code: def test_groupby_apply_timegrouper_with_nat_apply_squeeze(
      self, frame_for_truncated_bingrouper
  ):
      df = frame_for_truncated_bingrouper
  
      # We need to create a GroupBy object with only one non-NaT group,
      #  so use a huge freq so that all non-NaT dates will be grouped together
      tdg = Grouper(key="Date", freq="100YE")
      gb = df.groupby(tdg)
  
      # check that we will go through the singular_series path
      #  in _wrap_applied_output_series
      assert gb.ngroups == 1
      assert gb._selected_obj._get_axis(gb.axis).nlevels == 1
  
      # function that returns a Series
      msg = "DataFrameGroupBy.apply operated on the grouping columns"
      with tm.assert_produces_warning(FutureWarning, match=msg):
          res = gb.apply(lambda x: x["Quantity"] * 2)
  
      dti = Index(
          [Timestamp("2013-12-31")], dtype=df["Date"].dtype, name="Date"
      )
      expected = DataFrame(
          [[36, 6, 6, 10, 2]],
          index=dti,
          columns=Index([0, 1, 5, 2, 3], name="Quantity"),
      )
      tm.assert_frame_equal(res, expected)
  
imports: from datetime import datetime, timedelta
  import numpy
  import pytest
  import pytz
  import pandas
  from pandas import DataFrame, DatetimeIndex, Index, MultiIndex, Series, Timestamp, date_range, offsets
  import pandas._testing
  from pandas.core.groupby.grouper import Grouper
  from pandas.core.groupby.ops import BinGrouper
label_desc: Use image node_id 26 for calling the TestGroupBy obj's underlying member method code with example usage: obj.test_groupby_apply_timegrouper_with_nat_apply_squeeze(frame_for_truncated_bingrouper) without return types