code: def test_agg_timezone_round_trip():
      # GH 15426
      ts = pd.Timestamp("2016-01-01 12:00:00", tz="US/Pacific")
      df = DataFrame(
          {
              "a": 1,
              "b": [ts + dt.timedelta(minutes=nn) for nn in range(10)],
          }
      )
  
      result1 = df.groupby("a")["b"].agg("min").iloc[0]
      result2 = df.groupby("a")["b"].agg(lambda x: np.min(x)).iloc[0]
      result3 = df.groupby("a")["b"].min().iloc[0]
  
      assert result1 == ts
      assert result2 == ts
      assert result3 == ts
  
      dates = [
          pd.Timestamp(f"2016-01-0{i:d} 12:00:00", tz="US/Pacific")
          for i in range(1, 5)
      ]
      df = DataFrame({"A": ["a", "b"] * 2, "B": dates})
      grouped = df.groupby("A")
  
      ts = df["B"].iloc[0]
      assert ts == grouped.nth(0)["B"].iloc[0]
      assert ts == grouped.head(1)["B"].iloc[0]
      assert ts == grouped.first()["B"].iloc[0]
  
      # GH#27110 applying iloc should return a DataFrame
      msg = "DataFrameGroupBy.apply operated on the grouping columns"
      with tm.assert_produces_warning(FutureWarning, match=msg):
          assert ts == grouped.apply(lambda x: x.iloc[0]).iloc[0, 1]
  
      ts = df["B"].iloc[2]
      assert ts == grouped.last()["B"].iloc[0]
  
      # GH#27110 applying iloc should return a DataFrame
      msg = "DataFrameGroupBy.apply operated on the grouping columns"
      with tm.assert_produces_warning(FutureWarning, match=msg):
          assert ts == grouped.apply(lambda x: x.iloc[-1]).iloc[0, 1]
  
imports: import datetime
  from functools import partial
  import numpy
  import pytest
  from pandas.errors import SpecificationError
  import pandas
  from pandas import DataFrame, Index, MultiIndex, PeriodIndex, Series, date_range, period_range
  import pandas._testing
  from pandas.io.formats.printing import pprint_thing
label_desc: Use image node_id 18 for calling a global function with example usage: test_agg_timezone_round_trip() without return types