Merge branch 'main' into refactor-io-sql-execute

Author: gmcrocetti

doc/source/user_guide/enhancingperf.rst

@@ -427,7 +427,7 @@ prefer that Numba throw an error if it cannot compile a function in a way that
 speeds up your code, pass Numba the argument
 ``nopython=True`` (e.g.  ``@jit(nopython=True)``). For more on
 troubleshooting Numba modes, see the `Numba troubleshooting page
-<https://numba.pydata.org/numba-doc/latest/user/troubleshoot.html#the-compiled-code-is-too-slow>`__.
+<https://numba.readthedocs.io/en/stable/user/troubleshoot.html>`__.
 
 Using ``parallel=True`` (e.g. ``@jit(parallel=True)``) may result in a ``SIGABRT`` if the threading layer leads to unsafe
 behavior. You can first `specify a safe threading layer <https://numba.readthedocs.io/en/stable/user/threading-layer.html#selecting-a-threading-layer-for-safe-parallel-execution>`__

doc/source/user_guide/groupby.rst

@@ -418,7 +418,7 @@ You can also include the grouping columns if you want to operate on them.
 
 .. note::
 
-   The ``groupby`` operation in Pandas drops the ``name`` field of the columns Index object
+   The ``groupby`` operation in pandas drops the ``name`` field of the columns Index object
    after the operation. This change ensures consistency in syntax between different
    column selection methods within groupby operations.
 

doc/source/user_guide/io.rst

@@ -990,7 +990,7 @@ Thousand separators
 
 For large numbers that have been written with a thousands separator, you can
 set the ``thousands`` keyword to a string of length 1 so that integers will be parsed
-correctly:
+correctly.
 
 By default, numbers with a thousands separator will be parsed as strings:
 

doc/source/user_guide/merging.rst

@@ -586,7 +586,7 @@ A string argument to ``indicator`` will use the value as the name for the indica
 Overlapping value columns
 ~~~~~~~~~~~~~~~~~~~~~~~~~
 
-The merge ``suffixes`` argument takes a tuple of list of strings to append to
+The merge ``suffixes`` argument takes a tuple or list of strings to append to
 overlapping column names in the input :class:`DataFrame` to disambiguate the result
 columns:
 
@@ -979,7 +979,7 @@ nearest key rather than equal keys. For each row in the ``left`` :class:`DataFra
 the last row in the ``right`` :class:`DataFrame` are selected where the ``on`` key is less
 than the left's key. Both :class:`DataFrame` must be sorted by the key.
 
-Optionally an :func:`merge_asof` can perform a group-wise merge by matching the
+Optionally :func:`merge_asof` can perform a group-wise merge by matching the
 ``by`` key in addition to the nearest match on the ``on`` key.
 
 .. ipython:: python

doc/source/user_guide/scale.rst

@@ -5,7 +5,7 @@ Scaling to large datasets
 *************************
 
 pandas provides data structures for in-memory analytics, which makes using pandas
-to analyze datasets that are larger than memory datasets somewhat tricky. Even datasets
+to analyze datasets that are larger than memory somewhat tricky. Even datasets
 that are a sizable fraction of memory become unwieldy, as some pandas operations need
 to make intermediate copies.
 

doc/source/user_guide/timeseries.rst

@@ -1580,7 +1580,7 @@ the pandas objects.
    ts = ts[:5]
    ts.shift(1)
 
-The ``shift`` method accepts an ``freq`` argument which can accept a
+The ``shift`` method accepts a ``freq`` argument which can accept a
 ``DateOffset`` class or other ``timedelta``-like object or also an
 :ref:`offset alias <timeseries.offset_aliases>`.
 
@@ -2570,7 +2570,7 @@ because daylight savings time (DST) in a local time zone causes some times to oc
 twice within one day ("clocks fall back"). The following options are available:
 
 * ``'raise'``: Raises a ``ValueError`` (the default behavior)
-* ``'infer'``: Attempt to determine the correct offset base on the monotonicity of the timestamps
+* ``'infer'``: Attempt to determine the correct offset based on the monotonicity of the timestamps
 * ``'NaT'``: Replaces ambiguous times with ``NaT``
 * ``bool``: ``True`` represents a DST time, ``False`` represents non-DST time. An array-like of ``bool`` values is supported for a sequence of times.
 

doc/source/whatsnew/v3.0.0.rst

@@ -793,6 +793,7 @@ Styler
 Other
 ^^^^^
 - Bug in :class:`DataFrame` when passing a ``dict`` with a NA scalar and ``columns`` that would always return ``np.nan`` (:issue:`57205`)
+- Bug in :class:`Series` ignoring errors when trying to convert :class:`Series` input data to the given ``dtype`` (:issue:`60728`)
 - Bug in :func:`eval` on :class:`ExtensionArray` on including division ``/`` failed with a ``TypeError``. (:issue:`58748`)
 - Bug in :func:`eval` where the names of the :class:`Series` were not preserved when using ``engine="numexpr"``. (:issue:`10239`)
 - Bug in :func:`eval` with ``engine="numexpr"`` returning unexpected result for float division. (:issue:`59736`)

pandas/_config/config.py

@@ -141,6 +141,10 @@ def get_option(pat: str) -> Any:
     """
     Retrieve the value of the specified option.
 
+    This method allows users to query the current value of a given option
+    in the pandas configuration system. Options control various display,
+    performance, and behavior-related settings within pandas.
+
     Parameters
     ----------
     pat : str
@@ -429,6 +433,11 @@ def option_context(*args) -> Generator[None]:
     """
     Context manager to temporarily set options in a ``with`` statement.
 
+    This method allows users to set one or more pandas options temporarily
+    within a controlled block. The previous options' values are restored
+    once the block is exited. This is useful when making temporary adjustments
+    to pandas' behavior without affecting the global state.
+
     Parameters
     ----------
     *args : str | object

pandas/_libs/tslibs/period.pyx

@@ -2842,6 +2842,11 @@ class Period(_Period):
     """
     Represents a period of time.
 
+    A `Period` represents a specific time span rather than a point in time.
+    Unlike `Timestamp`, which represents a single instant, a `Period` defines a
+    duration, such as a month, quarter, or year. The exact representation is
+    determined by the `freq` parameter.
+
     Parameters
     ----------
     value : Period, str, datetime, date or pandas.Timestamp, default None

pandas/core/construction.py

@@ -81,6 +81,10 @@ def array(
     """
     Create an array.
 
+    This method constructs an array using pandas extension types when possible.
+    If `dtype` is specified, it determines the type of array returned. Otherwise,
+    pandas attempts to infer the appropriate dtype based on `data`.
+
     Parameters
     ----------
     data : Sequence of objects