Revert "DEPR: is_all_dates (pandas-dev#36697)"

This reverts commit 90a6135.

Author: simonjayhawkins

doc/source/whatsnew/v1.2.0.rst

@@ -524,8 +524,6 @@ Deprecations
 - Deprecated indexing :class:`DataFrame` rows with a single datetime-like string as ``df[string]``
   (given the ambiguity whether it is indexing the rows or selecting a column), use
   ``df.loc[string]`` instead (:issue:`36179`)
-- Deprecated casting an object-dtype index of ``datetime`` objects to :class:`.DatetimeIndex` in the :class:`Series` constructor (:issue:`23598`)
-- Deprecated :meth:`Index.is_all_dates` (:issue:`27744`)
 - The default value of ``regex`` for :meth:`Series.str.replace` will change from ``True`` to ``False`` in a future release. In addition, single character regular expressions will *not* be treated as literal strings when ``regex=True`` is set. (:issue:`24804`)
 - Deprecated automatic alignment on comparison operations between :class:`DataFrame` and :class:`Series`, do ``frame, ser = frame.align(ser, axis=1, copy=False)`` before e.g. ``frame == ser`` (:issue:`28759`)
 - :meth:`Rolling.count` with ``min_periods=None`` will default to the size of the window in a future version (:issue:`31302`)

pandas/core/generic.py

@@ -9466,13 +9466,7 @@ def truncate(
 
         # if we have a date index, convert to dates, otherwise
         # treat like a slice
-        if ax._is_all_dates:
-            if is_object_dtype(ax.dtype):
-                warnings.warn(
-                    "Treating object-dtype Index of date objects as DatetimeIndex "
-                    "is deprecated, will be removed in a future version.",
-                    FutureWarning,
-                )
+        if ax.is_all_dates:
             from pandas.core.tools.datetimes import to_datetime
 
             before = to_datetime(before)

pandas/core/indexes/base.py

@@ -2139,25 +2139,12 @@ def inferred_type(self) -> str_t:
         return lib.infer_dtype(self._values, skipna=False)
 
     @cache_readonly
-    def _is_all_dates(self) -> bool:
+    def is_all_dates(self) -> bool:
         """
         Whether or not the index values only consist of dates.
         """
         return is_datetime_array(ensure_object(self._values))
 
-    @cache_readonly
-    def is_all_dates(self):
-        """
-        Whether or not the index values only consist of dates.
-        """
-        warnings.warn(
-            "Index.is_all_dates is deprecated, will be removed in a future version.  "
-            "check index.inferred_type instead",
-            FutureWarning,
-            stacklevel=2,
-        )
-        return self._is_all_dates
-
     # --------------------------------------------------------------------
     # Pickle Methods
 

pandas/core/indexes/datetimelike.py

@@ -124,7 +124,7 @@ def _simple_new(
         return result
 
     @property
-    def _is_all_dates(self) -> bool:
+    def is_all_dates(self) -> bool:
         return True
 
     # ------------------------------------------------------------------------

pandas/core/indexes/interval.py

@@ -1021,7 +1021,7 @@ def func(self, other, sort=sort):
     # --------------------------------------------------------------------
 
     @property
-    def _is_all_dates(self) -> bool:
+    def is_all_dates(self) -> bool:
         """
         This is False even when left/right contain datetime-like objects,
         as the check is done on the Interval itself

pandas/core/indexes/multi.py

@@ -1805,7 +1805,7 @@ def to_flat_index(self):
         return Index(self._values, tupleize_cols=False)
 
     @property
-    def _is_all_dates(self) -> bool:
+    def is_all_dates(self) -> bool:
         return False
 
     def is_lexsorted(self) -> bool:

pandas/core/indexes/numeric.py

@@ -176,7 +176,7 @@ def _assert_safe_casting(cls, data, subarr):
         pass
 
     @property
-    def _is_all_dates(self) -> bool:
+    def is_all_dates(self) -> bool:
         """
         Checks that all the labels are datetime objects.
         """

pandas/core/missing.py

@@ -313,7 +313,7 @@ def _interpolate_scipy_wrapper(
         "piecewise_polynomial": _from_derivatives,
     }
 
-    if getattr(x, "_is_all_dates", False):
+    if getattr(x, "is_all_dates", False):
         # GH 5975, scipy.interp1d can't handle datetime64s
         x, new_x = x._values.astype("i8"), new_x.astype("i8")
 

pandas/core/series.py

@@ -423,7 +423,7 @@ def _set_axis(self, axis: int, labels, fastpath: bool = False) -> None:
         if not fastpath:
             labels = ensure_index(labels)
 
-        if labels._is_all_dates:
+        if labels.is_all_dates:
             deep_labels = labels
             if isinstance(labels, CategoricalIndex):
                 deep_labels = labels.categories
@@ -436,13 +436,6 @@ def _set_axis(self, axis: int, labels, fastpath: bool = False) -> None:
                     # need to set here because we changed the index
                     if fastpath:
                         self._mgr.set_axis(axis, labels)
-                    warnings.warn(
-                        "Automatically casting object-dtype Index of datetimes to "
-                        "DatetimeIndex is deprecated and will be removed in a "
-                        "future version.  Explicitly cast to DatetimeIndex instead.",
-                        FutureWarning,
-                        stacklevel=3,
-                    )
                 except (tslibs.OutOfBoundsDatetime, ValueError):
                     # labels may exceeds datetime bounds,
                     # or not be a DatetimeIndex

pandas/plotting/_matplotlib/core.py

@@ -1269,7 +1269,7 @@ def get_label(i):
         # would be too close together.
         condition = (
             not self._use_dynamic_x()
-            and (data.index._is_all_dates and self.use_index)
+            and (data.index.is_all_dates and self.use_index)
             and (not self.subplots or (self.subplots and self.sharex))
         )
 

pandas/tests/indexes/interval/test_interval.py

@@ -876,7 +876,7 @@ def test_is_all_dates(self):
             Timestamp("2017-01-01 00:00:00"), Timestamp("2018-01-01 00:00:00")
         )
         year_2017_index = IntervalIndex([year_2017])
-        assert not year_2017_index._is_all_dates
+        assert not year_2017_index.is_all_dates
 
     @pytest.mark.parametrize("key", [[5], (2, 3)])
     def test_get_value_non_scalar_errors(self, key):

pandas/tests/indexes/multi/test_equivalence.py

@@ -260,7 +260,7 @@ def test_is_():
 
 
 def test_is_all_dates(idx):
-    assert not idx._is_all_dates
+    assert not idx.is_all_dates
 
 
 def test_is_numeric(idx):

pandas/tests/indexes/test_base.py

@@ -1033,8 +1033,7 @@ def test_is_object(self, index, expected):
         indirect=["index"],
     )
     def test_is_all_dates(self, index, expected):
-        with tm.assert_produces_warning(FutureWarning):
-            assert index.is_all_dates is expected
+        assert index.is_all_dates is expected
 
     def test_summary(self, index):
         self._check_method_works(Index._summary, index)

pandas/tests/indexing/test_indexing.py

@@ -530,17 +530,15 @@ def test_string_slice(self):
         # string indexing against datetimelike with object
         # dtype should properly raises KeyError
         df = DataFrame([1], Index([pd.Timestamp("2011-01-01")], dtype=object))
-        assert df.index._is_all_dates
+        assert df.index.is_all_dates
         with pytest.raises(KeyError, match="'2011'"):
             df["2011"]
 
         with pytest.raises(KeyError, match="'2011'"):
-            with tm.assert_produces_warning(FutureWarning):
-                # This does an is_all_dates check
-                df.loc["2011", 0]
+            df.loc["2011", 0]
 
         df = DataFrame()
-        assert not df.index._is_all_dates
+        assert not df.index.is_all_dates
         with pytest.raises(KeyError, match="'2011'"):
             df["2011"]
 

pandas/tests/io/pytables/test_store.py

@@ -2441,17 +2441,13 @@ def test_series(self, setup_path):
         ts = tm.makeTimeSeries()
         self._check_roundtrip(ts, tm.assert_series_equal, path=setup_path)
 
-        with tm.assert_produces_warning(FutureWarning):
-            # auto-casting object->DatetimeIndex deprecated
-            ts2 = Series(ts.index, Index(ts.index, dtype=object))
+        ts2 = Series(ts.index, Index(ts.index, dtype=object))
         self._check_roundtrip(ts2, tm.assert_series_equal, path=setup_path)
 
-        with tm.assert_produces_warning(FutureWarning):
-            # auto-casting object->DatetimeIndex deprecated
-            ts3 = Series(
-                ts.values, Index(np.asarray(ts.index, dtype=object), dtype=object)
-            )
-        self._check_roundtrip(ts3, tm.assert_series_equal, path=setup_path)
+        ts3 = Series(ts.values, Index(np.asarray(ts.index, dtype=object), dtype=object))
+        self._check_roundtrip(
+            ts3, tm.assert_series_equal, path=setup_path, check_index_type=False
+        )
 
     def test_float_index(self, setup_path):
 

pandas/tests/series/test_constructors.py

@@ -104,11 +104,11 @@ def test_scalar_extension_dtype(self, ea_scalar_and_dtype):
     def test_constructor(self, datetime_series):
         with tm.assert_produces_warning(DeprecationWarning, check_stacklevel=False):
             empty_series = Series()
-        assert datetime_series.index._is_all_dates
+        assert datetime_series.index.is_all_dates
 
         # Pass in Series
         derived = Series(datetime_series)
-        assert derived.index._is_all_dates
+        assert derived.index.is_all_dates
 
         assert tm.equalContents(derived.index, datetime_series.index)
         # Ensure new index is not created
@@ -119,9 +119,9 @@ def test_constructor(self, datetime_series):
         assert mixed.dtype == np.object_
         assert mixed[1] is np.NaN
 
-        assert not empty_series.index._is_all_dates
+        assert not empty_series.index.is_all_dates
         with tm.assert_produces_warning(DeprecationWarning, check_stacklevel=False):
-            assert not Series().index._is_all_dates
+            assert not Series().index.is_all_dates
 
         # exception raised is of type ValueError GH35744
         with pytest.raises(ValueError, match="Data must be 1-dimensional"):

pandas/tests/series/test_repr.py

@@ -184,9 +184,7 @@ def test_timeseries_repr_object_dtype(self):
         index = Index(
             [datetime(2000, 1, 1) + timedelta(i) for i in range(1000)], dtype=object
         )
-        with tm.assert_produces_warning(FutureWarning):
-            # Index.is_all_dates deprecated
-            ts = Series(np.random.randn(len(index)), index)
+        ts = Series(np.random.randn(len(index)), index)
         repr(ts)
 
         ts = tm.makeTimeSeries(1000)

pandas/tests/window/moments/test_moments_rolling_apply.py

@@ -122,16 +122,13 @@ def test_center_reindex_series(raw, series):
     s = [f"x{x:d}" for x in range(12)]
     minp = 10
 
-    warn = None if raw else FutureWarning
-    with tm.assert_produces_warning(warn, check_stacklevel=False):
-        # GH#36697 is_all_dates deprecated
-        series_xp = (
-            series.reindex(list(series.index) + s)
-            .rolling(window=25, min_periods=minp)
-            .apply(f, raw=raw)
-            .shift(-12)
-            .reindex(series.index)
-        )
+    series_xp = (
+        series.reindex(list(series.index) + s)
+        .rolling(window=25, min_periods=minp)
+        .apply(f, raw=raw)
+        .shift(-12)
+        .reindex(series.index)
+    )
     series_rs = series.rolling(window=25, min_periods=minp, center=True).apply(
         f, raw=raw
     )
@@ -143,15 +140,12 @@ def test_center_reindex_frame(raw, frame):
     s = [f"x{x:d}" for x in range(12)]
     minp = 10
 
-    warn = None if raw else FutureWarning
-    with tm.assert_produces_warning(warn, check_stacklevel=False):
-        # GH#36697 is_all_dates deprecated
-        frame_xp = (
-            frame.reindex(list(frame.index) + s)
-            .rolling(window=25, min_periods=minp)
-            .apply(f, raw=raw)
-            .shift(-12)
-            .reindex(frame.index)
-        )
+    frame_xp = (
+        frame.reindex(list(frame.index) + s)
+        .rolling(window=25, min_periods=minp)
+        .apply(f, raw=raw)
+        .shift(-12)
+        .reindex(frame.index)
+    )
     frame_rs = frame.rolling(window=25, min_periods=minp, center=True).apply(f, raw=raw)
     tm.assert_frame_equal(frame_xp, frame_rs)