FIX-#4966: Fix to_timedelta to return Series instead of TimedeltaIndex

docs/release_notes/release_notes-0.16.0.rst

@@ -55,6 +55,7 @@ Key Features and Updates
   * FIX-#4996: Evaluate BenchmarkMode at each function call (#4997)
   * FIX-#4022: Fixed empty data frame with index (#4910)
   * FIX-#4090: Fixed check if the index is trivial (#4936)
+  * FIX-#4966: Fix `to_timedelta` to return Series instead of TimedeltaIndex (#5028)
   * FIX-#5042: Fix series __getitem__ with invalid strings (#5048)
   * FIX-#4691: Fix binary operations between virtual partitions (#5049)  
   * FIX-#5045: Fix ray virtual_partition.wait with duplicate object refs (#5058)

modin/core/storage_formats/base/query_compiler.py

@@ -1320,6 +1320,27 @@ def to_numeric(self, *args, **kwargs):  # noqa: PR02
         """
         return SeriesDefault.register(pandas.to_numeric)(self, *args, **kwargs)
 
+    @doc_utils.add_one_column_warning
+    @doc_utils.add_refer_to("to_timedelta")
+    def to_timedelta(self, unit="ns", errors="raise"):  # noqa: PR02
+        """
+        Convert argument to timedelta.
+
+        Parameters
+        ----------
+        unit : str, default: "ns"
+            Denotes the unit of the arg for numeric arg. Defaults to "ns".
+        errors : {"ignore", "raise", "coerce"}, default: "raise"
+
+        Returns
+        -------
+        BaseQueryCompiler
+            New QueryCompiler with converted to timedelta values.
+        """
+        return SeriesDefault.register(pandas.to_timedelta)(
+            self, unit=unit, errors=errors
+        )
+
     # FIXME: get rid of `**kwargs` parameter (Modin issue #3108).
     @doc_utils.add_one_column_warning
     @doc_utils.add_refer_to("Series.unique")

modin/core/storage_formats/pandas/query_compiler.py

@@ -1360,6 +1360,12 @@ def stack(self, level, dropna):
             pandas.to_numeric(df.squeeze(axis=1), *args, **kwargs)
         )
     )
+    to_timedelta = Map.register(
+        lambda s, *args, **kwargs: pandas.to_timedelta(
+            s.squeeze(axis=1), *args, **kwargs
+        ).to_frame(),
+        dtypes="timedelta64[ns]",
+    )
 
     # END Map partitions operations
 

modin/pandas/__init__.py

@@ -55,7 +55,6 @@
         DatetimeIndex,
         Timedelta,
         Timestamp,
-        to_timedelta,
         set_eng_float_format,
         options,
         set_option,
@@ -251,6 +250,7 @@ def init_remote_ray(partition):
     crosstab,
     lreshape,
     wide_to_long,
+    to_timedelta,
 )
 
 from modin._compat.pandas_api.namespace import pivot_table

modin/pandas/general.py

@@ -759,3 +759,18 @@ def get_names(obj):
         return list(names[0]) if is_list_like(names[0]) else [names[0]]
     else:
         return None
+
+
+@_inherit_docstrings(pandas.to_datetime, apilink="pandas.to_timedelta")
+@enable_logging
+def to_timedelta(arg, unit=None, errors="raise"):  # noqa: PR01, RT01, D200
+    """
+    Convert argument to timedelta.
+
+    Accepts str, timedelta, list-like or Series for arg parameter.
+    Returns a Series if and only if arg is provided as a Series.
+    """
+    if isinstance(arg, Series):
+        query_compiler = arg._query_compiler.to_timedelta(unit=unit, errors=errors)
+        return Series(query_compiler=query_compiler)
+    return pandas.to_timedelta(arg, unit=unit, errors=errors)

modin/pandas/test/test_general.py

@@ -26,6 +26,7 @@
     test_data_keys,
     df_equals,
     sort_index_for_equal_values,
+    eval_general,
 )
 
 
@@ -801,3 +802,25 @@ def test_empty_dataframe():
 def test_empty_series():
     s = pd.Series([])
     pd.to_numeric(s)
+
+
+@pytest.mark.parametrize(
+    "arg",
+    [[1, 2], ["a"], 1, "a"],
+    ids=["list_of_ints", "list_of_invalid_strings", "scalar", "invalid_scalar"],
+)
+def test_to_timedelta(arg):
+    # This test case comes from
+    # https://github.com/modin-project/modin/issues/4966
+    eval_general(pd, pandas, lambda lib: lib.to_timedelta(arg))
+
+
+@pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
+def test_series_to_timedelta(data):
+    def make_frame(lib):
+        series = lib.Series(
+            next(iter(data.values())) if isinstance(data, dict) else data
+        )
+        return lib.to_timedelta(series).to_frame(name="timedelta")
+
+    eval_general(pd, pandas, make_frame)