DEPR offsets: rename ‘Y’ to ‘YE'

doc/source/user_guide/timeseries.rst

@@ -889,7 +889,7 @@ into ``freq`` keyword arguments. The available date offsets and associated frequ
     :class:`~pandas.tseries.offsets.BQuarterEnd`, ``'BQ``, "business quarter end"
     :class:`~pandas.tseries.offsets.BQuarterBegin`, ``'BQS'``, "business quarter begin"
     :class:`~pandas.tseries.offsets.FY5253Quarter`, ``'REQ'``, "retail (aka 52-53 week) quarter"
-    :class:`~pandas.tseries.offsets.YearEnd`, ``'Y'``, "calendar year end"
+    :class:`~pandas.tseries.offsets.YearEnd`, ``'YE'``, "calendar year end"
     :class:`~pandas.tseries.offsets.YearBegin`, ``'YS'`` or ``'BYS'``,"calendar year begin"
     :class:`~pandas.tseries.offsets.BYearEnd`, ``'BY'``, "business year end"
     :class:`~pandas.tseries.offsets.BYearBegin`, ``'BYS'``, "business year begin"
@@ -1252,7 +1252,7 @@ frequencies. We will refer to these aliases as *offset aliases*.
     "BQ", "business quarter end frequency"
     "QS", "quarter start frequency"
     "BQS", "business quarter start frequency"
-    "Y", "year end frequency"
+    "YE", "year end frequency"
     "BY", "business year end frequency"
     "YS", "year start frequency"
     "BYS", "business year start frequency"
@@ -1379,18 +1379,18 @@ For some frequencies you can specify an anchoring suffix:
     "(B)Q(E)(S)\-SEP", "quarterly frequency, year ends in September"
     "(B)Q(E)(S)\-OCT", "quarterly frequency, year ends in October"
     "(B)Q(E)(S)\-NOV", "quarterly frequency, year ends in November"
-    "(B)Y(S)\-DEC", "annual frequency, anchored end of December. Same as 'Y'"
-    "(B)Y(S)\-JAN", "annual frequency, anchored end of January"
-    "(B)Y(S)\-FEB", "annual frequency, anchored end of February"
-    "(B)Y(S)\-MAR", "annual frequency, anchored end of March"
-    "(B)Y(S)\-APR", "annual frequency, anchored end of April"
-    "(B)Y(S)\-MAY", "annual frequency, anchored end of May"
-    "(B)Y(S)\-JUN", "annual frequency, anchored end of June"
-    "(B)Y(S)\-JUL", "annual frequency, anchored end of July"
-    "(B)Y(S)\-AUG", "annual frequency, anchored end of August"
-    "(B)Y(S)\-SEP", "annual frequency, anchored end of September"
-    "(B)Y(S)\-OCT", "annual frequency, anchored end of October"
-    "(B)Y(S)\-NOV", "annual frequency, anchored end of November"
+    "(B)Y(E)(S)\-DEC", "annual frequency, anchored end of December. Same as 'YE'"
+    "(B)Y(E)(S)\-JAN", "annual frequency, anchored end of January"
+    "(B)Y(E)(S)\-FEB", "annual frequency, anchored end of February"
+    "(B)Y(E)(S)\-MAR", "annual frequency, anchored end of March"
+    "(B)Y(E)(S)\-APR", "annual frequency, anchored end of April"
+    "(B)Y(E)(S)\-MAY", "annual frequency, anchored end of May"
+    "(B)Y(E)(S)\-JUN", "annual frequency, anchored end of June"
+    "(B)Y(E)(S)\-JUL", "annual frequency, anchored end of July"
+    "(B)Y(E)(S)\-AUG", "annual frequency, anchored end of August"
+    "(B)Y(E)(S)\-SEP", "annual frequency, anchored end of September"
+    "(B)Y(E)(S)\-OCT", "annual frequency, anchored end of October"
+    "(B)Y(E)(S)\-NOV", "annual frequency, anchored end of November"
 
 These can be used as arguments to ``date_range``, ``bdate_range``, constructors
 for ``DatetimeIndex``, as well as various other timeseries-related functions
@@ -1686,7 +1686,7 @@ the end of the interval.
 .. warning::
 
     The default values for ``label`` and ``closed`` is '**left**' for all
-    frequency offsets except for 'ME', 'Y', 'QE', 'BME', 'BY', 'BQ', and 'W'
+    frequency offsets except for 'ME', 'YE', 'QE', 'BME', 'BY', 'BQ', and 'W'
     which all have a default of 'right'.
 
     This might unintendedly lead to looking ahead, where the value for a later

doc/source/whatsnew/v2.2.0.rst

@@ -232,29 +232,14 @@ Other API changes
 Deprecations
 ~~~~~~~~~~~~
 
-Deprecate aliases ``M`` and ``Q`` in favour of ``ME`` and ``QE`` for offsets
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Deprecate aliases ``M``, ``Q``, and ``Y`` in favour of ``ME``, ``QE``, and ``YE`` for offsets
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-The alias ``M`` is deprecated in favour of ``ME`` for offsets, please use ``ME`` for "month end" instead of ``M`` (:issue:`9586`)
+Deprecated the following frequency aliases (:issue:`9586`):
 
-For example:
-
-*Previous behavior*:
-
-.. code-block:: ipython
-
-    In [7]: pd.date_range('2020-01-01', periods=3, freq='M')
-    Out [7]:
-    DatetimeIndex(['2020-01-31', '2020-02-29', '2020-03-31'],
-                  dtype='datetime64[ns]', freq='M')
-
-*Future behavior*:
-
-.. ipython:: python
-
-    pd.date_range('2020-01-01', periods=3, freq='ME')
-
-The alias ``Q`` is deprecated in favour of ``QE`` for offsets, please use ``QE`` for "quarter end" instead of ``Q`` (:issue:`9586`)
+- ``M`` (month end) has been renamed ``ME`` for offsets
+- ``Q`` (quarter end) has been renamed ``QE`` for offsets
+- ``Y`` (year end) has been renamed ``YE`` for offsets
 
 For example:
 

pandas/_libs/tslibs/dtypes.pyx

@@ -214,6 +214,19 @@ OFFSET_TO_PERIOD_FREQSTR: dict = {
     "QE-SEP": "Q-SEP",
     "QE-OCT": "Q-OCT",
     "QE-NOV": "Q-NOV",
+    "YE": "Y",
+    "YE-DEC": "Y-DEC",
+    "YE-JAN": "Y-JAN",
+    "YE-FEB": "Y-FEB",
+    "YE-MAR": "Y-MAR",
+    "YE-APR": "Y-APR",
+    "YE-MAY": "Y-MAY",
+    "YE-JUN": "Y-JUN",
+    "YE-JUL": "Y-JUL",
+    "YE-AUG": "Y-AUG",
+    "YE-SEP": "Y-SEP",
+    "YE-OCT": "Y-OCT",
+    "YE-NOV": "Y-NOV",
     "W": "W",
     "ME": "M",
     "Y": "Y",
@@ -236,6 +249,32 @@ OFFSET_DEPR_FREQSTR: dict[str, str]= {
     "Q-SEP": "QE-SEP",
     "Q-OCT": "QE-OCT",
     "Q-NOV": "QE-NOV",
+    "Y": "YE",
+    "Y-DEC": "YE-DEC",
+    "Y-JAN": "YE-JAN",
+    "Y-FEB": "YE-FEB",
+    "Y-MAR": "YE-MAR",
+    "Y-APR": "YE-APR",
+    "Y-MAY": "YE-MAY",
+    "Y-JUN": "YE-JUN",
+    "Y-JUL": "YE-JUL",
+    "Y-AUG": "YE-AUG",
+    "Y-SEP": "YE-SEP",
+    "Y-OCT": "YE-OCT",
+    "Y-NOV": "YE-NOV",
+    "A": "YE",
+    "A-DEC": "YE-DEC",
+    "A-JAN": "YE-JAN",
+    "A-FEB": "YE-FEB",
+    "A-MAR": "YE-MAR",
+    "A-APR": "YE-APR",
+    "A-MAY": "YE-MAY",
+    "A-JUN": "YE-JUN",
+    "A-JUL": "YE-JUL",
+    "A-AUG": "YE-AUG",
+    "A-SEP": "YE-SEP",
+    "A-OCT": "YE-OCT",
+    "A-NOV": "YE-NOV",
 }
 cdef dict c_OFFSET_TO_PERIOD_FREQSTR = OFFSET_TO_PERIOD_FREQSTR
 cdef dict c_OFFSET_DEPR_FREQSTR = OFFSET_DEPR_FREQSTR

pandas/_libs/tslibs/offsets.pyx

@@ -2518,7 +2518,7 @@ cdef class YearEnd(YearOffset):
     """
 
     _default_month = 12
-    _prefix = "Y"
+    _prefix = "YE"
     _day_opt = "end"
 
     cdef readonly:
@@ -4562,7 +4562,7 @@ prefix_mapping = {
     offset._prefix: offset
     for offset in [
         YearBegin,  # 'YS'
-        YearEnd,  # 'Y'
+        YearEnd,  # 'YE'
         BYearBegin,  # 'BYS'
         BYearEnd,  # 'BY'
         BusinessDay,  # 'B'
@@ -4604,7 +4604,7 @@ _lite_rule_alias = {
     "W": "W-SUN",
     "QE": "QE-DEC",
 
-    "Y": "Y-DEC",      # YearEnd(month=12),
+    "YE": "YE-DEC",      # YearEnd(month=12),
     "YS": "YS-JAN",    # YearBegin(month=1),
     "BY": "BY-DEC",    # BYearEnd(month=12),
     "BYS": "BYS-JAN",  # BYearBegin(month=1),
@@ -4637,6 +4637,7 @@ _dont_uppercase = {
     "qe-sep",
     "qe-oct",
     "qe-nov",
+    "ye",
 }
 
 
@@ -4762,6 +4763,13 @@ cpdef to_offset(freq, bint is_period=False):
                         f"instead of \'{name}\'"
                     )
                 elif is_period is True and name in c_OFFSET_DEPR_FREQSTR:
+                    if name.startswith("A"):
+                        warnings.warn(
+                            f"\'{name}\' will be deprecated, please use "
+                            f"\'{c_DEPR_ABBREVS.get(name)}\' instead.",
+                            FutureWarning,
+                            stacklevel=find_stack_level(),
+                        )
                     name = c_OFFSET_DEPR_FREQSTR.get(name)
 
                 if sep != "" and not sep.isspace():

pandas/core/arrays/datetimes.py

@@ -1520,7 +1520,7 @@ def isocalendar(self) -> DataFrame:
         Examples
         --------
         >>> datetime_series = pd.Series(
-        ...     pd.date_range("2000-01-01", periods=3, freq="Y")
+        ...     pd.date_range("2000-01-01", periods=3, freq="YE")
         ... )
         >>> datetime_series
         0   2000-12-31
@@ -2058,10 +2058,10 @@ def isocalendar(self) -> DataFrame:
         This method is available on Series with datetime values under
         the ``.dt`` accessor, and directly on DatetimeIndex.
 
-        >>> idx = pd.date_range("2012-01-01", "2015-01-01", freq="Y")
+        >>> idx = pd.date_range("2012-01-01", "2015-01-01", freq="YE")
         >>> idx
         DatetimeIndex(['2012-12-31', '2013-12-31', '2014-12-31'],
-                      dtype='datetime64[ns]', freq='Y-DEC')
+                      dtype='datetime64[ns]', freq='YE-DEC')
         >>> idx.is_leap_year
         array([ True, False, False])
 

pandas/core/generic.py

@@ -9199,11 +9199,11 @@ def resample(
                 Use frame.T.resample(...) instead.
         closed : {{'right', 'left'}}, default None
             Which side of bin interval is closed. The default is 'left'
-            for all frequency offsets except for 'ME', 'Y', 'Q', 'BME',
+            for all frequency offsets except for 'ME', 'YE', 'QE', 'BME',
             'BA', 'BQ', and 'W' which all have a default of 'right'.
         label : {{'right', 'left'}}, default None
             Which bin edge label to label bucket with. The default is 'left'
-            for all frequency offsets except for 'ME', 'Y', 'Q', 'BME',
+            for all frequency offsets except for 'ME', 'YE', 'QE', 'BME',
             'BA', 'BQ', and 'W' which all have a default of 'right'.
         convention : {{'start', 'end', 's', 'e'}}, default 'start'
             For `PeriodIndex` only, controls whether to use the start or

pandas/core/resample.py

@@ -2130,7 +2130,7 @@ def __init__(
         else:
             freq = to_offset(freq)
 
-        end_types = {"ME", "Y", "QE", "BME", "BY", "BQ", "W"}
+        end_types = {"ME", "YE", "QE", "BME", "BY", "BQ", "W"}
         rule = freq.rule_code
         if rule in end_types or ("-" in rule and rule[: rule.find("-")] in end_types):
             if closed is None:
@@ -2330,7 +2330,7 @@ def _adjust_bin_edges(
             "BQ",
             "BY",
             "QE",
-            "Y",
+            "YE",
             "W",
         ):
             # If the right end-point is on the last day of the month, roll forwards

pandas/core/series.py

@@ -5785,7 +5785,7 @@ def to_timestamp(
         2023-01-31    1
         2024-01-31    2
         2025-01-31    3
-        Freq: Y-JAN, dtype: int64
+        Freq: YE-JAN, dtype: int64
         """
         if not isinstance(self.index, PeriodIndex):
             raise TypeError(f"unsupported Type {type(self.index).__name__}")

pandas/tests/arithmetic/test_datetime64.py

@@ -1606,7 +1606,7 @@ def test_dt64_series_arith_overflow(self):
         # GH#12534, fixed by GH#19024
         dt = Timestamp("1700-01-31")
         td = Timedelta("20000 Days")
-        dti = date_range("1949-09-30", freq="100Y", periods=4)
+        dti = date_range("1949-09-30", freq="100YE", periods=4)
         ser = Series(dti)
         msg = "Overflow in int64 addition"
         with pytest.raises(OverflowError, match=msg):

pandas/tests/arrays/period/test_arrow_compat.py

@@ -33,7 +33,7 @@ def test_arrow_extension_type():
     "data, freq",
     [
         (pd.date_range("2017", periods=3), "D"),
-        (pd.date_range("2017", periods=3, freq="Y"), "Y-DEC"),
+        (pd.date_range("2017", periods=3, freq="YE"), "Y-DEC"),
     ],
 )
 def test_arrow_array(data, freq):

pandas/tests/arrays/test_datetimelike.py

@@ -30,7 +30,7 @@
 
 
 # TODO: more freq variants
-@pytest.fixture(params=["D", "B", "W", "ME", "QE", "Y"])
+@pytest.fixture(params=["D", "B", "W", "ME", "QE", "YE"])
 def freqstr(request):
     """Fixture returning parametrized frequency in string format."""
     return request.param

pandas/tests/arrays/test_datetimes.py

@@ -748,10 +748,14 @@ def test_iter_zoneinfo_fold(self, tz):
             ("2ME", "2M"),
             ("2QE", "2Q"),
             ("2QE-SEP", "2Q-SEP"),
+            ("1YE", "1Y"),
+            ("2YE-MAR", "2Y-MAR"),
+            ("1YE", "1A"),
+            ("2YE-MAR", "2A-MAR"),
         ],
     )
-    def test_date_range_frequency_M_Q_deprecated(self, freq, freq_depr):
-        # GH#9586
+    def test_date_range_frequency_M_Q_Y_A_deprecated(self, freq, freq_depr):
+        # GH#9586, GH#54275
         depr_msg = (
             f"'{freq_depr[1:]}' will be deprecated, please use '{freq[1:]}' instead."
         )

pandas/tests/frame/methods/test_asfreq.py

@@ -240,9 +240,13 @@ def test_asfreq_2ME(self, freq, freq_half):
             ("2ME", "2M"),
             ("2QE", "2Q"),
             ("2QE-SEP", "2Q-SEP"),
+            ("1YE", "1Y"),
+            ("2YE-MAR", "2Y-MAR"),
+            ("1YE", "1A"),
+            ("2YE-MAR", "2A-MAR"),
         ],
     )
-    def test_asfreq_frequency_M_Q_deprecated(self, freq, freq_depr):
+    def test_asfreq_frequency_M_Q_Y_A_deprecated(self, freq, freq_depr):
         # GH#9586
         depr_msg = (
             f"'{freq_depr[1:]}' will be deprecated, please use '{freq[1:]}' instead."

pandas/tests/frame/methods/test_reindex.py

@@ -37,7 +37,7 @@ def test_dti_set_index_reindex_datetimeindex(self):
         # GH#6631
         df = DataFrame(np.random.default_rng(2).random(6))
         idx1 = date_range("2011/01/01", periods=6, freq="ME", tz="US/Eastern")
-        idx2 = date_range("2013", periods=6, freq="Y", tz="Asia/Tokyo")
+        idx2 = date_range("2013", periods=6, freq="YE", tz="Asia/Tokyo")
 
         df = df.set_index(idx1)
         tm.assert_index_equal(df.index, idx1)

pandas/tests/frame/methods/test_to_timestamp.py

@@ -16,7 +16,7 @@
 import pandas._testing as tm
 
 
-def _get_with_delta(delta, freq="Y-DEC"):
+def _get_with_delta(delta, freq="YE-DEC"):
     return date_range(
         to_datetime("1/1/2001") + delta,
         to_datetime("12/31/2009") + delta,
@@ -36,7 +36,7 @@ def test_to_timestamp(self, frame_or_series):
         obj["mix"] = "a"
         obj = tm.get_obj(obj, frame_or_series)
 
-        exp_index = date_range("1/1/2001", end="12/31/2009", freq="Y-DEC")
+        exp_index = date_range("1/1/2001", end="12/31/2009", freq="YE-DEC")
         exp_index = exp_index + Timedelta(1, "D") - Timedelta(1, "ns")
         result = obj.to_timestamp("D", "end")
         tm.assert_index_equal(result.index, exp_index)
@@ -82,7 +82,7 @@ def test_to_timestamp_columns(self):
         # columns
         df = df.T
 
-        exp_index = date_range("1/1/2001", end="12/31/2009", freq="Y-DEC")
+        exp_index = date_range("1/1/2001", end="12/31/2009", freq="YE-DEC")
         exp_index = exp_index + Timedelta(1, "D") - Timedelta(1, "ns")
         result = df.to_timestamp("D", "end", axis=1)
         tm.assert_index_equal(result.columns, exp_index)

pandas/tests/frame/test_repr.py

@@ -357,7 +357,7 @@ def test_repr_np_nat_with_object(self, arg, box, expected):
         assert result == expected
 
     def test_frame_datetime64_pre1900_repr(self):
-        df = DataFrame({"year": date_range("1/1/1700", periods=50, freq="Y-DEC")})
+        df = DataFrame({"year": date_range("1/1/1700", periods=50, freq="YE-DEC")})
         # it works!
         repr(df)
 

pandas/tests/groupby/test_timegrouper.py

@@ -192,7 +192,7 @@ def test_timegrouper_with_reg_groups(self):
             ).set_index(["Date", "Buyer"])
 
             msg = "The default value of numeric_only"
-            result = df.groupby([Grouper(freq="Y"), "Buyer"]).sum(numeric_only=True)
+            result = df.groupby([Grouper(freq="YE"), "Buyer"]).sum(numeric_only=True)
             tm.assert_frame_equal(result, expected)
 
             expected = DataFrame(
@@ -335,7 +335,7 @@ def test_timegrouper_with_reg_groups(self):
             )
             tm.assert_frame_equal(result, expected)
 
-    @pytest.mark.parametrize("freq", ["D", "ME", "Y", "QE-APR"])
+    @pytest.mark.parametrize("freq", ["D", "ME", "YE", "QE-APR"])
     def test_timegrouper_with_reg_groups_freq(self, freq):
         # GH 6764 multiple grouping with/without sort
         df = DataFrame(
@@ -906,7 +906,7 @@ def test_groupby_apply_timegrouper_with_nat_apply_squeeze(
 
         # We need to create a GroupBy object with only one non-NaT group,
         #  so use a huge freq so that all non-NaT dates will be grouped together
-        tdg = Grouper(key="Date", freq="100Y")
+        tdg = Grouper(key="Date", freq="100YE")
         gb = df.groupby(tdg)
 
         # check that we will go through the singular_series path