class_docstr: Financial Holidays Transformer.
  
  This implementation wraps over holidays [1]_ by vacanza.
  
  Based on the index of ``X``, dates are extracted and passed to ``holidays``. Then
  upon generating the holiday information for that day (or absence of it) based on
  passed financial market information, a boolean series is prepared where ``True``
  indicates the date being a holiday and ``False`` otherwise. ``fit`` is a no-op for
  this transformer.
  
  Parameters
  ----------
  market : str
      An ISO 3166-1 Alpha-2 market code [2]_; not implemented for all countries (see
      documentation [3]_).
  years : Union[int, Iterable[int]], optional
      The year(s) to pre-calculate public holidays for at instantiation.
  expand : bool, optional
      Whether the entire year is calculated when one date from that year is
      requested.
  observed : bool, optional
      Whether to include the dates of when public holiday are observed (e.g. a
      holiday falling on a Sunday being observed the following Monday). False may not
      work for all countries.
  name : str, optional
      name of transformed series.
  
  References
  ----------
  .. [1] https://github.com/vacanza/python-holidays
  .. [2] https://www.iso20022.org/market-identifier-codes
  .. [3] https://python-holidays.readthedocs.io/en/latest/#available-financial-markets
  
  Notes
  -----
  If ``name`` is missing (by default), it is auto-populated as ``{market}_holidays``.
  
  Examples
  --------
  >>> from sktime.transformations.series.holiday import FinancialHolidaysTransformer
  >>>
  >>> import numpy
  >>> data = numpy.random.default_rng(seed=0).random(size=365)
  >>>
  >>> import pandas
  >>> index = pandas.date_range(start="2023-01-01", end="2023-12-31", freq="D")
  >>>
  >>> y = pandas.Series(data, index=index, name="random")
  >>>
  >>> y_t = FinancialHolidaysTransformer("XNYS").fit_transform(y)  # doctest: +SKIP
  >>> y_t.dtype  # doctest: +SKIP
  dtype('bool')
  >>> y_t.sum()  # doctest: +SKIP
  10
  >>> y_t.name  # doctest: +SKIP
  'XNYS_holidays'
code: def __init__(
      self, market, years=None, expand=True, observed=True, name=None
  ):
      self.market = market
      self.years = years
      self.expand = expand
      self.observed = observed
      self.name = name
  
      super().__init__()
  
imports: import pandas
  from sktime.transformations.base import BaseTransformer
label_desc: Use image node_id 1 to create a new FinancialHolidaysTransformer object from inherited base classes: BaseTransformer with example: obj = FinancialHolidaysTransformer(market, years, expand, observed, name)