code: def _check_series_convert_timestamps_localize(
      s: "PandasSeriesLike",
      from_timezone: Optional[str],
      to_timezone: Optional[str],
  ) -> "PandasSeriesLike":
      """
      Convert timestamp to timezone-naive in the specified timezone or local timezone
  
      Parameters
      ----------
      s : pandas.Series
      from_timezone : str
          the timezone to convert from. if None then use local timezone
      to_timezone : str
          the timezone to convert to. if None then use local timezone
  
      Returns
      -------
      pandas.Series
          `pandas.Series` where if it is a timestamp, has been converted to tz-naive
      """
      from pyspark.sql.pandas.utils import (
          require_minimum_pandas_version,
      )
  
      require_minimum_pandas_version()
  
      import pandas as pd
      from pandas.api.types import (  # type: ignore[attr-defined]
          is_datetime64_dtype,
      )
  
      from_tz = from_timezone or _get_local_timezone()
      to_tz = to_timezone or _get_local_timezone()
      # TODO: handle nested timestamps, such as ArrayType(TimestampType())?
      if isinstance(s.dtype, pd.DatetimeTZDtype):
          return s.dt.tz_convert(to_tz).dt.tz_localize(None)
      elif is_datetime64_dtype(s.dtype) and from_tz != to_tz:
          # `s.dt.tz_localize('tzlocal()')` doesn't work properly when including NaT.
          return cast(
              "PandasSeriesLike",
              s.apply(
                  lambda ts: ts.tz_localize(from_tz, ambiguous=False)
                  .tz_convert(to_tz)
                  .tz_localize(None)
                  if ts is not pd.NaT
                  else pd.NaT
              ),
          )
      else:
          return s
  
imports: import datetime
  import itertools
  from typing import Any, Callable, Iterable, List, Optional, Union, TYPE_CHECKING
  from pyspark.sql.types import cast, BooleanType, ByteType, ShortType, IntegerType, IntegralType, LongType, FloatType, DoubleType, DecimalType, StringType, BinaryType, DateType, TimestampType, TimestampNTZType, DayTimeIntervalType, ArrayType, MapType, StructType, StructField, NullType, DataType, UserDefinedType, _create_row
  from pyspark.errors import PySparkTypeError, UnsupportedOperationException, PySparkValueError
label_desc: Use image node_id 8 for calling a global function with example usage: _check_series_convert_timestamps_localize(s, from_timezone, to_timezone) and returns: s, cast, s