code: def test__flag_jumps_single_col_absolute_scale_flags_large_jump(
      timeseries_dataframe,
  ):
      """
      Test utility function for flagging jumps with absolute scale.
      Here, a large threshold is used to verify only one row is flagged.
      """
  
      # Setup
      df = timeseries_dataframe
  
      # Exercise
      result_incr = _flag_jumps_single_col(
          df,
          "col5",
          scale="absolute",
          direction="increasing",
          threshold=5,
      )
      result_decr = _flag_jumps_single_col(
          df,
          "col5",
          scale="absolute",
          direction="decreasing",
          threshold=5,
      )
      result_any = _flag_jumps_single_col(
          df, "col5", scale="absolute", direction="any", threshold=5
      )
  
      # Verify
      np.testing.assert_array_equal(result_incr.array, [0] * 10)
      np.testing.assert_array_equal(
          result_decr.array, [0, 0, 0, 0, 0, 0, 0, 0, 0, 1]
      )
      np.testing.assert_array_equal(
          result_any.array, [0, 0, 0, 0, 0, 0, 0, 0, 0, 1]
      )
  
imports: import numpy
  import pandas
  import pytest
  import janitor.timeseries
  from janitor.errors import JanitorError
  from janitor.timeseries import _flag_jumps_single_col
label_desc: Use image node_id 8 for calling a global function with example usage: test__flag_jumps_single_col_absolute_scale_flags_large_jump(timeseries_dataframe) without return types