code: def _check_series_localize_timestamps(s, timezone):
      
      from pyspark.sql.utils import require_minimum_pandas_version
      require_minimum_pandas_version()
  
      from pandas.api.types import is_datetime64tz_dtype
      tz = timezone or _get_local_timezone()
      # TODO: handle nested timestamps, such as ArrayType(TimestampType())?
      if is_datetime64tz_dtype(s.dtype):
          return s.dt.tz_convert(tz).dt.tz_localize(None)
      else:
          return s
docs: Convert timezone aware timestamps to timezone-naive in the specified timezone or local timezone.
  
      If the input series is not a timestamp series, then the same series is returned. If the input
      series is a timestamp series, then a converted series is returned.
  
      :param s: pandas.Series
      :param timezone: the timezone to convert. if None then use local timezone
      :return pandas.Series that have been converted to tz-naive