code: def _abnormal_value_repair(df, dt_col, mode, threshold):
      """
      This repair is used to replace detected abnormal data with the last non N/A number.
      """
      invalidInputError(
          mode in ["absolute", "relative"],
          f"mode should be one of ['absolute', 'relative'], but found {mode}.",
      )
      if mode == "absolute":
          invalidInputError(
              isinstance(threshold, tuple),
              "threshold should be a tuple when mode is set to 'absolute', "
              f"but found {type(threshold)}.",
          )
          invalidInputError(
              threshold[0] <= threshold[1],
              "threshold should be a tuple (min_value, max_value) when mode "
              f"is set to 'absolute', but found {threshold}.",
          )
          res_df = _abs_abnormal_value_repair(df, dt_col, threshold)
      else:
          invalidInputError(
              isinstance(threshold, float),
              "threshold should be a float when mode is set to 'relative', "
              f"but found {type(threshold)}.",
          )
          res_df = _rel_abnormal_value_repair(df, dt_col, threshold)
      return res_df
  
file_path: BigDL/python/chronos/src/bigdl/chronos/data/utils/quality_inspection.py
imports: import pandas
  import numpy
  from bigdl.nano.utils.common import invalidInputError
  import logging
label_desc: Use image node_id 9 for calling a global function with example usage: _abnormal_value_repair(df, dt_col, mode, threshold) and returns: res_df