DEPR: Period[B] (#53511)

* DEPR: Period[B]

* filter warnings

* xfail

* filter warning

* Change makePeriodIndex to D

* Suppress more specific message

Author: jbrockmendel

doc/source/whatsnew/v2.1.0.rst

@@ -348,6 +348,7 @@ Deprecations
 - Deprecated unused "closed" and "normalize" keywords in the :class:`DatetimeIndex` constructor (:issue:`52628`)
 - Deprecated unused "closed" keyword in the :class:`TimedeltaIndex` constructor (:issue:`52628`)
 - Deprecated logical operation between two non boolean :class:`Series` with different indexes always coercing the result to bool dtype. In a future version, this will maintain the return type of the inputs. (:issue:`52500`, :issue:`52538`)
+- Deprecated :class:`Period` and :class:`PeriodDtype` with ``BDay`` freq, use a :class:`DatetimeIndex` with ``BDay`` freq instead (:issue:`53446`)
 - 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`)

pandas/_libs/tslibs/period.pyx

@@ -107,7 +107,10 @@ from pandas._libs.tslibs.offsets cimport (
     to_offset,
 )
 
-from pandas._libs.tslibs.offsets import INVALID_FREQ_ERR_MSG
+from pandas._libs.tslibs.offsets import (
+    INVALID_FREQ_ERR_MSG,
+    BDay,
+)
 
 cdef:
     enum:
@@ -2812,6 +2815,18 @@ class Period(_Period):
                                      dt.hour, dt.minute, dt.second,
                                      dt.microsecond, 1000*nanosecond, base)
 
+        if isinstance(freq, BDay):
+            # GH#53446
+            import warnings
+
+            from pandas.util._exceptions import find_stack_level
+            warnings.warn(
+                "Period with BDay freq is deprecated and will be removed "
+                "in a future version. Use a DatetimeIndex with BDay freq instead.",
+                FutureWarning,
+                stacklevel=find_stack_level(),
+            )
+
         return cls._from_ordinal(ordinal, freq)
 
 

pandas/_testing/__init__.py

@@ -441,7 +441,8 @@ def makeTimedeltaIndex(
 
 def makePeriodIndex(k: int = 10, name=None, **kwargs) -> PeriodIndex:
     dt = datetime(2000, 1, 1)
-    return pd.period_range(start=dt, periods=k, freq="B", name=name, **kwargs)
+    pi = pd.period_range(start=dt, periods=k, freq="D", name=name, **kwargs)
+    return pi
 
 
 def makeMultiIndex(k: int = 10, names=None, **kwargs):

pandas/core/dtypes/dtypes.py

@@ -42,6 +42,7 @@
     PeriodDtypeBase,
     abbrev_to_npy_unit,
 )
+from pandas._libs.tslibs.offsets import BDay
 from pandas.compat import pa_version_under7p0
 from pandas.errors import PerformanceWarning
 from pandas.util._exceptions import find_stack_level
@@ -966,6 +967,15 @@ def __new__(cls, freq):
         if not isinstance(freq, BaseOffset):
             freq = cls._parse_dtype_strict(freq)
 
+        if isinstance(freq, BDay):
+            # GH#53446
+            warnings.warn(
+                "PeriodDtype[B] is deprecated and will be removed in a future "
+                "version. Use a DatetimeIndex with freq='B' instead",
+                FutureWarning,
+                stacklevel=find_stack_level(),
+            )
+
         try:
             dtype_code = cls._cache_dtypes[freq]
         except KeyError:

pandas/plotting/_matplotlib/timeseries.py

@@ -276,10 +276,22 @@ def maybe_convert_index(ax: Axes, data):
 
         freq_str = _get_period_alias(freq)
 
-        if isinstance(data.index, ABCDatetimeIndex):
-            data = data.tz_localize(None).to_period(freq=freq_str)
-        elif isinstance(data.index, ABCPeriodIndex):
-            data.index = data.index.asfreq(freq=freq_str)
+        import warnings
+
+        with warnings.catch_warnings():
+            # suppress Period[B] deprecation warning
+            # TODO: need to find an alternative to this before the deprecation
+            #  is enforced!
+            warnings.filterwarnings(
+                "ignore",
+                r"PeriodDtype\[B\] is deprecated",
+                category=FutureWarning,
+            )
+
+            if isinstance(data.index, ABCDatetimeIndex):
+                data = data.tz_localize(None).to_period(freq=freq_str)
+            elif isinstance(data.index, ABCPeriodIndex):
+                data.index = data.index.asfreq(freq=freq_str)
     return data
 
 

pandas/tests/arrays/test_datetimelike.py

@@ -2,6 +2,7 @@
 
 import array
 import re
+import warnings
 
 import numpy as np
 import pytest
@@ -48,7 +49,10 @@ def period_index(freqstr):
     the PeriodIndex behavior.
     """
     # TODO: non-monotone indexes; NaTs, different start dates
-    pi = pd.period_range(start=Timestamp("2000-01-01"), periods=100, freq=freqstr)
+    with warnings.catch_warnings():
+        # suppress deprecation of Period[B]
+        warnings.simplefilter("ignore")
+        pi = pd.period_range(start=Timestamp("2000-01-01"), periods=100, freq=freqstr)
     return pi
 
 
@@ -192,6 +196,9 @@ def test_take_fill(self, arr1d):
         result = arr.take([-1, 1], allow_fill=True, fill_value=NaT)
         assert result[0] is NaT
 
+    @pytest.mark.filterwarnings(
+        "ignore:Period with BDay freq is deprecated:FutureWarning"
+    )
     def test_take_fill_str(self, arr1d):
         # Cast str fill_value matching other fill_value-taking methods
         result = arr1d.take([-1, 1], allow_fill=True, fill_value=str(arr1d[-1]))
@@ -745,6 +752,7 @@ def test_astype_object(self, arr1d):
         assert asobj.dtype == "O"
         assert list(asobj) == list(dti)
 
+    @pytest.mark.filterwarnings(r"ignore:PeriodDtype\[B\] is deprecated:FutureWarning")
     def test_to_period(self, datetime_index, freqstr):
         dti = datetime_index
         arr = DatetimeArray(dti)
@@ -999,6 +1007,8 @@ def test_take_fill_valid(self, timedelta_index, fixed_now_ts):
             arr.take([-1, 1], allow_fill=True, fill_value=value)
 
 
+@pytest.mark.filterwarnings(r"ignore:Period with BDay freq is deprecated:FutureWarning")
+@pytest.mark.filterwarnings(r"ignore:PeriodDtype\[B\] is deprecated:FutureWarning")
 class TestPeriodArray(SharedTests):
     index_cls = PeriodIndex
     array_cls = PeriodArray

pandas/tests/base/test_unique.py

@@ -6,6 +6,7 @@
 from pandas.tests.base.common import allow_na_ops
 
 
+@pytest.mark.filterwarnings(r"ignore:PeriodDtype\[B\] is deprecated:FutureWarning")
 def test_unique(index_or_series_obj):
     obj = index_or_series_obj
     obj = np.repeat(obj, range(1, len(obj) + 1))
@@ -27,6 +28,7 @@ def test_unique(index_or_series_obj):
         tm.assert_numpy_array_equal(result, expected)
 
 
+@pytest.mark.filterwarnings(r"ignore:PeriodDtype\[B\] is deprecated:FutureWarning")
 @pytest.mark.parametrize("null_obj", [np.nan, None])
 def test_unique_null(null_obj, index_or_series_obj):
     obj = index_or_series_obj

pandas/tests/base/test_value_counts.py

@@ -19,6 +19,7 @@
 from pandas.tests.base.common import allow_na_ops
 
 
+@pytest.mark.filterwarnings(r"ignore:PeriodDtype\[B\] is deprecated:FutureWarning")
 def test_value_counts(index_or_series_obj):
     obj = index_or_series_obj
     obj = np.repeat(obj, range(1, len(obj) + 1))
@@ -54,6 +55,7 @@ def test_value_counts(index_or_series_obj):
 
 
 @pytest.mark.parametrize("null_obj", [np.nan, None])
+@pytest.mark.filterwarnings(r"ignore:PeriodDtype\[B\] is deprecated:FutureWarning")
 def test_value_counts_null(null_obj, index_or_series_obj):
     orig = index_or_series_obj
     obj = orig.copy()

pandas/tests/dtypes/test_dtypes.py

@@ -445,10 +445,13 @@ def test_construction(self):
     def test_cannot_use_custom_businessday(self):
         # GH#52534
         msg = "CustomBusinessDay cannot be used with Period or PeriodDtype"
+        msg2 = r"PeriodDtype\[B\] is deprecated"
         with pytest.raises(TypeError, match=msg):
-            PeriodDtype("C")
+            with tm.assert_produces_warning(FutureWarning, match=msg2):
+                PeriodDtype("C")
         with pytest.raises(TypeError, match=msg):
-            PeriodDtype(pd.offsets.CustomBusinessDay())
+            with tm.assert_produces_warning(FutureWarning, match=msg2):
+                PeriodDtype(pd.offsets.CustomBusinessDay())
 
     def test_subclass(self):
         a = PeriodDtype("period[D]")

pandas/tests/frame/methods/test_shift.py

@@ -249,20 +249,20 @@ def test_shift_with_periodindex(self, frame_or_series):
         else:
             tm.assert_numpy_array_equal(unshifted.dropna().values, ps.values[:-1])
 
-        shifted2 = ps.shift(1, "B")
-        shifted3 = ps.shift(1, offsets.BDay())
+        shifted2 = ps.shift(1, "D")
+        shifted3 = ps.shift(1, offsets.Day())
         tm.assert_equal(shifted2, shifted3)
-        tm.assert_equal(ps, shifted2.shift(-1, "B"))
+        tm.assert_equal(ps, shifted2.shift(-1, "D"))
 
         msg = "does not match PeriodIndex freq"
         with pytest.raises(ValueError, match=msg):
-            ps.shift(freq="D")
+            ps.shift(freq="W")
 
         # legacy support
-        shifted4 = ps.shift(1, freq="B")
+        shifted4 = ps.shift(1, freq="D")
         tm.assert_equal(shifted2, shifted4)
 
-        shifted5 = ps.shift(1, freq=offsets.BDay())
+        shifted5 = ps.shift(1, freq=offsets.Day())
         tm.assert_equal(shifted5, shifted4)
 
     def test_shift_other_axis(self):
@@ -492,10 +492,10 @@ def test_period_index_frame_shift_with_freq(self, frame_or_series):
         unshifted = shifted.shift(-1, freq="infer")
         tm.assert_equal(unshifted, ps)
 
-        shifted2 = ps.shift(freq="B")
+        shifted2 = ps.shift(freq="D")
         tm.assert_equal(shifted, shifted2)
 
-        shifted3 = ps.shift(freq=offsets.BDay())
+        shifted3 = ps.shift(freq=offsets.Day())
         tm.assert_equal(shifted, shifted3)
 
     def test_datetime_frame_shift_with_freq(self, datetime_frame, frame_or_series):
@@ -524,7 +524,7 @@ def test_datetime_frame_shift_with_freq(self, datetime_frame, frame_or_series):
     def test_period_index_frame_shift_with_freq_error(self, frame_or_series):
         ps = tm.makePeriodFrame()
         ps = tm.get_obj(ps, frame_or_series)
-        msg = "Given freq M does not match PeriodIndex freq B"
+        msg = "Given freq M does not match PeriodIndex freq D"
         with pytest.raises(ValueError, match=msg):
             ps.shift(freq="M")