DEPR: is_all_dates (pandas-dev#36697)

Author: jbrockmendel

doc/source/whatsnew/v1.2.0.rst

@@ -214,6 +214,8 @@ Deprecations
 - :meth:`DataFrame.lookup` is deprecated and will be removed in a future version, use :meth:`DataFrame.melt` and :meth:`DataFrame.loc` instead (:issue:`18682`)
 - The :meth:`Index.to_native_types` is deprecated. Use ``.astype(str)`` instead (:issue:`28867`)
 - Deprecated indexing :class:`DataFrame` rows with datetime-like strings ``df[string]``, 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`)
 
 .. ---------------------------------------------------------------------------
 

pandas/core/generic.py

@@ -9528,7 +9528,13 @@ def truncate(
 
         # if we have a date index, convert to dates, otherwise
         # treat like a slice
-        if ax.is_all_dates:
+        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,
+                )
             from pandas.core.tools.datetimes import to_datetime
 
             before = to_datetime(before)

pandas/core/indexes/base.py

@@ -2086,12 +2086,25 @@ 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

@@ -98,7 +98,7 @@ class DatetimeIndexOpsMixin(ExtensionIndex):
     _hasnans = hasnans  # for index / array -agnostic code
 
     @property
-    def is_all_dates(self) -> bool:
+    def _is_all_dates(self) -> bool:
         return True
 
     # ------------------------------------------------------------------------

pandas/core/indexes/interval.py

@@ -1092,7 +1092,7 @@ 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

@@ -1733,7 +1733,7 @@ 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

@@ -149,7 +149,7 @@ 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

@@ -199,7 +199,7 @@ def interpolate_1d(
         return yvalues
 
     if method == "time":
-        if not getattr(xvalues, "is_all_dates", None):
+        if not getattr(xvalues, "_is_all_dates", None):
             # if not issubclass(xvalues.dtype.type, np.datetime64):
             raise ValueError(
                 "time-weighted interpolation only works "
@@ -327,7 +327,7 @@ 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

@@ -409,14 +409,20 @@ def _set_axis(self, axis: int, labels, fastpath: bool = False) -> None:
         if not fastpath:
             labels = ensure_index(labels)
 
-        is_all_dates = labels.is_all_dates
-        if is_all_dates:
+        if labels._is_all_dates:
             if not isinstance(labels, (DatetimeIndex, PeriodIndex, TimedeltaIndex)):
                 try:
                     labels = DatetimeIndex(labels)
                     # 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

@@ -1238,7 +1238,7 @@ 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

@@ -871,7 +871,7 @@ def test_is_all_dates(self):
             pd.Timestamp("2017-01-01 00:00:00"), pd.Timestamp("2018-01-01 00:00:00")
         )
         year_2017_index = pd.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

@@ -202,7 +202,7 @@ 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

@@ -1153,7 +1153,8 @@ def test_is_object(self, index, expected):
         indirect=["index"],
     )
     def test_is_all_dates(self, index, expected):
-        assert index.is_all_dates is expected
+        with tm.assert_produces_warning(FutureWarning):
+            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

@@ -554,15 +554,17 @@ 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'"):
-            df.loc["2011", 0]
+            with tm.assert_produces_warning(FutureWarning):
+                # This does an is_all_dates check
+                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

@@ -2384,10 +2384,16 @@ def test_series(self, setup_path):
         ts = tm.makeTimeSeries()
         self._check_roundtrip(ts, tm.assert_series_equal, path=setup_path)
 
-        ts2 = Series(ts.index, Index(ts.index, dtype=object))
+        with tm.assert_produces_warning(FutureWarning):
+            # auto-casting object->DatetimeIndex deprecated
+            ts2 = Series(ts.index, Index(ts.index, dtype=object))
         self._check_roundtrip(ts2, tm.assert_series_equal, path=setup_path)
 
-        ts3 = Series(ts.values, Index(np.asarray(ts.index, dtype=object), dtype=object))
+        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, check_index_type=False
         )

pandas/tests/series/test_alter_axes.py

@@ -52,4 +52,4 @@ def test_set_index_makes_timeseries(self):
 
         s = Series(range(10))
         s.index = idx
-        assert s.index.is_all_dates
+        assert s.index._is_all_dates

pandas/tests/series/test_constructors.py

@@ -94,11 +94,11 @@ def test_scalar_conversion(self):
     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
@@ -109,9 +109,9 @@ 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 Exception
         with pytest.raises(Exception, match="Data must be 1-dimensional"):

pandas/tests/series/test_repr.py

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

pandas/tests/series/test_timeseries.py

@@ -9,8 +9,10 @@
 class TestTimeSeries:
     def test_timeseries_coercion(self):
         idx = tm.makeDateIndex(10000)
-        ser = Series(np.random.randn(len(idx)), idx.astype(object))
-        assert ser.index.is_all_dates
+        with tm.assert_produces_warning(FutureWarning):
+            ser = Series(np.random.randn(len(idx)), idx.astype(object))
+        with tm.assert_produces_warning(FutureWarning):
+            assert ser.index.is_all_dates
         assert isinstance(ser.index, DatetimeIndex)
 
     def test_contiguous_boolean_preserve_freq(self):

pandas/tests/window/moments/test_moments_rolling_apply.py

@@ -122,13 +122,16 @@ def test_center_reindex_series(raw, series):
     s = [f"x{x:d}" for x in range(12)]
     minp = 10
 
-    series_xp = (
-        series.reindex(list(series.index) + s)
-        .rolling(window=25, min_periods=minp)
-        .apply(f, raw=raw)
-        .shift(-12)
-        .reindex(series.index)
-    )
+    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_rs = series.rolling(window=25, min_periods=minp, center=True).apply(
         f, raw=raw
     )
@@ -140,12 +143,15 @@ def test_center_reindex_frame(raw, frame):
     s = [f"x{x:d}" for x in range(12)]
     minp = 10
 
-    frame_xp = (
-        frame.reindex(list(frame.index) + s)
-        .rolling(window=25, min_periods=minp)
-        .apply(f, raw=raw)
-        .shift(-12)
-        .reindex(frame.index)
-    )
+    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_rs = frame.rolling(window=25, min_periods=minp, center=True).apply(f, raw=raw)
     tm.assert_frame_equal(frame_xp, frame_rs)