code: def test_timestamp_groupby_quantile(unit):
      # GH 33168
      dti = pd.date_range(
          start="2020-04-19 00:00:00",
          freq="1min",
          periods=100,
          tz="UTC",
          unit=unit,
      ).floor("1h")
      df = DataFrame(
          {
              "timestamp": dti,
              "category": list(range(1, 101)),
              "value": list(range(101, 201)),
          }
      )
  
      result = df.groupby("timestamp").quantile([0.2, 0.8])
  
      mi = pd.MultiIndex.from_product(
          [dti[::99], [0.2, 0.8]], names=("timestamp", None)
      )
      expected = DataFrame(
          [
              {"category": 12.8, "value": 112.8},
              {"category": 48.2, "value": 148.2},
              {"category": 68.8, "value": 168.8},
              {"category": 92.2, "value": 192.2},
          ],
          index=mi,
      )
  
      tm.assert_frame_equal(result, expected)
  
imports: import numpy
  import pytest
  import pandas
  from pandas import DataFrame, Index
  import pandas._testing
label_desc: Use image node_id 20 for calling a global function with example usage: test_timestamp_groupby_quantile(unit) without return types