code: def regression_stats(
      y: pd.Series,
  ) -> List[Tuple[str, str, float, bool]]:
      """Computes regression statistics on response.
  
      Args:
          y (pd.Series): Response.
  
      Returns:
          List[Tuple[str, str, float, bool]]: Tuples of form: (name, description, value, is_lower_better).
      """
      labels = y.values
      labels_avg = np.average(labels)
      labels_max = max(labels)
      labels_min = min(labels)
      return [
          (
              "response_min_val",
              "Minimum value of response.",
              float(labels_min),
              True,
          ),
          (
              "response_avg_val",
              "Average value of response.",
              float(labels_avg),
              True,
          ),
          (
              "response_max_val",
              "Maximum value of response.",
              float(labels_max),
              True,
          ),
      ]
  
file_path: interpret/python/powerlift/src/powerlift/measures/task_measures.py
imports: from math import log, e
  from numbers import Number
  from typing import Iterable, List, Tuple
  import numpy
  import pandas
label_desc: Use image node_id 3 for calling a global function with example usage: regression_stats(y) and returns: list