Deprecate Series.applymap

python/cudf/cudf/core/series.py

@@ -5,6 +5,7 @@
 import functools
 import inspect
 import pickle
+import warnings
 from collections import abc as abc
 from shutil import get_terminal_size
 from typing import Any, Dict, MutableMapping, Optional, Set, Tuple, Type, Union
@@ -1012,7 +1013,10 @@ def map(self, arg, na_action=None) -> "Series":
             result.name = self.name
             result.index = self.index
         else:
-            result = self.applymap(arg)
+            # TODO: switch to `apply`
+            with warnings.catch_warnings():
+                warnings.simplefilter("ignore", category=FutureWarning)
+                result = self.applymap(arg)
         return result
 
     @_cudf_nvtx_annotate
@@ -2210,6 +2214,11 @@ def applymap(self, udf, out_dtype=None):
         4    105
         dtype: int64
         """
+        warnings.warn(
+            "Series.applymap is deprecated and will be removed "
+            "in a future cuDF release. Use Series.apply instead.",
+            FutureWarning,
+        )
         if not callable(udf):
             raise ValueError("Input UDF must be a callable object.")
         return self._from_data({self.name: self._unaryop(udf)}, self._index)

python/cudf/cudf/tests/test_applymap.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2018-2021, NVIDIA CORPORATION.
+# Copyright (c) 2018-2022, NVIDIA CORPORATION.
 
 from itertools import product
 from math import floor
@@ -29,9 +29,10 @@ def test_applymap_round(nelem, masked):
     sr = Series(data)
 
     # Call applymap
-    out = sr.applymap(
-        lambda x: (floor(x) + 1 if x - floor(x) >= 0.5 else floor(x))
-    )
+    with pytest.warns(FutureWarning):
+        out = sr.applymap(
+            lambda x: (floor(x) + 1 if x - floor(x) >= 0.5 else floor(x))
+        )
 
     if masked:
         # Fill masked values
@@ -50,7 +51,8 @@ def test_applymap_change_out_dtype():
 
     sr = Series(data)
 
-    out = sr.applymap(lambda x: float(x), out_dtype=float)
+    with pytest.warns(FutureWarning):
+        out = sr.applymap(lambda x: float(x), out_dtype=float)
 
     # Check
     expect = np.array(data, dtype=float)

python/cudf/cudf/tests/test_transform.py

@@ -29,6 +29,7 @@ def test_applymap_python_lambda(dtype, udf, testfunc):
     lhs_arr = np.random.random(size).astype(dtype)
     lhs_ser = Series(lhs_arr)
 
-    out_ser = lhs_ser.applymap(udf)
+    with pytest.warns(FutureWarning):
+        out_ser = lhs_ser.applymap(udf)
     result = testfunc(lhs_arr)
     np.testing.assert_almost_equal(result, out_ser.to_numpy())

python/cudf/cudf/tests/test_udf_masked_ops.py

@@ -645,15 +645,17 @@ def test_masked_udf_caching():
 
     data = cudf.Series([1, 2, 3])
     expect = data**2
-    got = data.applymap(lambda x: x**2)
+    with pytest.warns(FutureWarning):
+        got = data.applymap(lambda x: x**2)
 
     assert_eq(expect, got, check_dtype=False)
 
     # update the constant value being used and make sure
     # it does not result in a cache hit
 
     expect = data**3
-    got = data.applymap(lambda x: x**3)
+    with pytest.warns(FutureWarning):
+        got = data.applymap(lambda x: x**3)
     assert_eq(expect, got, check_dtype=False)
 
     # make sure we get a hit when reapplying