merge

Author: mcgeestocks

ci/code_checks.sh

@@ -105,16 +105,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas.errors.UnsupportedFunctionCall \
         pandas.test \
         pandas.NaT \
-        pandas.Timestamp.strptime \
-        pandas.Timestamp.time \
-        pandas.Timestamp.timetuple \
-        pandas.Timestamp.timetz \
-        pandas.Timestamp.to_datetime64 \
-        pandas.Timestamp.toordinal \
-        pandas.Timestamp.tzname \
-        pandas.Timestamp.utcoffset \
-        pandas.Timestamp.utctimetuple \
-        pandas.Timestamp.weekday \
         pandas.arrays.TimedeltaArray \
         pandas.Period.asfreq \
         pandas.Period.now \

doc/source/getting_started/install.rst

@@ -216,7 +216,7 @@ pandas is equipped with an exhaustive set of unit tests, covering about 97% of
 the code base as of this writing. To run it on your machine to verify that
 everything is working (and that you have all of the dependencies, soft and hard,
 installed), make sure you have `pytest
-<https://docs.pytest.org/en/latest/>`__ >= 7.0 and `Hypothesis
+<https://docs.pytest.org/en/latest/>`__ >= 7.3.2 and `Hypothesis
 <https://hypothesis.readthedocs.io/en/latest/>`__ >= 6.34.2, then run:
 
 ::

doc/source/whatsnew/v2.0.3.rst

@@ -28,6 +28,7 @@ Bug fixes
 - Bug in :func:`read_csv` when defining ``dtype`` with ``bool[pyarrow]`` for the ``"c"`` and ``"python"`` engines (:issue:`53390`)
 - Bug in :meth:`Series.str.split` and :meth:`Series.str.rsplit` with ``expand=True`` for :class:`ArrowDtype` with ``pyarrow.string`` (:issue:`53532`)
 - Bug in indexing methods (e.g. :meth:`DataFrame.__getitem__`) where taking the entire :class:`DataFrame`/:class:`Series` would raise an ``OverflowError`` when Copy on Write was enabled and the length of the array was over the maximum size a 32-bit integer can hold (:issue:`53616`)
+- Bug when constructing a :class:`DataFrame` with columns of an :class:`ArrowDtype` with a ``pyarrow.dictionary`` type that reindexes the data (:issue:`53617`)
 - Bug when indexing a :class:`DataFrame` or :class:`Series` with an :class:`Index` with a timestamp :class:`ArrowDtype` would raise an ``AttributeError`` (:issue:`53644`)
 
 .. ---------------------------------------------------------------------------

doc/source/whatsnew/v2.1.0.rst

@@ -19,6 +19,7 @@ Enhancements
 Copy-on-Write improvements
 ^^^^^^^^^^^^^^^^^^^^^^^^^^
 
+- :meth:`Series.transform` not respecting Copy-on-Write when ``func`` modifies :class:`Series` inplace (:issue:`53747`)
 - Calling :meth:`Index.values` will now return a read-only NumPy array (:issue:`53704`)
 - Setting a :class:`Series` into a :class:`DataFrame` now creates a lazy instead of a deep copy (:issue:`53142`)
 - The :class:`DataFrame` constructor, when constructing a DataFrame from a dictionary
@@ -193,6 +194,8 @@ If installed, we now require:
 +-----------------+-----------------+----------+---------+
 | pytables        | 3.7.0           |          |    X    |
 +-----------------+-----------------+----------+---------+
+| pytest          | 7.3.2           |          |    X    |
++-----------------+-----------------+----------+---------+
 | python-snappy   | 0.6.1           |          |    X    |
 +-----------------+-----------------+----------+---------+
 | pyxlsb          | 1.0.9           |          |    X    |
@@ -288,6 +291,7 @@ Deprecations
 - Deprecated :func:`value_counts`, use ``pd.Series(obj).value_counts()`` instead (:issue:`47862`)
 - Deprecated :meth:`Series.first` and :meth:`DataFrame.first` (please create a mask and filter using ``.loc`` instead) (:issue:`45908`)
 - Deprecated :meth:`Series.interpolate` and :meth:`DataFrame.interpolate` for object-dtype (:issue:`53631`)
+- Deprecated :meth:`Series.last` and :meth:`DataFrame.last` (please create a mask and filter using ``.loc`` instead) (:issue:`53692`)
 - Deprecated allowing ``downcast`` keyword other than ``None``, ``False``, "infer", or a dict with these as values in :meth:`Series.fillna`, :meth:`DataFrame.fillna` (:issue:`40988`)
 - Deprecated allowing arbitrary ``fill_value`` in :class:`SparseDtype`, in a future version the ``fill_value`` will need to be compatible with the ``dtype.subtype``, either a scalar that can be held by that subtype or ``NaN`` for integer or bool subtypes (:issue:`23124`)
 - Deprecated behavior of :func:`assert_series_equal` and :func:`assert_frame_equal` considering NA-like values (e.g. ``NaN`` vs ``None`` as equivalent) (:issue:`52081`)
@@ -358,12 +362,11 @@ Datetimelike
 ^^^^^^^^^^^^
 - :meth:`DatetimeIndex.map` with ``na_action="ignore"`` now works as expected. (:issue:`51644`)
 - Bug in :func:`date_range` when ``freq`` was a :class:`DateOffset` with ``nanoseconds`` (:issue:`46877`)
-- Bug in :meth:`Timestamp.date`, :meth:`Timestamp.isocalendar` were returning incorrect results for inputs outside those supported by the Python standard library's datetime module (:issue:`53668`)
+- Bug in :meth:`Timestamp.date`, :meth:`Timestamp.isocalendar`, :meth:`Timestamp.timetuple`, and :meth:`Timestamp.toordinal` were returning incorrect results for inputs outside those supported by the Python standard library's datetime module (:issue:`53668`)
 - Bug in :meth:`Timestamp.round` with values close to the implementation bounds returning incorrect results instead of raising ``OutOfBoundsDatetime`` (:issue:`51494`)
 - Bug in :meth:`arrays.DatetimeArray.map` and :meth:`DatetimeIndex.map`, where the supplied callable operated array-wise instead of element-wise (:issue:`51977`)
 - Bug in constructing a :class:`Series` or :class:`DataFrame` from a datetime or timedelta scalar always inferring nanosecond resolution instead of inferring from the input (:issue:`52212`)
 - Bug in parsing datetime strings with weekday but no day e.g. "2023 Sept Thu" incorrectly raising ``AttributeError`` instead of ``ValueError`` (:issue:`52659`)
--
 
 Timedelta
 ^^^^^^^^^
@@ -491,7 +494,6 @@ Reshaping
 - Bug in :meth:`DataFrame.idxmin` and :meth:`DataFrame.idxmax`, where the axis dtype would be lost for empty frames (:issue:`53265`)
 - Bug in :meth:`DataFrame.merge` not merging correctly when having ``MultiIndex`` with single level (:issue:`52331`)
 - Bug in :meth:`DataFrame.stack` losing extension dtypes when columns is a :class:`MultiIndex` and frame contains mixed dtypes (:issue:`45740`)
-- Bug in :meth:`DataFrame.stack` would incorrectly order results when ``sort=True`` and the input had :class:`MultiIndex` levels that were not sorted (:issue:`53636`)
 - Bug in :meth:`DataFrame.transpose` inferring dtype for object column (:issue:`51546`)
 - Bug in :meth:`Series.combine_first` converting ``int64`` dtype to ``float64`` and losing precision on very large integers (:issue:`51764`)
 -

pandas/_libs/tslibs/nattype.pyx

@@ -256,7 +256,16 @@ cdef class _NaT(datetime):
 
     def to_datetime64(self) -> np.datetime64:
         """
-        Return a numpy.datetime64 object with 'ns' precision.
+        Return a numpy.datetime64 object with same precision.
+
+        Examples
+        --------
+        >>> ts = pd.Timestamp(year=2023, month=1, day=1,
+        ...                   hour=10, second=15)
+        >>> ts
+        Timestamp('2023-01-01 10:00:15')
+        >>> ts.to_datetime64()
+        numpy.datetime64('2023-01-01T10:00:15.000000')
         """
         return np.datetime64("NaT", "ns")
 
@@ -429,6 +438,14 @@ class NaTType(_NaT):
         Return the day of the week represented by the date.
 
         Monday == 0 ... Sunday == 6.
+
+        Examples
+        --------
+        >>> ts = pd.Timestamp('2023-01-01')
+        >>> ts
+        Timestamp('2023-01-01  00:00:00')
+        >>> ts.weekday()
+        6
         """,
     )
     isoweekday = _make_nan_func(
@@ -514,13 +531,6 @@ class NaTType(_NaT):
         """,
     )
     # _nat_methods
-    utctimetuple = _make_error_func("utctimetuple", datetime)
-    timetz = _make_error_func("timetz", datetime)
-    timetuple = _make_error_func("timetuple", datetime)
-    time = _make_error_func("time", datetime)
-    toordinal = _make_error_func("toordinal", datetime)
-    tzname = _make_error_func("tzname", datetime)
-    utcoffset = _make_error_func("utcoffset", datetime)
 
     # "fromisocalendar" was introduced in 3.8
     fromisocalendar = _make_error_func("fromisocalendar", datetime)
@@ -570,7 +580,106 @@ class NaTType(_NaT):
         datetime.date(2023, 1, 1)
         """
         )
+    utctimetuple = _make_error_func(
+        "utctimetuple",
+        """
+        Return UTC time tuple, compatible with time.localtime().
+
+        Examples
+        --------
+        >>> ts = pd.Timestamp('2023-01-01 10:00:00', tz='Europe/Brussels')
+        >>> ts
+        Timestamp('2023-01-01 10:00:00+0100', tz='Europe/Brussels')
+        >>> ts.utctimetuple()
+        time.struct_time(tm_year=2023, tm_mon=1, tm_mday=1, tm_hour=9,
+        tm_min=0, tm_sec=0, tm_wday=6, tm_yday=1, tm_isdst=0)
+        """
+        )
+    utcoffset = _make_error_func(
+        "utcoffset",
+        """
+        Return utc offset.
+
+        Examples
+        --------
+        >>> ts = pd.Timestamp('2023-01-01 10:00:00', tz='Europe/Brussels')
+        >>> ts
+        Timestamp('2023-01-01 10:00:00+0100', tz='Europe/Brussels')
+        >>> ts.utcoffset()
+        datetime.timedelta(seconds=3600)
+        """
+        )
+    tzname = _make_error_func(
+        "tzname",
+        """
+        Return time zone name.
+
+        Examples
+        --------
+        >>> ts = pd.Timestamp('2023-01-01 10:00:00', tz='Europe/Brussels')
+        >>> ts
+        Timestamp('2023-01-01 10:00:00+0100', tz='Europe/Brussels')
+        >>> ts.tzname()
+        'CET'
+        """
+        )
+    time = _make_error_func(
+        "time",
+        """
+        Return time object with same time but with tzinfo=None.
+
+        Examples
+        --------
+        >>> ts = pd.Timestamp('2023-01-01 10:00:00')
+        >>> ts
+        Timestamp('2023-01-01 10:00:00')
+        >>> ts.time()
+        datetime.time(10, 0)
+        """,
+        )
+    timetuple = _make_error_func(
+        "timetuple",
+        """
+        Return time tuple, compatible with time.localtime().
+
+        Examples
+        --------
+        >>> ts = pd.Timestamp('2023-01-01 10:00:00')
+        >>> ts
+        Timestamp('2023-01-01 10:00:00')
+        >>> ts.timetuple()
+        time.struct_time(tm_year=2023, tm_mon=1, tm_mday=1,
+        tm_hour=10, tm_min=0, tm_sec=0, tm_wday=6, tm_yday=1, tm_isdst=-1)
+        """
+        )
+    timetz = _make_error_func(
+        "timetz",
+        """
+        Return time object with same time and tzinfo.
+
+        Examples
+        --------
+        >>> ts = pd.Timestamp('2023-01-01 10:00:00', tz='Europe/Brussels')
+        >>> ts
+        Timestamp('2023-01-01 10:00:00+0100', tz='Europe/Brussels')
+        >>> ts.timetz()
+        datetime.time(10, 0, tzinfo=<DstTzInfo 'Europe/Brussels' CET+1:00:00 STD>)
+        """
+        )
+    toordinal = _make_error_func(
+        "toordinal",
+        """
+        Return proleptic Gregorian ordinal. January 1 of year 1 is day 1.
 
+        Examples
+        --------
+        >>> ts = pd.Timestamp('2023-01-01 10:00:50')
+        >>> ts
+        Timestamp('2023-01-01 10:00:50')
+        >>> ts.toordinal()
+        738521
+        """
+        )
     ctime = _make_error_func(
         "ctime",
         """
@@ -612,6 +721,12 @@ class NaTType(_NaT):
         Timestamp.strptime(string, format)
 
         Function is not implemented. Use pd.to_datetime().
+
+        Examples
+        --------
+        >>> pd.Timestamp.strptime("2023-01-01", "%d/%m/%y")
+        Traceback (most recent call last):
+        NotImplementedError
         """,
     )
 

pandas/_libs/tslibs/period.pyx

@@ -1917,7 +1917,8 @@ cdef class _Period(PeriodMixin):
         Parameters
         ----------
         freq : str, BaseOffset
-            The desired frequency.
+            The desired frequency. If passing a `str`, it needs to be a
+            valid :ref:`period alias <timeseries.period_aliases>`.
         how : {'E', 'S', 'end', 'start'}, default 'end'
             Start or end of the timespan.