code: def transform_series(
      series: pd.Series[Any]
      | pd.Index[Any]
      | pd.api.extensions.ExtensionArray,
  ) -> npt.NDArray[Any]:
      """Transforms a Pandas series into serialized form
  
      Args:
          series (pd.Series) : the Pandas series to transform
  
      Returns:
          ndarray
  
      """
      import pandas as pd
  
      # not checking for pd here, this function should only be called if it
      # is already known that series is a Pandas Series type
      if isinstance(series, pd.PeriodIndex):
          vals = series.to_timestamp().values
      else:
          vals = series.to_numpy()
      return vals
  
imports: from __future__ import annotations
  import logging
  import datetime
  import uuid
  from functools import lru_cache
  from threading import Lock
  from typing import TYPE_CHECKING, Any
  import numpy
  from ..core.types import ID
  from ..settings import settings
  from .strings import format_docstring
label_desc: Use image node_id 14 for calling a global function with example usage: transform_series(series) and returns: vals