CLN: enforce deprecation of interpolate with object dtype (#57820)

* remove interpolate with object dtype

* enforce deprecation interpolate with object dtype, correct tests

* fix ruff error

* add a note to v3.0.0

* combine two conditions

* change blocks of if statements to avoid duplicate checks

* replace err msg containing 'Try setting at least one column to a numeric dtype'

* simplify if condition

Author: natmokval

doc/source/whatsnew/v3.0.0.rst

@@ -201,6 +201,7 @@ Removal of prior version deprecations/changes
 - Changed the default value of ``observed`` in :meth:`DataFrame.groupby` and :meth:`Series.groupby` to ``True`` (:issue:`51811`)
 - Enforced deprecation disallowing parsing datetimes with mixed time zones unless user passes ``utc=True`` to :func:`to_datetime` (:issue:`57275`)
 - Enforced deprecation of :meth:`.DataFrameGroupBy.get_group` and :meth:`.SeriesGroupBy.get_group` allowing the ``name`` argument to be a non-tuple when grouping by a list of length 1 (:issue:`54155`)
+- Enforced deprecation of :meth:`Series.interpolate` and :meth:`DataFrame.interpolate` for object-dtype (:issue:`57820`)
 - Enforced deprecation of ``axis=None`` acting the same as ``axis=0`` in the DataFrame reductions ``sum``, ``prod``, ``std``, ``var``, and ``sem``, passing ``axis=None`` will now reduce over both axes; this is particularly the case when doing e.g. ``numpy.sum(df)`` (:issue:`21597`)
 - Enforced deprecation of passing a dictionary to :meth:`SeriesGroupBy.agg` (:issue:`52268`)
 - Enforced deprecation of string ``AS`` denoting frequency in :class:`YearBegin` and strings ``AS-DEC``, ``AS-JAN``, etc. denoting annual frequencies with various fiscal year starts (:issue:`57793`)

pandas/core/generic.py

@@ -7816,17 +7816,11 @@ def interpolate(
             obj, should_transpose = self, False
         else:
             obj, should_transpose = (self.T, True) if axis == 1 else (self, False)
+            # GH#53631
             if np.any(obj.dtypes == object):
-                # GH#53631
-                if not (obj.ndim == 2 and np.all(obj.dtypes == object)):
-                    # don't warn in cases that already raise
-                    warnings.warn(
-                        f"{type(self).__name__}.interpolate with object dtype is "
-                        "deprecated and will raise in a future version. Call "
-                        "obj.infer_objects(copy=False) before interpolating instead.",
-                        FutureWarning,
-                        stacklevel=find_stack_level(),
-                    )
+                raise TypeError(
+                    f"{type(self).__name__} cannot interpolate with object dtype."
+                )
 
         if method in fillna_methods and "fill_value" in kwargs:
             raise ValueError(
@@ -7842,13 +7836,6 @@ def interpolate(
 
         limit_direction = missing.infer_limit_direction(limit_direction, method)
 
-        if obj.ndim == 2 and np.all(obj.dtypes == object):
-            raise TypeError(
-                "Cannot interpolate with all object-dtype columns "
-                "in the DataFrame. Try setting at least one "
-                "column to a numeric dtype."
-            )
-
         if method.lower() in fillna_methods:
             # TODO(3.0): remove this case
             # TODO: warn/raise on limit_direction or kwargs which are ignored?

pandas/tests/copy_view/test_interp_fillna.py

@@ -111,20 +111,12 @@ def test_interp_fill_functions_inplace(func, dtype):
     assert view._mgr._has_no_reference(0)
 
 
-def test_interpolate_cleaned_fill_method():
-    # Check that "method is set to None" case works correctly
+def test_interpolate_cannot_with_object_dtype():
     df = DataFrame({"a": ["a", np.nan, "c"], "b": 1})
-    df_orig = df.copy()
-
-    msg = "DataFrame.interpolate with object dtype"
-    with tm.assert_produces_warning(FutureWarning, match=msg):
-        result = df.interpolate(method="linear")
 
-    assert np.shares_memory(get_array(result, "a"), get_array(df, "a"))
-    result.iloc[0, 0] = Timestamp("2021-12-31")
-
-    assert not np.shares_memory(get_array(result, "a"), get_array(df, "a"))
-    tm.assert_frame_equal(df, df_orig)
+    msg = "DataFrame cannot interpolate with object dtype"
+    with pytest.raises(TypeError, match=msg):
+        df.interpolate()
 
 
 def test_interpolate_object_convert_no_op():

pandas/tests/frame/methods/test_interpolate.py

@@ -76,29 +76,14 @@ def test_interp_basic(self):
                 "D": list("abcd"),
             }
         )
-        expected = DataFrame(
-            {
-                "A": [1.0, 2.0, 3.0, 4.0],
-                "B": [1.0, 4.0, 9.0, 9.0],
-                "C": [1, 2, 3, 5],
-                "D": list("abcd"),
-            }
-        )
-        msg = "DataFrame.interpolate with object dtype"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            result = df.interpolate()
-        tm.assert_frame_equal(result, expected)
+        msg = "DataFrame cannot interpolate with object dtype"
+        with pytest.raises(TypeError, match=msg):
+            df.interpolate()
 
-        # check we didn't operate inplace GH#45791
         cvalues = df["C"]._values
         dvalues = df["D"].values
-        assert np.shares_memory(cvalues, result["C"]._values)
-        assert np.shares_memory(dvalues, result["D"]._values)
-
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            res = df.interpolate(inplace=True)
-        assert res is None
-        tm.assert_frame_equal(df, expected)
+        with pytest.raises(TypeError, match=msg):
+            df.interpolate(inplace=True)
 
         # check we DID operate inplace
         assert np.shares_memory(df["C"]._values, cvalues)
@@ -117,14 +102,16 @@ def test_interp_basic_with_non_range_index(self, using_infer_string):
             }
         )
 
-        msg = "DataFrame.interpolate with object dtype"
-        warning = FutureWarning if not using_infer_string else None
-        with tm.assert_produces_warning(warning, match=msg):
+        msg = "DataFrame cannot interpolate with object dtype"
+        if not using_infer_string:
+            with pytest.raises(TypeError, match=msg):
+                df.set_index("C").interpolate()
+        else:
             result = df.set_index("C").interpolate()
-        expected = df.set_index("C")
-        expected.loc[3, "A"] = 3
-        expected.loc[5, "B"] = 9
-        tm.assert_frame_equal(result, expected)
+            expected = df.set_index("C")
+            expected.loc[3, "A"] = 3
+            expected.loc[5, "B"] = 9
+            tm.assert_frame_equal(result, expected)
 
     def test_interp_empty(self):
         # https://github.com/pandas-dev/pandas/issues/35598
@@ -315,22 +302,14 @@ def test_interp_raise_on_only_mixed(self, axis):
                 "E": [1, 2, 3, 4],
             }
         )
-        msg = (
-            "Cannot interpolate with all object-dtype columns "
-            "in the DataFrame. Try setting at least one "
-            "column to a numeric dtype."
-        )
+        msg = "DataFrame cannot interpolate with object dtype"
         with pytest.raises(TypeError, match=msg):
             df.astype("object").interpolate(axis=axis)
 
     def test_interp_raise_on_all_object_dtype(self):
         # GH 22985
         df = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}, dtype="object")
-        msg = (
-            "Cannot interpolate with all object-dtype columns "
-            "in the DataFrame. Try setting at least one "
-            "column to a numeric dtype."
-        )
+        msg = "DataFrame cannot interpolate with object dtype"
         with pytest.raises(TypeError, match=msg):
             df.interpolate()
 

pandas/tests/series/methods/test_interpolate.py

@@ -846,10 +846,10 @@ def test_interpolate_unsorted_index(self, ascending, expected_values):
 
     def test_interpolate_asfreq_raises(self):
         ser = Series(["a", None, "b"], dtype=object)
-        msg2 = "Series.interpolate with object dtype"
+        msg2 = "Series cannot interpolate with object dtype"
         msg = "Invalid fill method"
-        with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(FutureWarning, match=msg2):
+        with pytest.raises(TypeError, match=msg2):
+            with pytest.raises(ValueError, match=msg):
                 ser.interpolate(method="asfreq")
 
     def test_interpolate_fill_value(self):