DEPR: Deprecating .clip_lower and .clip_upper (pandas-dev#24203)

Author: datapythonista

doc/source/whatsnew/v0.24.0.rst

@@ -1115,6 +1115,7 @@ Deprecations
 - Creating a :class:`TimedeltaIndex` or :class:`DatetimeIndex` by passing range arguments `start`, `end`, and `periods` is deprecated in favor of :func:`timedelta_range` and :func:`date_range` (:issue:`23919`)
 - Passing a string alias like ``'datetime64[ns, UTC]'`` as the `unit` parameter to :class:`DatetimeTZDtype` is deprecated. Use :class:`DatetimeTZDtype.construct_from_string` instead (:issue:`23990`).
 - In :meth:`Series.where` with Categorical data, providing an ``other`` that is not present in the categories is deprecated. Convert the categorical to a different dtype or add the ``other`` to the categories first (:issue:`24077`).
+- :meth:`Series.clip_lower`, :meth:`Series.clip_upper`, :meth:`DataFrame.clip_lower` and :meth:`DataFrame.clip_upper` are deprecated and will be removed in a future version. Use ``Series.clip(lower=threshold)``, ``Series.clip(upper=threshold)`` and the equivalent ``DataFrame`` methods (:issue:`24203`)
 
 
 .. _whatsnew_0240.deprecations.datetimelike_int_ops:

pandas/core/generic.py

@@ -7204,11 +7204,6 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
             Same type as calling object with the values outside the
             clip boundaries replaced
 
-        See Also
-        --------
-        clip_lower : Clip values below specified threshold(s).
-        clip_upper : Clip values above specified threshold(s).
-
         Examples
         --------
         >>> data = {'col_0': [9, -3, 0, -1, 5], 'col_1': [-2, -7, 6, 8, -5]}
@@ -7281,18 +7276,23 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
 
         result = self
         if lower is not None:
-            result = result.clip_lower(lower, axis, inplace=inplace)
+            result = result._clip_with_one_bound(lower, method=self.ge,
+                                                 axis=axis, inplace=inplace)
         if upper is not None:
             if inplace:
                 result = self
-            result = result.clip_upper(upper, axis, inplace=inplace)
+            result = result._clip_with_one_bound(upper, method=self.le,
+                                                 axis=axis, inplace=inplace)
 
         return result
 
     def clip_upper(self, threshold, axis=None, inplace=False):
         """
         Trim values above a given threshold.
 
+        .. deprecated:: 0.24.0
+            Use clip(upper=threshold) instead.
+
         Elements above the `threshold` will be changed to match the
         `threshold` value(s). Threshold can be a single value or an array,
         in the latter case it performs the truncation element-wise.
@@ -7319,18 +7319,15 @@ def clip_upper(self, threshold, axis=None, inplace=False):
 
         Returns
         -------
-        clipped
+        Series or DataFrame
             Original data with values trimmed.
 
         See Also
         --------
-        DataFrame.clip : General purpose method to trim DataFrame values to
-            given threshold(s).
-        DataFrame.clip_lower : Trim DataFrame values below given
-            threshold(s).
         Series.clip : General purpose method to trim Series values to given
             threshold(s).
-        Series.clip_lower : Trim Series values below given threshold(s).
+        DataFrame.clip : General purpose method to trim DataFrame values to
+            given threshold(s).
 
         Examples
         --------
@@ -7363,13 +7360,19 @@ def clip_upper(self, threshold, axis=None, inplace=False):
         4    1
         dtype: int64
         """
+        warnings.warn('clip_upper(threshold) is deprecated, '
+                      'use clip(upper=threshold) instead',
+                      FutureWarning, stacklevel=2)
         return self._clip_with_one_bound(threshold, method=self.le,
                                          axis=axis, inplace=inplace)
 
     def clip_lower(self, threshold, axis=None, inplace=False):
         """
         Trim values below a given threshold.
 
+        .. deprecated:: 0.24.0
+            Use clip(lower=threshold) instead.
+
         Elements below the `threshold` will be changed to match the
         `threshold` value(s). Threshold can be a single value or an array,
         in the latter case it performs the truncation element-wise.
@@ -7397,18 +7400,15 @@ def clip_lower(self, threshold, axis=None, inplace=False):
 
         Returns
         -------
-        clipped
+        Series or DataFrame
             Original data with values trimmed.
 
         See Also
         --------
-        DataFrame.clip : General purpose method to trim DataFrame values to
-            given threshold(s).
-        DataFrame.clip_upper : Trim DataFrame values above given
-            threshold(s).
         Series.clip : General purpose method to trim Series values to given
             threshold(s).
-        Series.clip_upper : Trim Series values above given threshold(s).
+        DataFrame.clip : General purpose method to trim DataFrame values to
+            given threshold(s).
 
         Examples
         --------
@@ -7476,6 +7476,9 @@ def clip_lower(self, threshold, axis=None, inplace=False):
         1  4  5
         2  5  6
         """
+        warnings.warn('clip_lower(threshold) is deprecated, '
+                      'use clip(lower=threshold) instead',
+                      FutureWarning, stacklevel=2)
         return self._clip_with_one_bound(threshold, method=self.ge,
                                          axis=axis, inplace=inplace)
 

pandas/tests/frame/test_analytics.py

@@ -1841,10 +1841,12 @@ def test_clip(self, float_frame):
         median = float_frame.median().median()
         original = float_frame.copy()
 
-        capped = float_frame.clip_upper(median)
+        with tm.assert_produces_warning(FutureWarning):
+            capped = float_frame.clip_upper(median)
         assert not (capped.values > median).any()
 
-        floored = float_frame.clip_lower(median)
+        with tm.assert_produces_warning(FutureWarning):
+            floored = float_frame.clip_lower(median)
         assert not (floored.values < median).any()
 
         double = float_frame.clip(upper=median, lower=median)
@@ -1858,11 +1860,13 @@ def test_inplace_clip(self, float_frame):
         median = float_frame.median().median()
         frame_copy = float_frame.copy()
 
-        frame_copy.clip_upper(median, inplace=True)
+        with tm.assert_produces_warning(FutureWarning):
+            frame_copy.clip_upper(median, inplace=True)
         assert not (frame_copy.values > median).any()
         frame_copy = float_frame.copy()
 
-        frame_copy.clip_lower(median, inplace=True)
+        with tm.assert_produces_warning(FutureWarning):
+            frame_copy.clip_lower(median, inplace=True)
         assert not (frame_copy.values < median).any()
         frame_copy = float_frame.copy()
 
@@ -2263,7 +2267,8 @@ def test_series_broadcasting(self):
         s_nan = Series([np.nan, np.nan, 1])
 
         with tm.assert_produces_warning(None):
-            df_nan.clip_lower(s, axis=0)
+            with tm.assert_produces_warning(FutureWarning):
+                df_nan.clip_lower(s, axis=0)
             for op in ['lt', 'le', 'gt', 'ge', 'eq', 'ne']:
                 getattr(df, op)(s_nan, axis=0)
 

pandas/tests/series/test_analytics.py

@@ -924,8 +924,10 @@ def test_matmul(self):
     def test_clip(self, datetime_series):
         val = datetime_series.median()
 
-        assert datetime_series.clip_lower(val).min() == val
-        assert datetime_series.clip_upper(val).max() == val
+        with tm.assert_produces_warning(FutureWarning):
+            assert datetime_series.clip_lower(val).min() == val
+        with tm.assert_produces_warning(FutureWarning):
+            assert datetime_series.clip_upper(val).max() == val
 
         assert datetime_series.clip(lower=val).min() == val
         assert datetime_series.clip(upper=val).max() == val
@@ -943,8 +945,10 @@ def test_clip_types_and_nulls(self):
 
         for s in sers:
             thresh = s[2]
-            lower = s.clip_lower(thresh)
-            upper = s.clip_upper(thresh)
+            with tm.assert_produces_warning(FutureWarning):
+                lower = s.clip_lower(thresh)
+            with tm.assert_produces_warning(FutureWarning):
+                upper = s.clip_upper(thresh)
             assert lower[notna(lower)].min() == thresh
             assert upper[notna(upper)].max() == thresh
             assert list(isna(s)) == list(isna(lower))
@@ -971,8 +975,12 @@ def test_clip_against_series(self):
         s = Series([1.0, 1.0, 4.0])
         threshold = Series([1.0, 2.0, 3.0])
 
-        assert_series_equal(s.clip_lower(threshold), Series([1.0, 2.0, 4.0]))
-        assert_series_equal(s.clip_upper(threshold), Series([1.0, 1.0, 3.0]))
+        with tm.assert_produces_warning(FutureWarning):
+            assert_series_equal(s.clip_lower(threshold),
+                                Series([1.0, 2.0, 4.0]))
+        with tm.assert_produces_warning(FutureWarning):
+            assert_series_equal(s.clip_upper(threshold),
+                                Series([1.0, 1.0, 3.0]))
 
         lower = Series([1.0, 2.0, 3.0])
         upper = Series([1.5, 2.5, 3.5])