DEPR: remove ptp (pandas-dev#30458)

Author: jbrockmendel

doc/source/whatsnew/v1.0.0.rst

@@ -569,6 +569,7 @@ or ``matplotlib.Axes.plot``. See :ref:`plotting.formatters` for more.
 - A tuple passed to :meth:`DataFrame.groupby` is now exclusively treated as a single key (:issue:`18314`)
 - Removed the previously deprecated :meth:`Index.contains`, use ``key in index`` instead (:issue:`30103`)
 - Addition and subtraction of ``int`` or integer-arrays is no longer allowed in :class:`Timestamp`, :class:`DatetimeIndex`, :class:`TimedeltaIndex`, use ``obj + n * obj.freq`` instead of ``obj + n`` (:issue:`22535`)
+- Removed :meth:`Series.ptp` (:issue:`21614`)
 - Removed :meth:`Series.from_array` (:issue:`18258`)
 - Removed :meth:`DataFrame.from_items` (:issue:`18458`)
 - Removed :meth:`DataFrame.as_matrix`, :meth:`Series.as_matrix` (:issue:`18458`)

pandas/core/generic.py

@@ -28,7 +28,7 @@
 
 from pandas._config import config
 
-from pandas._libs import Timestamp, iNaT, properties
+from pandas._libs import Timestamp, iNaT, lib, properties
 from pandas._typing import Dtype, FilePathOrBuffer, FrameOrSeries, JSONSerializable
 from pandas.compat import set_function_name
 from pandas.compat._optional import import_optional_dependency
@@ -1920,6 +1920,11 @@ def __array__(self, dtype=None):
         return com.values_from_object(self)
 
     def __array_wrap__(self, result, context=None):
+        result = lib.item_from_zerodim(result)
+        if is_scalar(result):
+            # e.g. we get here with np.ptp(series)
+            # ptp also requires the item_from_zerodim
+            return result
         d = self._construct_axes_dict(self._AXIS_ORDERS, copy=False)
         return self._constructor(result, **d).__finalize__(self)
 
@@ -10166,40 +10171,6 @@ def mad(self, axis=None, skipna=None, level=None):
             _min_examples,
         )
 
-    @classmethod
-    def _add_series_only_operations(cls):
-        """
-        Add the series only operations to the cls; evaluate the doc
-        strings again.
-        """
-
-        axis_descr, name, name2 = _doc_parms(cls)
-
-        def nanptp(values, axis=0, skipna=True):
-            nmax = nanops.nanmax(values, axis, skipna)
-            nmin = nanops.nanmin(values, axis, skipna)
-            warnings.warn(
-                "Method .ptp is deprecated and will be removed "
-                "in a future version. Use numpy.ptp instead.",
-                FutureWarning,
-                stacklevel=4,
-            )
-            return nmax - nmin
-
-        cls.ptp = _make_stat_function(
-            cls,
-            "ptp",
-            name,
-            name2,
-            axis_descr,
-            """Return the difference between the min and max value.
-            \n.. deprecated:: 0.24.0 Use numpy.ptp instead
-            \nReturn the difference between the maximum value and the
-            minimum value in the object. This is the equivalent of the
-            ``numpy.ndarray`` method ``ptp``.""",
-            nanptp,
-        )
-
     @classmethod
     def _add_series_or_dataframe_operations(cls):
         """

pandas/core/series.py

@@ -4390,7 +4390,6 @@ def to_period(self, freq=None, copy=True):
     ["index"], docs={"index": "The index (axis labels) of the Series."},
 )
 Series._add_numeric_operations()
-Series._add_series_only_operations()
 Series._add_series_or_dataframe_operations()
 
 # Add arithmetic!

pandas/tests/series/test_analytics.py

@@ -198,41 +198,7 @@ def test_ptp(self):
         N = 1000
         arr = np.random.randn(N)
         ser = Series(arr)
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            assert np.ptp(ser) == np.ptp(arr)
-
-        # GH11163
-        s = Series([3, 5, np.nan, -3, 10])
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            assert s.ptp() == 13
-            assert pd.isna(s.ptp(skipna=False))
-
-        mi = pd.MultiIndex.from_product([["a", "b"], [1, 2, 3]])
-        s = pd.Series([1, np.nan, 7, 3, 5, np.nan], index=mi)
-
-        expected = pd.Series([6, 2], index=["a", "b"], dtype=np.float64)
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            tm.assert_series_equal(s.ptp(level=0), expected)
-
-        expected = pd.Series([np.nan, np.nan], index=["a", "b"])
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            tm.assert_series_equal(s.ptp(level=0, skipna=False), expected)
-
-        msg = "No axis named 1 for object type <class 'pandas.core.series.Series'>"
-        with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-                s.ptp(axis=1)
-
-        s = pd.Series(["a", "b", "c", "d", "e"])
-        msg = r"unsupported operand type\(s\) for -: 'str' and 'str'"
-        with pytest.raises(TypeError, match=msg):
-            with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-                s.ptp()
-
-        msg = r"Series\.ptp does not implement numeric_only\."
-        with pytest.raises(NotImplementedError, match=msg):
-            with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-                s.ptp(numeric_only=True)
+        assert np.ptp(ser) == np.ptp(arr)
 
     def test_repeat(self):
         s = Series(np.random.randn(3), index=["a", "b", "c"])