CLN: Enforce deprecation get_group with tuples of length 1 (#57743)

* CLN: Enforce deprecation get_group with tuples of length 1 * Add in similar deprecation involving iteration * type ignore

Author: rhshadrach

doc/source/whatsnew/v3.0.0.rst

@@ -200,10 +200,12 @@ Removal of prior version deprecations/changes
 - All arguments in :meth:`Series.to_dict` are now keyword only (:issue:`56493`)
 - 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 ``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 silent-downcasting deprecation for :ref:`all relevant methods <whatsnew_220.silent_downcasting>` (:issue:`54710`)
 - In :meth:`DataFrame.stack`, the default value of ``future_stack`` is now ``True``; specifying ``False`` will raise a ``FutureWarning`` (:issue:`55448`)
+- Iterating over a :class:`.DataFrameGroupBy` or :class:`.SeriesGroupBy` will return tuples of length 1 for the groups when grouping by ``level`` a list of length 1 (:issue:`50064`)
 - Methods ``apply``, ``agg``, and ``transform`` will no longer replace NumPy functions (e.g. ``np.sum``) and built-in functions (e.g. ``min``) with the equivalent pandas implementation; use string aliases (e.g. ``"sum"`` and ``"min"``) if you desire to use the pandas implementation (:issue:`53974`)
 - Passing both ``freq`` and ``fill_value`` in :meth:`DataFrame.shift` and :meth:`Series.shift` and :meth:`.DataFrameGroupBy.shift` now raises a ``ValueError`` (:issue:`54818`)
 - Removed :meth:`.DataFrameGroupBy.quantile` and :meth:`.SeriesGroupBy.quantile` supporting bool dtype (:issue:`53975`)

pandas/core/groupby/groupby.py

@@ -919,17 +919,9 @@ def get_group(self, name) -> DataFrame | Series:
  ):
  # GH#25971
  if isinstance(name, tuple) and len(name) == 1:
- # Allow users to pass tuples of length 1 to silence warning
  name = name[0]
- elif not isinstance(name, tuple):
- warnings.warn(
- "When grouping with a length-1 list-like, "
- "you will need to pass a length-1 tuple to get_group in a future "
- "version of pandas. Pass `(name,)` instead of `name` to silence "
- "this warning.",
- FutureWarning,
- stacklevel=find_stack_level(),
- )
+ else:
+ raise KeyError(name)
 
  inds = self._get_index(name)
  if not len(inds):
@@ -1015,18 +1007,11 @@ def __iter__(self) -> Iterator[tuple[Hashable, NDFrameT]]:
  keys = self.keys
  level = self.level
  result = self._grouper.get_iterator(self._selected_obj)
- # error: Argument 1 to "len" has incompatible type "Hashable"; expected "Sized"
- if is_list_like(level) and len(level) == 1: # type: ignore[arg-type]
- # GH 51583
- warnings.warn(
- "Creating a Groupby object with a length-1 list-like "
- "level parameter will yield indexes as tuples in a future version. "
- "To keep indexes as scalars, create Groupby objects with "
- "a scalar level parameter instead.",
- FutureWarning,
- stacklevel=find_stack_level(),
- )
- if isinstance(keys, list) and len(keys) == 1:
+ # mypy: Argument 1 to "len" has incompatible type "Hashable"; expected "Sized"
+ if (
+ (is_list_like(level) and len(level) == 1) # type: ignore[arg-type]
+ or (isinstance(keys, list) and len(keys) == 1)
+ ):
  # GH#42795 - when keys is a list, return tuples even when length is 1
  result = (((key,), group) for key, group in result)
  return result

pandas/tests/groupby/test_categorical.py

@@ -252,11 +252,7 @@ def test_level_get_group(observed):
  names=["Index1", "Index2"],
  ),
  )
- msg = "you will need to pass a length-1 tuple"
- with tm.assert_produces_warning(FutureWarning, match=msg):
- # GH#25971 - warn when not passing a length-1 tuple
- result = g.get_group("a")
-
+ result = g.get_group(("a",))
  tm.assert_frame_equal(result, expected)
 
 

pandas/tests/groupby/test_groupby.py

@@ -2529,19 +2529,14 @@ def test_groupby_string_dtype():
 @pytest.mark.parametrize(
  "level_arg, multiindex", [([0], False), ((0,), False), ([0], True), ((0,), True)]
 )
-def test_single_element_listlike_level_grouping_deprecation(level_arg, multiindex):
+def test_single_element_listlike_level_grouping(level_arg, multiindex):
  # GH 51583
  df = DataFrame({"a": [1, 2], "b": [3, 4], "c": [5, 6]}, index=["x", "y"])
  if multiindex:
  df = df.set_index(["a", "b"])
- depr_msg = (
- "Creating a Groupby object with a length-1 list-like "
- "level parameter will yield indexes as tuples in a future version. "
- "To keep indexes as scalars, create Groupby objects with "
- "a scalar level parameter instead."
- )
- with tm.assert_produces_warning(FutureWarning, match=depr_msg):
- [key for key, _ in df.groupby(level=level_arg)]
+ result = [key for key, _ in df.groupby(level=level_arg)]
+ expected = [(1,), (2,)] if multiindex else [("x",), ("y",)]
+ assert result == expected
 
 
 @pytest.mark.parametrize("func", ["sum", "cumsum", "cumprod", "prod"])
@@ -2880,22 +2875,18 @@ def test_groupby_series_with_datetimeindex_month_name():
  "kwarg, value, name, warn",
  [
  ("by", "a", 1, None),
- ("by", ["a"], 1, FutureWarning),
  ("by", ["a"], (1,), None),
  ("level", 0, 1, None),
- ("level", [0], 1, FutureWarning),
  ("level", [0], (1,), None),
  ],
 )
-def test_depr_get_group_len_1_list_likes(test_series, kwarg, value, name, warn):
+def test_get_group_len_1_list_likes(test_series, kwarg, value, name, warn):
  # GH#25971
  obj = DataFrame({"b": [3, 4, 5]}, index=Index([1, 1, 2], name="a"))
  if test_series:
  obj = obj["b"]
  gb = obj.groupby(**{kwarg: value})
- msg = "you will need to pass a length-1 tuple"
- with tm.assert_produces_warning(warn, match=msg):
- result = gb.get_group(name)
+ result = gb.get_group(name)
  if test_series:
  expected = Series([3, 4], index=Index([1, 1], name="a"), name="b")
  else: