine.py
index 1f721c65982d4..b8994e679d4b1 100644
--- a/pandas/io/excel/_calamine.py
+++ b/pandas/io/excel/_calamine.py
@@ -75,7 +75,7 @@ def load_workbook(
from python_calamine import load_workbook
return load_workbook(
- f... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57689 | 2024-03-01T12:14:35Z | 2024-03-01T13:42:31Z | 2024-03-01T13:42:31Z | 2024-03-01T13:47:52Z |
BUG: datetime parsing fails on a leapday | diff --git a/pandas/_libs/tslibs/parsing.pyx b/pandas/_libs/tslibs/parsing.pyx
index ad723df485ba6..435f323ce14aa 100644
--- a/pandas/_libs/tslibs/parsing.pyx
+++ b/pandas/_libs/tslibs/parsing.pyx
@@ -938,6 +938,8 @@ def guess_datetime_format(dt_str: str, bint dayfirst=False) -> str | None:
# same default used b... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57685 | 2024-02-29T22:11:43Z | 2024-02-29T23:25:31Z | null | 2024-03-01T22:10:33Z |
CLN: Enforce deprecation of axis=None in DataFrame reductions | diff --git a/asv_bench/benchmarks/stat_ops.py b/asv_bench/benchmarks/stat_ops.py
index 89bda81ccf08c..8913293dfa20e 100644
--- a/asv_bench/benchmarks/stat_ops.py
+++ b/asv_bench/benchmarks/stat_ops.py
@@ -33,6 +33,7 @@ def setup(self, op, axis):
("median", 1),
("median", None),
... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57684 | 2024-02-29T21:28:18Z | 2024-03-05T23:04:38Z | 2024-03-05T23:04:38Z | 2024-03-05T23:09:23Z |
wip Remove docstring substitutions | diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index f530466c0fc30..f8d25fdc6b80f 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -187,11 +187,7 @@
console,
format as fmt,
)
-from pandas.io.formats.info import (
- INFO_DOCSTRING,
- DataFrameInfo,
- frame_sub_kwargs,
-)
+fro... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57683 | 2024-02-29T18:37:31Z | 2024-03-31T18:38:34Z | null | 2024-03-31T18:38:34Z |
BUG: Subtraction fails with matching index of different name and type (pandas-dev#57524) | diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index 0f125af599b12..7b70e9cc54ea9 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -268,6 +268,7 @@ Bug fixes
- Fixed bug in :meth:`DataFrame.to_string` that raised ``StopIteration`` with nested DataFrames.... | - [x] closes #57524
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [ ]... | https://api.github.com/repos/pandas-dev/pandas/pulls/57680 | 2024-02-29T15:24:23Z | 2024-03-20T17:30:53Z | null | 2024-03-20T17:30:54Z |
BUG: pd.unique(Index) now returns Index as Index.unique | diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index 9812521fe2767..cc8f26bf95a2f 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -390,6 +390,7 @@ Other
^^^^^
- Bug in :class:`DataFrame` when passing a ``dict`` with a NA scalar and ``columns`` that wou... | Some old tests are adjusted for consistency.
- [x] closes #57043(Replace xxxx with the GitHub issue number)
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://p... | https://api.github.com/repos/pandas-dev/pandas/pulls/57679 | 2024-02-29T14:49:53Z | 2024-03-12T17:26:38Z | 2024-03-12T17:26:38Z | 2024-03-13T03:58:37Z |
DOC: Extended the documentation for `DataFrame.sort_values()` | diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index f530466c0fc30..b64aaf8537ad9 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -6819,7 +6819,9 @@ def sort_values(
4 D 7 2 e
5 C 4 3 F
- Sort by col1
+ **Sort by a single column**
+... | The current docstring for [`DataFrame.sort_values()`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.sort_values.html) is lacking clarity, and also contains links that are not converted to hyperlinks. I extended and rephrased part of the documentation for this method. In particular:
- Added further ex... | https://api.github.com/repos/pandas-dev/pandas/pulls/57678 | 2024-02-29T12:11:25Z | 2024-03-05T20:50:32Z | 2024-03-05T20:50:32Z | 2024-03-05T20:50:40Z |
DOC: Extended the documentation for `DataFrame.sort_values()` | diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index f530466c0fc30..5abe2a2720ef6 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -6819,7 +6819,9 @@ def sort_values(
4 D 7 2 e
5 C 4 3 F
- Sort by col1
+ **Sort by a single column**
+... | The current docstring for [`DataFrame.sort_values()`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.sort_values.html) is lacking clarity, and also contains links that are not converted to hyperlinks. I extended and rephrased part of the documentation for this method. In particular:
- Added further ex... | https://api.github.com/repos/pandas-dev/pandas/pulls/57677 | 2024-02-29T10:36:50Z | 2024-02-29T10:59:54Z | null | 2024-02-29T10:59:54Z |
WEB: Remove unmaintained projects from Ecosystem | diff --git a/web/pandas/community/ecosystem.md b/web/pandas/community/ecosystem.md
index 58c5da67bcd74..715a2fafbe87a 100644
--- a/web/pandas/community/ecosystem.md
+++ b/web/pandas/community/ecosystem.md
@@ -21,10 +21,6 @@ please let us know.
## Statistics and machine learning
-### [pandas-tfrecords](https://pypi... | Lots of projects in our Ecosystem page seem to be obsolete and irrelevant now. There are few more that could probably be removed to help users find the relevant ones faster and easier, but I'm just removing the ones that didn't have any commit for at least two years.
| https://api.github.com/repos/pandas-dev/pandas/pulls/57675 | 2024-02-29T09:51:32Z | 2024-03-05T00:53:52Z | 2024-03-05T00:53:52Z | 2024-03-05T00:53:59Z |
CI: avoid `guess_datetime_format` failure on 29th of Feburary | diff --git a/pandas/_libs/tslibs/parsing.pyx b/pandas/_libs/tslibs/parsing.pyx
index ad723df485ba6..94c549cbd3db0 100644
--- a/pandas/_libs/tslibs/parsing.pyx
+++ b/pandas/_libs/tslibs/parsing.pyx
@@ -936,8 +936,10 @@ def guess_datetime_format(dt_str: str, bint dayfirst=False) -> str | None:
datetime_attrs_to_... | - [ ] closes #57672 (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/co... | https://api.github.com/repos/pandas-dev/pandas/pulls/57674 | 2024-02-29T09:19:22Z | 2024-03-05T20:14:53Z | 2024-03-05T20:14:53Z | 2024-03-05T20:15:00Z |
CLN: Enforce deprecation of pinning name in SeriesGroupBy.agg | diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index a95f0485abd5f..d16d3fa85bc1b 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -191,6 +191,7 @@ Removal of prior version deprecations/changes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
- :func:`read... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57671 | 2024-02-29T04:24:12Z | 2024-03-05T00:40:27Z | 2024-03-05T00:40:27Z | 2024-03-05T00:46:31Z |
DOC: Update drop duplicates documentation to specify method limitation | diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index f530466c0fc30..da354cbfc80dd 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -6506,6 +6506,11 @@ def drop_duplicates(
DataFrame or None
DataFrame with duplicates removed or None if ``inplace=True``.
+ Notes
+ ... | - [x] closes #56784
| https://api.github.com/repos/pandas-dev/pandas/pulls/57670 | 2024-02-29T03:11:19Z | 2024-03-05T00:55:24Z | 2024-03-05T00:55:24Z | 2024-03-05T01:45:57Z |
CLN: More numpy 2 stuff | diff --git a/pandas/_libs/src/vendored/ujson/python/objToJSON.c b/pandas/_libs/src/vendored/ujson/python/objToJSON.c
index 74ca8ead3d936..fa91db5fe34e3 100644
--- a/pandas/_libs/src/vendored/ujson/python/objToJSON.c
+++ b/pandas/_libs/src/vendored/ujson/python/objToJSON.c
@@ -74,7 +74,6 @@ typedef struct __NpyArrContex... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57668 | 2024-02-28T23:30:02Z | 2024-03-02T19:52:12Z | 2024-03-02T19:52:12Z | 2024-03-02T19:52:13Z |
ENH: Report how far off the formatting is | diff --git a/pandas/io/excel/_base.py b/pandas/io/excel/_base.py
index 6fa23ef94d200..8a287beac7afd 100644
--- a/pandas/io/excel/_base.py
+++ b/pandas/io/excel/_base.py
@@ -1327,7 +1327,8 @@ def _value_with_fmt(
# xref https://support.microsoft.com/en-au/office/excel-specifications-and-limits-1672b34d-7043... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57667 | 2024-02-28T20:34:52Z | 2024-02-28T22:21:32Z | 2024-02-28T22:21:32Z | 2024-02-28T22:56:28Z |
BUG: interchange protocol with nullable datatypes a non-null validity | diff --git a/doc/source/whatsnew/v2.2.2.rst b/doc/source/whatsnew/v2.2.2.rst
index 058f7aebcd538..96f210ce6b7b9 100644
--- a/doc/source/whatsnew/v2.2.2.rst
+++ b/doc/source/whatsnew/v2.2.2.rst
@@ -13,6 +13,7 @@ including other versions of pandas.
Fixed regressions
~~~~~~~~~~~~~~~~~
+- :meth:`DataFrame.__dataframe__... | - [ ] closes #57643 (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/co... | https://api.github.com/repos/pandas-dev/pandas/pulls/57665 | 2024-02-28T19:56:04Z | 2024-03-07T19:55:05Z | 2024-03-07T19:55:05Z | 2024-04-10T12:07:45Z |
FIX: fix default argument of duplicated | diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index f530466c0fc30..cd20307214726 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -6572,7 +6572,7 @@ def drop_duplicates(
def duplicated(
self,
subset: Hashable | Sequence[Hashable] | None = None,
- keep: DropKeep = ... | `df.duplicated(keep=False)`
Should have default `keep` parameter as `False`
It's proper result for `df.duplicated()` to show all duplicates.
- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase... | https://api.github.com/repos/pandas-dev/pandas/pulls/57658 | 2024-02-28T04:10:02Z | 2024-02-28T04:17:38Z | null | 2024-02-28T04:17:38Z |
Fixing bug_ 57596 | diff --git a/pandas/core/indexing.py b/pandas/core/indexing.py
index c7a938dbc4449..ae58e9b52012e 100644
--- a/pandas/core/indexing.py
+++ b/pandas/core/indexing.py
@@ -1490,6 +1490,11 @@ def _convert_to_indexer(self, key, axis: AxisInt):
# if we are a label return me
try:
+ i... | - [x] closes #57596
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [ ... | https://api.github.com/repos/pandas-dev/pandas/pulls/57657 | 2024-02-28T03:26:37Z | 2024-03-18T01:28:23Z | null | 2024-03-18T01:28:24Z |
CLN: Enforce deprecation of using alias for builtin/NumPy funcs (#57444) | diff --git a/scripts/handle_outliers.py b/scripts/handle_outliers.py
new file mode 100644
index 0000000000000..7b945a6ddf327
--- /dev/null
+++ b/scripts/handle_outliers.py
@@ -0,0 +1,30 @@
+import pandas as pd
+import numpy as np
+
+
+"""
+Detect and handle outliers in a DataFrame.
+
+Parameters:
+ data: DataFrame
+... | * CLN: Enforce deprecation of using alias for builtin/NumPy funcs
* GH# and whatsnew
* Fixup docs
* More tests
* Restore docstring
* Test fixes
* Test fixups
* Test fixes
* Test fixup
* Test fixes
- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](... | https://api.github.com/repos/pandas-dev/pandas/pulls/57655 | 2024-02-27T23:51:12Z | 2024-02-28T17:32:32Z | null | 2024-02-28T17:32:33Z |
REF: simplify pytables _set_tz | diff --git a/pandas/io/pytables.py b/pandas/io/pytables.py
index c7ee1cac2e14a..c835a7365d158 100644
--- a/pandas/io/pytables.py
+++ b/pandas/io/pytables.py
@@ -21,7 +21,6 @@
Final,
Literal,
cast,
- overload,
)
import warnings
@@ -85,6 +84,7 @@
DatetimeArray,
PeriodArray,
)
+from pandas... | yak-shaving aimed at pieces of the Ice Cream Agreement. | https://api.github.com/repos/pandas-dev/pandas/pulls/57654 | 2024-02-27T23:01:49Z | 2024-02-28T00:25:21Z | 2024-02-28T00:25:21Z | 2024-02-28T00:39:40Z |
CLN: unify error message when parsing datetimes with mixed time zones with utc=False | diff --git a/pandas/_libs/tslib.pyx b/pandas/_libs/tslib.pyx
index a09f4321c0d3c..d320bfdbe3022 100644
--- a/pandas/_libs/tslib.pyx
+++ b/pandas/_libs/tslib.pyx
@@ -598,7 +598,8 @@ cpdef array_to_datetime(
is_same_offsets = len(out_tzoffset_vals) == 1
if not is_same_offsets:
raise ValueEr... | xref #57275, #55793
unified ValueError message when parsing datetimes with mixed time zones with utc=False
so far we get two different ValueError messages:
```
import pandas as pd
from datetime import datetime
import pytz
str_my ="2020-10-26 00:00:00+06:00"
ts = pd.Timestamp("2018-01-01", tz="US/Pacific")
... | https://api.github.com/repos/pandas-dev/pandas/pulls/57653 | 2024-02-27T22:18:28Z | 2024-02-28T16:42:10Z | 2024-02-28T16:42:10Z | 2024-02-28T16:42:18Z |
TST: fix test_complibs on mac | diff --git a/pandas/tests/io/pytables/test_file_handling.py b/pandas/tests/io/pytables/test_file_handling.py
index ed5f8cde7db7b..d8f38e9cdad1f 100644
--- a/pandas/tests/io/pytables/test_file_handling.py
+++ b/pandas/tests/io/pytables/test_file_handling.py
@@ -8,6 +8,7 @@
is_ci_environment,
is_platform_linux,... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57652 | 2024-02-27T22:03:16Z | 2024-02-27T23:24:40Z | 2024-02-27T23:24:40Z | 2024-02-28T00:40:01Z |
PERF: Return RangeIndex from RangeIndex.join when possible | diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index a95f0485abd5f..fa148a2f4a4d8 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -253,6 +253,7 @@ Performance improvements
- Performance improvement in :meth:`Index.take` when ``indices`` is a full range ... | Discovered in https://github.com/pandas-dev/pandas/pull/57441 | https://api.github.com/repos/pandas-dev/pandas/pulls/57651 | 2024-02-27T20:08:44Z | 2024-03-05T00:57:57Z | 2024-03-05T00:57:57Z | 2024-03-05T00:58:01Z |
DOC: RT03 fix for read_sql_query, read_feather | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 322942acb429c..c6e8ac43fdc8c 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -878,11 +878,9 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.plotting.parallel_coordinates\
pandas.plotting.radviz\
pandas.plottin... | - [x] xref #57416 (Replace xxxx with the GitHub issue number)
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57649 | 2024-02-27T18:09:11Z | 2024-02-28T16:41:09Z | 2024-02-28T16:41:08Z | 2024-02-28T16:41:16Z |
DOC: Add clarification to groupby docs regarding hashes and equality | diff --git a/pandas/core/shared_docs.py b/pandas/core/shared_docs.py
index 787a03471cf6e..06621f7127da3 100644
--- a/pandas/core/shared_docs.py
+++ b/pandas/core/shared_docs.py
@@ -178,6 +178,12 @@
<https://pandas.pydata.org/pandas-docs/stable/groupby.html>`__ for more
detailed usage and examples, including splitting... | closes #57526 | https://api.github.com/repos/pandas-dev/pandas/pulls/57648 | 2024-02-27T18:03:37Z | 2024-03-06T21:48:04Z | 2024-03-06T21:48:04Z | 2024-03-06T21:48:13Z |
PERF: Return RangeIndex from RangeIndex.reindex when possible | diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index fae7edba057ec..23ae0f3ea1bc7 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -256,6 +256,7 @@ Performance improvements
- Performance improvement in :meth:`RangeIndex.__getitem__` with a boolean mask r... | Discovered in https://github.com/pandas-dev/pandas/pull/57441 | https://api.github.com/repos/pandas-dev/pandas/pulls/57647 | 2024-02-27T17:33:32Z | 2024-03-05T23:03:34Z | 2024-03-05T23:03:34Z | 2024-03-05T23:03:36Z |
BUG: Change output returned by _LocIndexer._convert_to_indexer to return key with greater resolution value | diff --git a/doc/source/whatsnew/v2.2.1.rst b/doc/source/whatsnew/v2.2.1.rst
index 310dd921e44f6..ce2c54668ed61 100644
--- a/doc/source/whatsnew/v2.2.1.rst
+++ b/doc/source/whatsnew/v2.2.1.rst
@@ -62,6 +62,7 @@ Bug fixes
- Fixed bug in :func:`pandas.api.interchange.from_dataframe` which wasn't converting columns names... | Resolution info:
**Resolution.RESO_SEC - 3 for seconds**
**Resolution.RESO_MIN - 4 for minute**
Observation:
With the previous code, when the current entry (**resolution: 4, entry: '2024-02-24 10:08'**) has a greater resolution value than the smallest amongst previous entries (in this case **resolution: 3, entr... | https://api.github.com/repos/pandas-dev/pandas/pulls/57646 | 2024-02-27T15:59:38Z | 2024-03-20T17:24:38Z | null | 2024-03-20T17:24:38Z |
Create median_absolute_deviation | diff --git a/median_absolute_deviation b/median_absolute_deviation
new file mode 100644
index 0000000000000..a3a456f55877d
--- /dev/null
+++ b/median_absolute_deviation
@@ -0,0 +1,14 @@
+#MedianAbsoluteDeviation(MAD)
+
+def mad(self):
+ """
+ Calculates the median absolute deviation of each column in the DataFrame.
+... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57639 | 2024-02-27T06:01:55Z | 2024-02-27T15:28:09Z | null | 2024-02-27T15:28:39Z |
DOC: RT03 fix for read_sql method | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 875e328110aaf..9d773ade8cd8d 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -1092,7 +1092,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.read_orc\
pandas.read_sas\
pandas.read_spss\
- pandas.read_sq... | - [x] xref #57416 (Replace xxxx with the GitHub issue number)
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57638 | 2024-02-27T04:23:06Z | 2024-02-27T17:00:30Z | 2024-02-27T17:00:30Z | 2024-02-27T17:03:12Z |
BUG: Fix dataframe.update not updating dtype #55509 v2 | diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index a95f0485abd5f..6cba1806d3274 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -265,6 +265,7 @@ Bug fixes
~~~~~~~~~
- Fixed bug in :meth:`DataFrame.join` inconsistently setting result index name (:issu... | - [x] closes #55509.
- [x] 3 Tests added and passed.
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [x] Added an entry in the latest `doc/source/whatsnew/v3.0.rst`. (?)
A new PR was opened to replace the previous one (#55634) because... | https://api.github.com/repos/pandas-dev/pandas/pulls/57637 | 2024-02-27T02:56:34Z | 2024-03-02T18:57:28Z | 2024-03-02T18:57:28Z | 2024-03-05T11:57:44Z |
Support structural subtyping with ExtensionArray | diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index 8bb051b6228ce..7d158706d7433 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -28,6 +28,7 @@ enhancement2
Other enhancements
^^^^^^^^^^^^^^^^^^
+- :class:`ExtensionArray` now supports the structural... | - [X] closes #57633
This is a very naive implementation. Ideally we would move a lot of the extraneous functions / attributes out of the core `ExtensionArray` class and into a better home
| https://api.github.com/repos/pandas-dev/pandas/pulls/57634 | 2024-02-26T20:21:56Z | 2024-03-19T20:04:51Z | null | 2024-03-19T20:04:51Z |
Compile take functions for uint dtypes | diff --git a/pandas/_libs/algos.pyi b/pandas/_libs/algos.pyi
index caf5425dfc7b4..0a6be851e1efd 100644
--- a/pandas/_libs/algos.pyi
+++ b/pandas/_libs/algos.pyi
@@ -165,6 +165,15 @@ def take_1d_int32_float64(
def take_1d_int64_int64(
values: np.ndarray, indexer: npt.NDArray[np.intp], out: np.ndarray, fill_value=.... | Not sure why this wasn't compiled before, maybe because of wheel size? We should at least compile the exact matching, not averse to skipping the cross product with different itemsizes | https://api.github.com/repos/pandas-dev/pandas/pulls/57632 | 2024-02-26T18:18:13Z | 2024-03-16T17:47:44Z | 2024-03-16T17:47:43Z | 2024-03-16T23:38:34Z |
DOC: fix PR01/SA01 errors for pandas.tseries.offsets.*.is_(month|quarter|year)_(end|start) | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 875e328110aaf..b4a03eaae2aef 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -506,217 +506,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.melt\
pandas.option_context\
pandas.read_fwf\
- pandas.reset_... | - [x] xref #57438 (Replace xxxx with the GitHub issue number)
- [x] xref #57417 (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks pas... | https://api.github.com/repos/pandas-dev/pandas/pulls/57630 | 2024-02-26T15:14:39Z | 2024-02-27T16:54:13Z | 2024-02-27T16:54:13Z | 2024-02-28T04:34:41Z |
BUG: Unexpected behaviour when inserting timestamps into Series #57596 | diff --git a/.github/actions/run-tests/action.yml b/.github/actions/run-tests/action.yml
index b4778b74df335..4a9fe04a8f5f9 100644
--- a/.github/actions/run-tests/action.yml
+++ b/.github/actions/run-tests/action.yml
@@ -20,11 +20,6 @@ runs:
path: test-data.xml
if: failure()
- - name: Report Covera... | Resolution info:
**Resolution.RESO_SEC - 3 for seconds**
**Resolution.RESO_MIN - 4 for minute**
Observation:
With the previous code, when the current entry (**resolution: 4, entry: '2024-02-24 10:08'**) has a greater resolution value than the smallest amongst previous entries (in this case **resolution: 3, entr... | https://api.github.com/repos/pandas-dev/pandas/pulls/57628 | 2024-02-26T00:25:00Z | 2024-02-27T14:41:58Z | null | 2024-02-27T14:41:58Z |
DEPR: remove deprecated units ‘H’, ’T’, and smaller from Timedelta, TimedeltaIndex | diff --git a/asv_bench/benchmarks/timeseries.py b/asv_bench/benchmarks/timeseries.py
index 8e1deb99a66a4..06f488f7baaaf 100644
--- a/asv_bench/benchmarks/timeseries.py
+++ b/asv_bench/benchmarks/timeseries.py
@@ -183,7 +183,7 @@ def setup(self):
self.dt_ts = Series(5, rng3, dtype="datetime64[ns]")
def t... | xref #54061
removed deprecated units `"H", "T", "S", "t", "L", "l", "U", "u", "N", "n"` from Timedelta, TimedeltaIndex
UPDATE:
- Enforced deprecation of strings ``T, t``, ``L, l``, ``U, u``, and ``N, n`` denoting frequencies in classes`Minute`, `Milli` `Micro`, and `Nano`
- Enforced deprecation of strings ``T, ... | https://api.github.com/repos/pandas-dev/pandas/pulls/57627 | 2024-02-25T22:55:17Z | 2024-03-21T19:17:20Z | 2024-03-21T19:17:20Z | 2024-03-21T21:02:04Z |
BUG: Unexpected behaviour when inserting timestamps into Series (#57596) | diff --git a/.github/actions/run-tests/action.yml b/.github/actions/run-tests/action.yml
index b4778b74df335..4a9fe04a8f5f9 100644
--- a/.github/actions/run-tests/action.yml
+++ b/.github/actions/run-tests/action.yml
@@ -20,11 +20,6 @@ runs:
path: test-data.xml
if: failure()
- - name: Report Covera... | …Series #57596
- [x] closes #57596
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#p... | https://api.github.com/repos/pandas-dev/pandas/pulls/57626 | 2024-02-25T22:17:11Z | 2024-02-26T00:08:30Z | null | 2024-02-26T00:08:30Z |
remove check to enforce ES01 errors | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 47a2cf93a4f89..d8c3690632283 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -414,1048 +414,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.tseries.offsets.YearEnd.rule_code # There should be no backslash in the final line, p... | - [x] closes https://github.com/pandas-dev/pandas/issues/57440
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57625 | 2024-02-25T22:04:10Z | 2024-02-26T17:56:33Z | 2024-02-26T17:56:33Z | 2024-02-26T18:19:29Z |
Remove inline from khash_python | diff --git a/pandas/_libs/include/pandas/vendored/klib/khash_python.h b/pandas/_libs/include/pandas/vendored/klib/khash_python.h
index 8bb3f84369b0b..811fdd139de2c 100644
--- a/pandas/_libs/include/pandas/vendored/klib/khash_python.h
+++ b/pandas/_libs/include/pandas/vendored/klib/khash_python.h
@@ -16,7 +16,7 @@ typed... | @DeaMariaLeon noted that #57575 caused a slight regression in the benchmarks. This is the only thing from that PR that could reasonably affect performance in any way | https://api.github.com/repos/pandas-dev/pandas/pulls/57618 | 2024-02-25T15:33:34Z | 2024-02-26T11:32:24Z | 2024-02-26T11:32:24Z | 2024-02-26T15:59:41Z |
Doc: resolve GL08 for pandas.Timedelta.microseconds, unit & value | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 231d40e17c0c0..a8d1c9d8df056 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -165,9 +165,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.Series.dt.qyear\
pandas.Series.dt.unit\
pandas.Series.empty\
- ... | - [x] xref #57443
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [ ] ... | https://api.github.com/repos/pandas-dev/pandas/pulls/57616 | 2024-02-25T09:54:14Z | 2024-02-28T17:34:29Z | 2024-02-28T17:34:29Z | 2024-02-28T17:34:36Z |
Doc: fixing RT03 errors for pandas.DataFrame.expanding | diff --git a/pandas/core/window/expanding.py b/pandas/core/window/expanding.py
index c3ee53c1b4551..abe853a8aa259 100644
--- a/pandas/core/window/expanding.py
+++ b/pandas/core/window/expanding.py
@@ -51,6 +51,9 @@ class Expanding(RollingAndExpandingMixin):
"""
Provide expanding window calculations.
+ An... | All RT03 Errors resolved in the following cases:
1. scripts/validate_docstrings.py --format=actions --errors=RT03 pandas.DataFrame.expanding
- [x] xref https://github.com/pandas-dev/pandas/issues/57416
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html... | https://api.github.com/repos/pandas-dev/pandas/pulls/57615 | 2024-02-25T09:31:13Z | 2024-02-26T23:05:05Z | 2024-02-26T23:05:05Z | 2024-03-10T20:00:29Z |
DOC: Add `DataFrame.isetitem` method | diff --git a/doc/source/reference/frame.rst b/doc/source/reference/frame.rst
index 31a1c6008bce8..7680c8b434866 100644
--- a/doc/source/reference/frame.rst
+++ b/doc/source/reference/frame.rst
@@ -74,6 +74,7 @@ Indexing, iteration
DataFrame.where
DataFrame.mask
DataFrame.query
+ DataFrame.isetitem
For ... | - [x] closes #57602 (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/c... | https://api.github.com/repos/pandas-dev/pandas/pulls/57614 | 2024-02-25T09:10:37Z | 2024-02-27T16:52:07Z | 2024-02-27T16:52:07Z | 2024-02-28T03:23:23Z |
fix SA01 error for pandas.ArrowDtype | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 47a2cf93a4f89..7f5f2f2d406fc 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -2152,7 +2152,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
MSG='Partially validate docstrings (SA01)' ; echo $MSG
$BASE_DIR/scripts/validate_docstri... | All SA01 Errors resolved in the following cases:
1. scripts/validate_docstrings.py --format=actions --errors=SA01 pandas.ArrowDtype
- [x] xref https://github.com/pandas-dev/pandas/issues/57417
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-... | https://api.github.com/repos/pandas-dev/pandas/pulls/57613 | 2024-02-25T08:46:35Z | 2024-02-26T18:11:03Z | 2024-02-26T18:11:03Z | 2024-02-26T18:23:47Z |
Doc: Fix PR07 errors for pandas.DataFrame.align | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 47a2cf93a4f89..bbfe67e2ae94c 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -1766,7 +1766,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
MSG='Partially validate docstrings (PR07)' ; echo $MSG
$BASE_DIR/scripts/validate_docstri... | All PR07 Errors resolved in the following cases:
1. scripts/validate_docstrings.py --format=actions --errors=PR07 pandas.DataFrame.align
- [x] xref https://github.com/pandas-dev/pandas/issues/57420
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#wri... | https://api.github.com/repos/pandas-dev/pandas/pulls/57612 | 2024-02-25T08:14:36Z | 2024-02-26T18:14:28Z | 2024-02-26T18:14:28Z | 2024-02-26T18:24:32Z |
Doc: fix PR01 docstring errors for pandas.CategoricalIndex.equals and pandas.CategoricalIndex.map | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 6de0a8c2ca325..e8e5056694f88 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -415,8 +415,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
MSG='Partially validate docstrings (PR01)' ; echo $MSG
$BASE_DIR/scripts/validate_docstring... | All PR01 Errors resolved in the following cases:
1. scripts/validate_docstrings.py --format=actions --errors=ES01 pandas.CategoricalIndex.equals
2. scripts/validate_docstrings.py --format=actions --errors=ES01 pandas.CategoricalIndex.map
- [x] xref https://github.com/pandas-dev/pandas/issues/57438
- [x] [Tests ... | https://api.github.com/repos/pandas-dev/pandas/pulls/57611 | 2024-02-25T07:50:42Z | 2024-02-26T23:05:32Z | 2024-02-26T23:05:32Z | 2024-03-11T00:19:59Z |
Doc: fix ES01 for pandas.CategoricalDtype | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 47a2cf93a4f89..e6c47250afaa4 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -423,7 +423,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.Categorical.ordered\
pandas.Categorical.remove_unused_categories\
pand... | All ES01 Errors resolved in the following cases:
1. scripts/validate_docstrings.py --format=actions --errors=ES01 pandas.CategoricalDtype
- [x] xref #57440
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a n... | https://api.github.com/repos/pandas-dev/pandas/pulls/57610 | 2024-02-25T07:24:48Z | 2024-02-26T17:59:11Z | null | 2024-02-26T18:23:35Z |
Doc: resolve GL08 for pandas.core.groupby.SeriesGroupBy.value_counts | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 6de0a8c2ca325..22c3a71812de7 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -178,7 +178,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.Timestamp.tzinfo\
pandas.Timestamp.value\
pandas.Timestamp.year\
- ... | All GL08 Errors resolved in the following cases:
1. scripts/validate_docstrings.py --format=actions --errors=GL08 pandas.core.groupby.SeriesGroupBy.value_counts
- [x] xref https://github.com/pandas-dev/pandas/issues/57443
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contri... | https://api.github.com/repos/pandas-dev/pandas/pulls/57609 | 2024-02-25T06:31:48Z | 2024-02-26T22:34:41Z | 2024-02-26T22:34:41Z | 2024-02-26T22:34:49Z |
TYP: misc annotations | diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 3253f9ab87363..e683fc50c1c5d 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -127,7 +127,7 @@ repos:
types: [python]
stages: [manual]
additional_dependencies: &pyright_dependencies
- - pyright@1.... | to pass more of the pandas-stubs tests. | https://api.github.com/repos/pandas-dev/pandas/pulls/57606 | 2024-02-25T01:44:07Z | 2024-02-26T18:28:44Z | 2024-02-26T18:28:44Z | 2024-04-07T10:59:14Z |
DOC: fix RT03 for CategoricalIndex.set_categories, DataFrame.astype, DataFrame.at_time and DataFrame.ewm | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 47a2cf93a4f89..e60e6cec9d89a 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -1882,10 +1882,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
MSG='Partially validate docstrings (RT03)' ; echo $MSG
$BASE_DIR/scripts/validate_docstr... | Resolve all RT03 errors for the following cases:
1. scripts/validate_docstrings.py --format=actions --errors=RT03 pandas.CategoricalIndex.set_categories (already valid)
2. scripts/validate_docstrings.py --format=actions --errors=RT03 pandas.DataFrame.astype
3. scripts/validate_docstrings.py --format=actions --erro... | https://api.github.com/repos/pandas-dev/pandas/pulls/57605 | 2024-02-24T23:49:36Z | 2024-02-26T18:29:43Z | 2024-02-26T18:29:43Z | 2024-02-26T18:29:49Z |
DOC: ES01 fix for HDFS Methods | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 47a2cf93a4f89..25bb691caed71 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -521,10 +521,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.DatetimeIndex.year\
pandas.DatetimeTZDtype.tz\
pandas.DatetimeTZDtype... | All ES01 Errors resolved in the following cases:
scripts/validate_docstrings.py --format=actions --errors=ES01 pandas.HDFStore.put
scripts/validate_docstrings.py --format=actions --errors=ES01 pandas.HDFStore.get
scripts/validate_docstrings.py --format=actions --errors=ES01 pandas.HDFStore.info
scripts/validat... | https://api.github.com/repos/pandas-dev/pandas/pulls/57604 | 2024-02-24T19:30:39Z | 2024-02-26T17:58:50Z | null | 2024-02-28T05:20:24Z |
DOC: fix RT03 for pandas.Index.to_numpy and pandas.Categorial.set_categories | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index f1e7f6d477906..47a2cf93a4f89 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -1882,8 +1882,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
MSG='Partially validate docstrings (RT03)' ; echo $MSG
$BASE_DIR/scripts/validate_docstri... | Resolve all errors for the following cases:
1. scripts/validate_docstrings.py --format=actions --errors=RT03 pandas.Index.to_numpy
2. scripts/validate_docstrings.py --format=actions --errors=RT03 pandas.Categorical.set_categories
Also fixes typos and wrong default value in docstring of pandas.Categorical.set_cat... | https://api.github.com/repos/pandas-dev/pandas/pulls/57603 | 2024-02-24T16:48:03Z | 2024-02-24T18:34:28Z | 2024-02-24T18:34:28Z | 2024-02-24T23:16:57Z |
DOC: Fixing GL08 errors for pandas.ExcelFile.sheet_names and pandas.MultiIndex.codes | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 875e328110aaf..4a9e18fb33eaa 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -145,7 +145,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
MSG='Partially validate docstrings (GL08)' ; echo $MSG
$BASE_DIR/scripts/validate_docstrings.... | Resolved GL08 errors for the following:
1. scripts/validate_docstrings.py --format=actions --errors=GL08 pandas.ExcelFile.sheet_names
2. scripts/validate_docstrings.py --format=actions --errors=GL08 pandas.MultiIndex.codes
Ref: #57443
- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tes... | https://api.github.com/repos/pandas-dev/pandas/pulls/57601 | 2024-02-24T14:19:18Z | 2024-02-27T22:10:03Z | 2024-02-27T22:10:03Z | 2024-02-28T03:45:10Z |
DOC: Whatsnew notable bugfix on groupby behavior with unobserved groups | diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index 1f9f5e85a6c4b..da03c8f50086a 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -43,10 +43,63 @@ Notable bug fixes
These are bug fixes that might have notable behavior changes.
-.. _whatsnew_300.nota... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57600 | 2024-02-24T13:02:58Z | 2024-02-26T18:31:47Z | 2024-02-26T18:31:47Z | 2024-02-27T08:43:05Z |
REF: Move compute to BinGrouper.result_index_and_ids | diff --git a/pandas/core/groupby/ops.py b/pandas/core/groupby/ops.py
index 46ef0f38706bc..738b4970b0924 100644
--- a/pandas/core/groupby/ops.py
+++ b/pandas/core/groupby/ops.py
@@ -1113,23 +1113,7 @@ def indices(self):
@cache_readonly
def group_info(self) -> tuple[npt.NDArray[np.intp], int]:
- ngroup... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57599 | 2024-02-24T11:59:24Z | 2024-02-24T18:29:05Z | 2024-02-24T18:29:05Z | 2024-02-24T20:45:53Z |
CLN: Use group_info less | diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index c90ae4d590b45..3011fa235b22d 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -813,7 +813,7 @@ def value_counts(
from pandas.core.reshape.merge import get_join_indexers
from pandas.cor... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57598 | 2024-02-24T11:47:58Z | 2024-02-24T18:27:37Z | 2024-02-24T18:27:37Z | 2024-02-24T20:46:08Z |
DOC: ES01 fix for to_csv method | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index f1e7f6d477906..11257a49761ad 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -476,7 +476,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.DataFrame.sparse.from_spmatrix\
pandas.DataFrame.sparse.to_coo\
pandas... | All ES01 Errors resolved in the following cases:
scripts/validate_docstrings.py --format=actions --errors=ES01 pandas.DataFrame.to_csv
- [x] xref #57440
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new... | https://api.github.com/repos/pandas-dev/pandas/pulls/57597 | 2024-02-24T11:26:06Z | 2024-02-26T17:58:27Z | null | 2024-02-26T17:58:28Z |
PERF: groupby(...).__len__ | diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index d44824183f05f..35c88d544c985 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -178,6 +178,7 @@ Performance improvements
- Performance improvement in :meth:`RangeIndex.take` returning a :class:`RangeInd... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57595 | 2024-02-23T23:21:07Z | 2024-02-24T00:10:17Z | 2024-02-24T00:10:17Z | 2024-02-24T00:24:42Z |
CLN: groupby.first/last unused compat | diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 668c9863612d8..711ed1a564868 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -3250,27 +3250,10 @@ def first(
1 5.0 1
3 6.0 3
"""
-
- def first_compat(obj: NDFrameT... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57589 | 2024-02-23T21:09:33Z | 2024-02-23T21:54:30Z | null | 2024-02-28T22:43:09Z |
PERF: Return a RangeIndex from __getitem__ with a bool mask when possible | diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index d6e3ac1ea48cc..d07f4f9f05708 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -167,6 +167,7 @@ Removal of prior version deprecations/changes
Performance improvements
~~~~~~~~~~~~~~~~~~~~~~~~
+- :met... | Discovered in https://github.com/pandas-dev/pandas/pull/57441
| https://api.github.com/repos/pandas-dev/pandas/pulls/57588 | 2024-02-23T20:08:34Z | 2024-03-02T02:24:32Z | 2024-03-02T02:24:32Z | 2024-03-02T02:24:35Z |
DOC-#57585: Add `Use Modin` section on `Scaling to large datasets` page | diff --git a/doc/source/user_guide/scale.rst b/doc/source/user_guide/scale.rst
index b262de5d71439..080f8484ce969 100644
--- a/doc/source/user_guide/scale.rst
+++ b/doc/source/user_guide/scale.rst
@@ -374,5 +374,33 @@ datasets.
You see more dask examples at https://examples.dask.org.
+Use Modin
+---------
+
+Modin... | - [x] closes #57585 (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/c... | https://api.github.com/repos/pandas-dev/pandas/pulls/57586 | 2024-02-23T14:55:27Z | 2024-03-07T17:17:03Z | 2024-03-07T17:17:03Z | 2024-03-07T17:17:43Z |
Backport PR #57582 on branch 2.2.x (DOC: Add contributors for 2.2.1) | diff --git a/doc/source/whatsnew/v2.2.0.rst b/doc/source/whatsnew/v2.2.0.rst
index d9ab0452c8334..e015afb17dce5 100644
--- a/doc/source/whatsnew/v2.2.0.rst
+++ b/doc/source/whatsnew/v2.2.0.rst
@@ -946,4 +946,4 @@ Other
Contributors
~~~~~~~~~~~~
-.. contributors:: v2.1.4..v2.2.0|HEAD
+.. contributors:: v2.1.4..v2.2.... | Backport PR #57582: DOC: Add contributors for 2.2.1 | https://api.github.com/repos/pandas-dev/pandas/pulls/57583 | 2024-02-23T14:21:06Z | 2024-02-23T14:48:32Z | 2024-02-23T14:48:32Z | 2024-02-23T14:48:32Z |
DOC: Add contributors for 2.2.1 | diff --git a/doc/source/whatsnew/v2.2.0.rst b/doc/source/whatsnew/v2.2.0.rst
index 9d29044c27833..329ef2859f56f 100644
--- a/doc/source/whatsnew/v2.2.0.rst
+++ b/doc/source/whatsnew/v2.2.0.rst
@@ -948,4 +948,4 @@ Other
Contributors
~~~~~~~~~~~~
-.. contributors:: v2.1.4..v2.2.0|HEAD
+.. contributors:: v2.1.4..v2.2.... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57582 | 2024-02-23T13:48:36Z | 2024-02-23T14:20:56Z | 2024-02-23T14:20:56Z | 2024-02-23T14:20:57Z |
Updating timeseries.offset_aliases links to use :ref: format | diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 668672ed05f72..0880e6730fd93 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -8569,8 +8569,8 @@ def asfreq(
Notes
-----
- To learn more about the frequency strings, please see `this link
- <https://p... | During code review on https://github.com/pandas-dev/pandas/pull/57562 it was suggested to update the links from this format
`this link <https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.
to this format
:ref:`this link<timeseries.offset_aliases>`
I found several plac... | https://api.github.com/repos/pandas-dev/pandas/pulls/57581 | 2024-02-23T07:47:20Z | 2024-02-23T09:55:27Z | 2024-02-23T09:55:27Z | 2024-02-23T17:04:21Z |
Backport PR #57576 on branch 2.2.x (DOC: Add release date for 2.2.1) | diff --git a/doc/source/whatsnew/v2.2.1.rst b/doc/source/whatsnew/v2.2.1.rst
index fa5304c1c3b56..f4ed594613349 100644
--- a/doc/source/whatsnew/v2.2.1.rst
+++ b/doc/source/whatsnew/v2.2.1.rst
@@ -1,6 +1,6 @@
.. _whatsnew_221:
-What's new in 2.2.1 (February XX, 2024)
+What's new in 2.2.1 (February 22, 2024)
-------... | Backport PR #57576: DOC: Add release date for 2.2.1 | https://api.github.com/repos/pandas-dev/pandas/pulls/57579 | 2024-02-23T03:34:03Z | 2024-02-23T04:47:35Z | 2024-02-23T04:47:35Z | 2024-02-23T04:47:35Z |
DOC: Add release date for 2.2.1 | diff --git a/doc/source/whatsnew/v2.2.1.rst b/doc/source/whatsnew/v2.2.1.rst
index fa5304c1c3b56..f4ed594613349 100644
--- a/doc/source/whatsnew/v2.2.1.rst
+++ b/doc/source/whatsnew/v2.2.1.rst
@@ -1,6 +1,6 @@
.. _whatsnew_221:
-What's new in 2.2.1 (February XX, 2024)
+What's new in 2.2.1 (February 22, 2024)
-------... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57576 | 2024-02-23T02:51:14Z | 2024-02-23T03:33:51Z | 2024-02-23T03:33:51Z | 2024-02-23T03:33:51Z |
CLN: Assorted khash-python cleanups | diff --git a/pandas/_libs/include/pandas/vendored/klib/khash_python.h b/pandas/_libs/include/pandas/vendored/klib/khash_python.h
index 5a933b45d9e21..8bb3f84369b0b 100644
--- a/pandas/_libs/include/pandas/vendored/klib/khash_python.h
+++ b/pandas/_libs/include/pandas/vendored/klib/khash_python.h
@@ -1,6 +1,9 @@
// Lic... | null | https://api.github.com/repos/pandas-dev/pandas/pulls/57575 | 2024-02-23T02:41:25Z | 2024-02-23T17:09:33Z | 2024-02-23T17:09:33Z | 2024-02-23T17:20:54Z |
CLN: Clean up unnecessary templating in hashtable | diff --git a/pandas/_libs/hashtable_class_helper.pxi.in b/pandas/_libs/hashtable_class_helper.pxi.in
index 26dcf0b6c4ce3..c4ed8a5ec30f9 100644
--- a/pandas/_libs/hashtable_class_helper.pxi.in
+++ b/pandas/_libs/hashtable_class_helper.pxi.in
@@ -82,18 +82,6 @@ cimported_types = ['complex64',
'uint64'... | khash already provides a macro for these which takes the type as the first argument - no need to import function names the way we do | https://api.github.com/repos/pandas-dev/pandas/pulls/57574 | 2024-02-23T02:00:18Z | 2024-02-23T02:07:15Z | null | 2024-02-23T02:07:16Z |
Backport PR #57314 on branch 2.2.x (BUG: Fix near-minimum timestamp handling) | diff --git a/doc/source/whatsnew/v2.2.1.rst b/doc/source/whatsnew/v2.2.1.rst
index 35d64c99f2002..fa5304c1c3b56 100644
--- a/doc/source/whatsnew/v2.2.1.rst
+++ b/doc/source/whatsnew/v2.2.1.rst
@@ -21,6 +21,7 @@ Fixed regressions
~~~~~~~~~~~~~~~~~
- Fixed memory leak in :func:`read_csv` (:issue:`57039`)
- Fixed perfo... | Backport PR #57314: BUG: Fix near-minimum timestamp handling | https://api.github.com/repos/pandas-dev/pandas/pulls/57573 | 2024-02-22T23:53:48Z | 2024-02-23T00:38:10Z | 2024-02-23T00:38:10Z | 2024-02-23T00:38:10Z |
TST: Clean contexts | diff --git a/doc/source/development/contributing_codebase.rst b/doc/source/development/contributing_codebase.rst
index 62559c4232b51..39e279fd5c917 100644
--- a/doc/source/development/contributing_codebase.rst
+++ b/doc/source/development/contributing_codebase.rst
@@ -596,14 +596,15 @@ with the specific exception subcl... | * Replaced only use of `use_numexpr`
* Created pytest native `temp_file` fixture for use over `tm.ensure_clean`
| https://api.github.com/repos/pandas-dev/pandas/pulls/57571 | 2024-02-22T20:25:42Z | 2024-02-24T18:36:06Z | 2024-02-24T18:36:05Z | 2024-02-24T18:36:09Z |
BUG: Interchange object data buffer has the wrong dtype / from_dataframe incorrect | diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 375c74f29e63a..3253f9ab87363 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -53,13 +53,11 @@ repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.5.0
hooks:
- - id: check-ast
- id: check... | - [ ] closes #54781 (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/co... | https://api.github.com/repos/pandas-dev/pandas/pulls/57570 | 2024-02-22T18:30:43Z | 2024-02-23T17:12:43Z | 2024-02-23T17:12:43Z | 2024-02-23T17:12:56Z |
Backport PR #57556 on branch 2.2.x (Remove PyArrow deprecation warning) | diff --git a/.github/workflows/unit-tests.yml b/.github/workflows/unit-tests.yml
index 4c7aa1e1e49ee..8736674bbf965 100644
--- a/.github/workflows/unit-tests.yml
+++ b/.github/workflows/unit-tests.yml
@@ -92,10 +92,7 @@ jobs:
- name: "Numpy Dev"
env_file: actions-311-numpydev.yaml
p... | #57556 | https://api.github.com/repos/pandas-dev/pandas/pulls/57568 | 2024-02-22T17:45:49Z | 2024-02-22T18:45:36Z | 2024-02-22T18:45:36Z | 2024-02-22T18:45:40Z |
DEPS: update numexpr to use not buggy numexpr 2.8.x anymore (update to 2.9.0) - fix critical CVE-2023-39631 | diff --git a/pyproject.toml b/pyproject.toml
index 82a9d72c8cc74..43cf1274dc380 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -64,7 +64,7 @@ matplotlib = "pandas:plotting._matplotlib"
[project.optional-dependencies]
test = ['hypothesis>=6.46.1', 'pytest>=7.3.2', 'pytest-xdist>=2.2.0']
pyarrow = ['pyarrow>=10.0... | update numexpr to 2.9.0 to fix CVE-2023-39631 findings
HINT: come from other project (apache-superset) where panda is injecting this faulty numexpr inside the project as sub-dependency
- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-... | https://api.github.com/repos/pandas-dev/pandas/pulls/57567 | 2024-02-22T14:22:22Z | 2024-02-22T16:54:52Z | null | 2024-02-22T16:54:53Z |
DOC: fix ES01 for pandas.Flags | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 04c3ff3a42971..6469f39e7c332 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -521,7 +521,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.DatetimeIndex.year\
pandas.DatetimeTZDtype.tz\
pandas.DatetimeTZDtype.... | All ES01 Errors resolved in the following cases:
1. scripts/validate_docstrings.py --format=actions --errors=ES01 pandas.Flags
- [x] xref https://github.com/pandas-dev/pandas/issues/57440
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests... | https://api.github.com/repos/pandas-dev/pandas/pulls/57563 | 2024-02-22T07:45:14Z | 2024-02-22T17:00:31Z | 2024-02-22T17:00:31Z | 2024-02-23T02:36:10Z |
DOC: fixing GL08 errors for pandas.DatetimeIndex.as_unit and pandas.DatetimeIndex.freq | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 47a2cf93a4f89..d89c64700ffbb 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -71,6 +71,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
MSG='Partially validate docstrings (PR02)' ; echo $MSG
$BASE_DIR/scripts/validate_docstrings.... | All GL08 Errors resolved in the following cases:
1. scripts/validate_docstrings.py --format=actions --errors=GL08 pandas.DatetimeIndex.as_unit
2. scripts/validate_docstrings.py --format=actions --errors=GL08 pandas.DatetimeIndex.freq
_Note: [6232a2e](https://github.com/pandas-dev/pandas/pull/57562/commits/6232a2... | https://api.github.com/repos/pandas-dev/pandas/pulls/57562 | 2024-02-22T06:32:35Z | 2024-02-26T18:12:56Z | 2024-02-26T18:12:56Z | 2024-02-26T18:24:00Z |
DOC: fixing PR01 errors for pandas.Categorical and pandas.Categorical.__array__ | diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 6469f39e7c332..f1e7f6d477906 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -1458,8 +1458,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
MSG='Partially validate docstrings (PR01)' ; echo $MSG
$BASE_DIR/scripts/validate_docstri... | All PR01 Errors resolved in the following cases:
1. scripts/validate_docstrings.py --format=actions --errors=PR01 pandas.Categorical
2. scripts/validate_docstrings.py --format=actions --errors=PR01 pandas.Categorical.__array__
- [x] xref https://github.com/pandas-dev/pandas/issues/57438
- [x] [Tests added and p... | https://api.github.com/repos/pandas-dev/pandas/pulls/57561 | 2024-02-22T05:43:38Z | 2024-02-23T17:13:26Z | 2024-02-23T17:13:26Z | 2024-02-23T17:14:24Z |
PERF: Switch conditions in RangeIndex._shallow_copy | diff --git a/pandas/core/indexes/range.py b/pandas/core/indexes/range.py
index 8552839b12d18..8a2e3fbf500a4 100644
--- a/pandas/core/indexes/range.py
+++ b/pandas/core/indexes/range.py
@@ -474,8 +474,9 @@ def _shallow_copy(self, values, name: Hashable = no_default):
diff = values[1] - values[0]
... | xref https://github.com/pandas-dev/pandas/pull/57534#issuecomment-1957832841
`is_range_indexer` lets us short circuit unlike checking the remainder
```python
In [1]: from pandas import *; import numpy as np
...: np.random.seed(123)
...: size = 1_000_000
...: ngroups = 1000
...: data = Series(np.r... | https://api.github.com/repos/pandas-dev/pandas/pulls/57560 | 2024-02-21T23:28:26Z | 2024-02-22T14:39:55Z | 2024-02-22T14:39:55Z | 2024-02-22T16:35:31Z |
CLN: correct file names in a comment in _optional.py | diff --git a/pandas/compat/_optional.py b/pandas/compat/_optional.py
index ddd9b591d3e83..26beca6a0e4b6 100644
--- a/pandas/compat/_optional.py
+++ b/pandas/compat/_optional.py
@@ -16,7 +16,8 @@
if TYPE_CHECKING:
import types
-# Update install.rst & setup.cfg when updating versions!
+# Update install.rst, actio... | corrected file names in a comment in `pandas/compat/_optional.py` | https://api.github.com/repos/pandas-dev/pandas/pulls/57558 | 2024-02-21T22:49:11Z | 2024-02-21T23:50:56Z | 2024-02-21T23:50:56Z | 2024-02-21T23:51:02Z |
Backport PR #57551: BLD: Add pyarrow extra for pip installation | diff --git a/.github/workflows/package-checks.yml b/.github/workflows/package-checks.yml
index d59ddf272f705..7c1da5678a2aa 100644
--- a/.github/workflows/package-checks.yml
+++ b/.github/workflows/package-checks.yml
@@ -24,7 +24,7 @@ jobs:
runs-on: ubuntu-22.04
strategy:
matrix:
- extra: ["test... | null | https://api.github.com/repos/pandas-dev/pandas/pulls/57557 | 2024-02-21T22:28:47Z | 2024-02-21T23:49:28Z | 2024-02-21T23:49:28Z | 2024-02-21T23:49:31Z |
Remove PyArrow deprecation warning | diff --git a/.github/workflows/unit-tests.yml b/.github/workflows/unit-tests.yml
index 533b81013a264..855973a22886a 100644
--- a/.github/workflows/unit-tests.yml
+++ b/.github/workflows/unit-tests.yml
@@ -64,10 +64,7 @@ jobs:
- name: "Numpy Dev"
env_file: actions-311-numpydev.yaml
p... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57556 | 2024-02-21T22:21:14Z | 2024-02-22T17:43:15Z | 2024-02-22T17:43:15Z | 2024-02-22T17:48:22Z |
CLN: Remove pickle support pre-pandas 1.0 | diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index 3fdb4af52a8c0..575113434b531 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -94,7 +94,7 @@ Other API changes
- Made ``dtype`` a required argument in :meth:`ExtensionArray._from_sequence_of_strings` (... | For a major pandas 3.0 release, I think it's reasonable that pickle support for pre-pandas 1.0 can be removed by now.
Retry at https://github.com/pandas-dev/pandas/pull/57155
| https://api.github.com/repos/pandas-dev/pandas/pulls/57555 | 2024-02-21T21:09:59Z | 2024-02-22T22:43:58Z | 2024-02-22T22:43:58Z | 2024-02-22T22:44:01Z |
Roadmap: remove ArrayManager | diff --git a/web/pandas/about/roadmap.md b/web/pandas/about/roadmap.md
index 4c12e3e786a32..aba95ec2c03fc 100644
--- a/web/pandas/about/roadmap.md
+++ b/web/pandas/about/roadmap.md
@@ -90,33 +90,6 @@ data types within pandas. This will let us take advantage of its I/O
capabilities and provide for better interoperabili... | - [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/con... | https://api.github.com/repos/pandas-dev/pandas/pulls/57554 | 2024-02-21T20:29:46Z | 2024-02-21T21:13:55Z | 2024-02-21T21:13:55Z | 2024-02-21T22:20:48Z |
API: avoid passing Manager to subclass __init__ | diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 8fd0cd8c66e3c..1be72c60783ec 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -651,25 +651,36 @@ def _constructor(self) -> type[DataFrame]:
return DataFrame
def _constructor_from_mgr(self, mgr, axes) -> DataFrame:
- if ... | - [x] closes #57032 (Replace xxxx with the GitHub issue number)
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/co... | https://api.github.com/repos/pandas-dev/pandas/pulls/57553 | 2024-02-21T20:21:57Z | 2024-03-26T01:40:18Z | 2024-03-26T01:40:18Z | 2024-04-10T12:08:36Z |
Backport PR #57439 on branch 2.2.x (BUG: read_json returning Index instead of RangeIndex) | diff --git a/doc/source/whatsnew/v2.2.1.rst b/doc/source/whatsnew/v2.2.1.rst
index ab62a7c7598d5..d81032fafa730 100644
--- a/doc/source/whatsnew/v2.2.1.rst
+++ b/doc/source/whatsnew/v2.2.1.rst
@@ -18,6 +18,7 @@ Fixed regressions
- Fixed regression in :func:`concat` changing long-standing behavior that always sorted th... | Backport PR #57439: BUG: read_json returning Index instead of RangeIndex | https://api.github.com/repos/pandas-dev/pandas/pulls/57552 | 2024-02-21T19:41:37Z | 2024-02-21T20:46:10Z | 2024-02-21T20:46:10Z | 2024-02-21T20:46:10Z |
BLD: Add pyarrow extra for pip installation | diff --git a/.github/workflows/package-checks.yml b/.github/workflows/package-checks.yml
index 28c56ec7ff03b..2de1649d42dfd 100644
--- a/.github/workflows/package-checks.yml
+++ b/.github/workflows/package-checks.yml
@@ -24,7 +24,7 @@ jobs:
runs-on: ubuntu-22.04
strategy:
matrix:
- extra: ["test... | Partial feedback from #54466 | https://api.github.com/repos/pandas-dev/pandas/pulls/57551 | 2024-02-21T18:15:16Z | 2024-02-21T20:13:44Z | 2024-02-21T20:13:44Z | 2024-02-21T22:29:11Z |
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