code: def highlight_min(data, color="lightgreen"):
      """
      Highlights the minimum in a Series or DataFrame.
      """
      attr = f"background-color: {color}"
      if data.ndim == 1:  # Series from .apply(axis=0) or axis=1
          is_min = data == data.min()
          return [attr if v else "" for v in is_min]
      else:  # from .apply(axis=None)
          return pd.DataFrame(
              np.where(is_min, attr, ""),
              index=data.index,
              columns=data.columns,
          )
  
file_path: gluonts/src/gluonts/nursery/spliced_binned_pareto/training_functions.py
imports: from typing import Optional
  import matplotlib
  import matplotlib.pyplot
  import numpy
  import pandas
  import torch.nn
  import torch.optim
  from .distr_tcn import DistributionalTCN
label_desc: Use image node_id 4 for calling a global function with example usage: highlight_min(data, color) and returns: unknown, pd