Merge branch 'main' into autofilter-feature

Author: antznette1

doc/source/whatsnew/v3.0.0.rst

@@ -156,6 +156,8 @@ All warnings for upcoming changes in pandas will have the base class :class:`pan
 
 Other enhancements
 ^^^^^^^^^^^^^^^^^^
+- :class:`pandas.NamedAgg` now supports passing ``*args`` and ``**kwargs``
+  to calls of ``aggfunc`` (:issue:`58283`)
 - :func:`pandas.merge` propagates the ``attrs`` attribute to the result if all
   inputs have identical ``attrs``, as has so far already been the case for
   :func:`pandas.concat`.
@@ -1122,6 +1124,7 @@ I/O
 - Bug in :meth:`read_csv` for the ``c`` and ``python`` engines where parsing numbers with large exponents caused overflows. Now, numbers with large positive exponents are parsed as ``inf`` or ``-inf`` depending on the sign of the mantissa, while those with large negative exponents are parsed as ``0.0`` (:issue:`62617`, :issue:`38794`, :issue:`62740`)
 - Bug in :meth:`read_csv` raising ``TypeError`` when ``index_col`` is specified and ``na_values`` is a dict containing the key ``None``. (:issue:`57547`)
 - Bug in :meth:`read_csv` raising ``TypeError`` when ``nrows`` and ``iterator`` are specified without specifying a ``chunksize``. (:issue:`59079`)
+- Bug in :meth:`read_csv` where it did not appropriately skip a line when instructed, causing Empty Data Error (:issue:`62739`)
 - Bug in :meth:`read_csv` where the order of the ``na_values`` makes an inconsistency when ``na_values`` is a list non-string values. (:issue:`59303`)
 - Bug in :meth:`read_csv` with ``c`` and ``python`` engines reading big integers as strings. Now reads them as python integers. (:issue:`51295`)
 - Bug in :meth:`read_csv` with ``engine="c"`` reading large float numbers with preceding integers as strings. Now reads them as floats. (:issue:`51295`)

pandas/core/apply.py

@@ -1745,7 +1745,13 @@ def reconstruct_func(
     >>> reconstruct_func("min")
     (False, 'min', None, None)
     """
-    relabeling = func is None and is_multi_agg_with_relabel(**kwargs)
+    from pandas.core.groupby.generic import NamedAgg
+
+    relabeling = func is None and (
+        is_multi_agg_with_relabel(**kwargs)
+        or any(isinstance(v, NamedAgg) for v in kwargs.values())
+    )
+
     columns: tuple[str, ...] | None = None
     order: npt.NDArray[np.intp] | None = None
 
@@ -1766,9 +1772,22 @@ def reconstruct_func(
         # "Callable[..., Any] | str | list[Callable[..., Any] | str] |
         # MutableMapping[Hashable, Callable[..., Any] | str | list[Callable[..., Any] |
         # str]] | None")
+        converted_kwargs = {}
+        for key, val in kwargs.items():
+            if isinstance(val, NamedAgg):
+                aggfunc = val.aggfunc
+                if val.args or val.kwargs:
+                    aggfunc = lambda x, func=aggfunc, a=val.args, kw=val.kwargs: func(
+                        x, *a, **kw
+                    )
+                converted_kwargs[key] = (val.column, aggfunc)
+            else:
+                converted_kwargs[key] = val
+
         func, columns, order = normalize_keyword_aggregation(  # type: ignore[assignment]
-            kwargs
+            converted_kwargs
         )
+
     assert func is not None
 
     return relabeling, func, columns, order

pandas/core/arrays/boolean.py

@@ -45,10 +45,15 @@ class BooleanDtype(BaseMaskedDtype):
     """
     Extension dtype for boolean data.
 
+    This is a pandas Extension dtype for boolean data with support for
+    missing values. BooleanDtype is the dtype companion to :class:`.BooleanArray`,
+    which implements Kleene logic (sometimes called three-value logic) for
+    logical operations. See :ref:`boolean.kleene` for more.
+
     .. warning::
 
-       BooleanDtype is considered experimental. The implementation and
-       parts of the API may change without warning.
+        BooleanDtype is considered experimental. The implementation and
+        parts of the API may change without warning.
 
     Attributes
     ----------
@@ -60,12 +65,24 @@ class BooleanDtype(BaseMaskedDtype):
 
     See Also
     --------
+    arrays.BooleanArray : Array of boolean (True/False) data with missing values.
+    Int64Dtype : Extension dtype for int64 integer data.
     StringDtype : Extension dtype for string data.
 
     Examples
     --------
     >>> pd.BooleanDtype()
     BooleanDtype
+
+    >>> pd.array([True, False, None], dtype=pd.BooleanDtype())
+    <BooleanArray>
+    [True, False, <NA>]
+    Length: 3, dtype: boolean
+
+    >>> pd.array([True, False, None], dtype="boolean")
+    <BooleanArray>
+    [True, False, <NA>]
+    Length: 3, dtype: boolean
     """
 
     name: ClassVar[str] = "boolean"