Merge branch 'main' into ipython

Author: saldanhad

ci/code_checks.sh

@@ -100,7 +100,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Timedelta.max PR02" \
         -i "pandas.Timedelta.min PR02" \
         -i "pandas.Timedelta.resolution PR02" \
-        -i "pandas.TimedeltaIndex.to_pytimedelta RT03,SA01" \
         -i "pandas.Timestamp.max PR02" \
         -i "pandas.Timestamp.min PR02" \
         -i "pandas.Timestamp.nanosecond GL08" \
@@ -160,7 +159,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.errors.CSSWarning SA01" \
         -i "pandas.errors.CategoricalConversionWarning SA01" \
         -i "pandas.errors.ChainedAssignmentError SA01" \
-        -i "pandas.errors.ClosedFileError SA01" \
         -i "pandas.errors.DataError SA01" \
         -i "pandas.errors.DuplicateLabelError SA01" \
         -i "pandas.errors.IntCastingNaNError SA01" \
@@ -170,7 +168,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.errors.NumExprClobberingError SA01" \
         -i "pandas.errors.NumbaUtilError SA01" \
         -i "pandas.errors.OptionError SA01" \
-        -i "pandas.errors.OutOfBoundsDatetime SA01" \
         -i "pandas.errors.OutOfBoundsTimedelta SA01" \
         -i "pandas.errors.PerformanceWarning SA01" \
         -i "pandas.errors.PossibleDataLossError SA01" \

doc/source/user_guide/10min.rst

@@ -177,7 +177,7 @@ See the indexing documentation :ref:`Indexing and Selecting Data <indexing>` and
 Getitem (``[]``)
 ~~~~~~~~~~~~~~~~
 
-For a :class:`DataFrame`, passing a single label selects a columns and
+For a :class:`DataFrame`, passing a single label selects a column and
 yields a :class:`Series` equivalent to ``df.A``:
 
 .. ipython:: python

doc/source/user_guide/dsintro.rst

@@ -87,8 +87,9 @@ index will be pulled out.
 
 **From scalar value**
 
-If ``data`` is a scalar value, an index must be
-provided. The value will be repeated to match the length of **index**.
+If ``data`` is a scalar value, the value will be repeated to match
+the length of **index**.  If the **index** is not provided, it defaults
+to ``RangeIndex(1)``.
 
 .. ipython:: python
 

pandas/_libs/src/vendored/ujson/python/JSONtoObj.c

@@ -38,9 +38,11 @@ Numeric decoder derived from TCL library
 
 // Licence at LICENSES/ULTRAJSON_LICENSE
 
-#include "pandas/vendored/ujson/lib/ultrajson.h"
+// clang-format off
 #define PY_SSIZE_T_CLEAN
 #include <Python.h>
+#include "pandas/vendored/ujson/lib/ultrajson.h"
+// clang-format on
 
 static int Object_objectAddKey(void *Py_UNUSED(prv), JSOBJ obj, JSOBJ name,
                                JSOBJ value) {

pandas/_libs/tslibs/nattype.pyx

@@ -500,6 +500,8 @@ class NaTType(_NaT):
         --------
         to_timedelta : Convert argument to timedelta.
         Timedelta : Represents a duration, the difference between two dates or times.
+        Timedelta.seconds : Returns the seconds component of the timedelta.
+        Timedelta.microseconds : Returns the microseconds component of the timedelta.
 
         Examples
         --------

pandas/_libs/tslibs/np_datetime.pyx

@@ -176,6 +176,15 @@ class OutOfBoundsDatetime(ValueError):
     """
     Raised when the datetime is outside the range that can be represented.
 
+    This error occurs when attempting to convert or parse a datetime value
+    that exceeds the bounds supported by pandas' internal datetime
+    representation.
+
+    See Also
+    --------
+    to_datetime : Convert argument to datetime.
+    Timestamp : Pandas replacement for python ``datetime.datetime`` object.
+
     Examples
     --------
     >>> pd.to_datetime("08335394550")

pandas/_libs/tslibs/timedeltas.pyx

@@ -1196,6 +1196,8 @@ cdef class _Timedelta(timedelta):
         --------
         to_timedelta : Convert argument to timedelta.
         Timedelta : Represents a duration, the difference between two dates or times.
+        Timedelta.seconds : Returns the seconds component of the timedelta.
+        Timedelta.microseconds : Returns the microseconds component of the timedelta.
 
         Examples
         --------
@@ -1493,6 +1495,7 @@ cdef class _Timedelta(timedelta):
 
         See Also
         --------
+        Timedelta.asm8 : Return a numpy timedelta64 array scalar view.
         numpy.ndarray.view : Returns a view of an array with the same data.
         Timedelta.to_numpy : Converts the Timedelta to a NumPy timedelta64.
         Timedelta.total_seconds : Returns the total duration of the Timedelta

pandas/core/arrays/timedeltas.py

@@ -790,6 +790,19 @@ def to_pytimedelta(self) -> npt.NDArray[np.object_]:
         Returns
         -------
         numpy.ndarray
+            A NumPy ``timedelta64`` object representing the same duration as the
+            original pandas ``Timedelta`` object. The precision of the resulting
+            object is in nanoseconds, which is the default
+            time resolution used by pandas for ``Timedelta`` objects, ensuring
+            high precision for time-based calculations.
+
+        See Also
+        --------
+        to_timedelta : Convert argument to timedelta format.
+        Timedelta : Represents a duration between two dates or times.
+        DatetimeIndex: Index of datetime64 data.
+        Timedelta.components : Return a components namedtuple-like
+                               of a single timedelta.
 
         Examples
         --------
@@ -800,6 +813,14 @@ def to_pytimedelta(self) -> npt.NDArray[np.object_]:
         >>> tdelta_idx.to_pytimedelta()
         array([datetime.timedelta(days=1), datetime.timedelta(days=2),
                datetime.timedelta(days=3)], dtype=object)
+
+        >>> tidx = pd.TimedeltaIndex(data=["1 days 02:30:45", "3 days 04:15:10"])
+        >>> tidx
+        TimedeltaIndex(['1 days 02:30:45', '3 days 04:15:10'],
+               dtype='timedelta64[ns]', freq=None)
+        >>> tidx.to_pytimedelta()
+        array([datetime.timedelta(days=1, seconds=9045),
+                datetime.timedelta(days=3, seconds=15310)], dtype=object)
         """
         return ints_to_pytimedelta(self._ndarray)
 

pandas/errors/__init__.py

@@ -615,6 +615,16 @@ class ClosedFileError(Exception):
     """
     Exception is raised when trying to perform an operation on a closed HDFStore file.
 
+    ``ClosedFileError`` is specific to operations on ``HDFStore`` objects. Once an
+    HDFStore is closed, its resources are no longer available, and any further attempt
+    to access data or perform file operations will raise this exception.
+
+    See Also
+    --------
+    HDFStore.close : Closes the PyTables file handle.
+    HDFStore.open : Opens the file in the specified mode.
+    HDFStore.is_open : Returns a boolean indicating whether the file is open.
+
     Examples
     --------
     >>> store = pd.HDFStore("my-store", "a")  # doctest: +SKIP