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# pandas.Series.tz_convert

Series.tz_convert(tz, axis=0, level=None, copy=<no_default>)

  Convert tz-aware axis to target time zone.

  This method converts the timezone of a datetime-based index from one timezone to another.

  Parameters:
    tz str or tzinfo object or None

      Target time zone. Passing `None` will convert to UTC and remove the timezone information.

    axis{0 or ‘index’, 1 or ‘columns’}, default 0

      The axis to convert

    level int, str, default None

      If axis is a MultiIndex, convert a specific level. Otherwise must be None.

    copy bool, default False

      This keyword is now ignored; changing its value will have no impact on the method.

      Deprecated since version 3.0.0: This keyword is ignored and will be removed in pandas 4.0. Since pandas 3.0, this method always returns a new object using a lazy copy mechanism that defers copies until necessary (Copy-on-Write). See the user guide on Copy-on-Write for more details.

  Returns:
    Series/DataFrame

      Object with time zone converted axis.

  Raises:
    TypeError

      If the axis is tz-naive.

  See also

  `DataFrame.tz_localize`

    Localize tz-naive index of DataFrame to target time zone.

  `Series.tz_localize`

    Localize tz-naive index of Series to target time zone.

  Examples

  Change to another time zone:

      >>> s = pd.Series(
      ...     [1],
      ...     index=pd.DatetimeIndex(["2018-09-15 01:30:00+02:00"]),
      ... )
      >>> s.tz_convert("Asia/Shanghai")
      2018-09-15 07:30:00+08:00    1
      dtype: int64

  Pass None to convert to UTC and get a tz-naive index:

      >>> s = pd.Series([1], index=pd.DatetimeIndex(["2018-09-15 01:30:00+02:00"]))
      >>> s.tz_convert(None)
      2018-09-14 23:30:00    1
      dtype: int64