code: def test_groupby_quantile_NA_float(any_float_dtype):
      # GH#42849
      df = DataFrame(
          {"x": [1, 1], "y": [0.2, np.nan]}, dtype=any_float_dtype
      )
      result = df.groupby("x")["y"].quantile(0.5)
      exp_index = Index([1.0], dtype=any_float_dtype, name="x")
  
      if any_float_dtype in ["Float32", "Float64"]:
          expected_dtype = any_float_dtype
      else:
          expected_dtype = None
  
      expected = pd.Series(
          [0.2], dtype=expected_dtype, index=exp_index, name="y"
      )
      tm.assert_series_equal(result, expected)
  
      result = df.groupby("x")["y"].quantile([0.5, 0.75])
      expected = pd.Series(
          [0.2] * 2,
          index=pd.MultiIndex.from_product(
              (exp_index, [0.5, 0.75]), names=["x", None]
          ),
          name="y",
          dtype=expected_dtype,
      )
      tm.assert_series_equal(result, expected)
  
imports: import numpy
  import pytest
  import pandas
  from pandas import DataFrame, Index
  import pandas._testing
label_desc: Use image node_id 13 for calling a global function with example usage: test_groupby_quantile_NA_float(any_float_dtype) without return types