class_docstr: Country 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 country (and subdivision) 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
  ----------
  country : str
      An ISO 3166-1 Alpha-2 country code. [2]_
  subdiv : str, optional
      The subdivision (e.g. state or province); not implemented for all countries
      (see documentation [3]_). [2]_
  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.
  categories : Tuple[str], optional
      requested holiday categories.
  name : str, optional
      name of transformed series.
  
  References
  ----------
  .. [1] https://github.com/vacanza/python-holidays
  .. [2] https://www.iso.org/obp/ui/#search/code/
  .. [3] https://python-holidays.readthedocs.io/en/latest/#available-countries
  
  Notes
  -----
  If ``name`` is missing (by default), it is auto-populated using ``country`` and
  ``subdiv`` as ``{country}_holidays`` or ``{country}_{subdiv}_holidays``.
  
  Examples
  --------
  >>> from sktime.transformations.series.holiday import CountryHolidaysTransformer
  >>>
  >>> from sktime.datasets import load_airline
  >>> y = load_airline()
  >>>
  >>> y_t = CountryHolidaysTransformer("US").fit_transform(y)  # doctest: +SKIP
  >>> y_t.dtype  # doctest: +SKIP
  dtype('bool')
  >>> y_t.sum()  # doctest: +SKIP
  14
  >>> y_t.name  # doctest: +SKIP
  'US_holidays'
code: def __init__(
      self,
      country,
      subdiv=None,
      years=None,
      expand=True,
      observed=True,
      categories=None,
      name=None,
  ):
      self.country = country
      self.subdiv = subdiv
      self.years = years
      self.expand = expand
      self.observed = observed
      self.categories = categories
      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 CountryHolidaysTransformer object from inherited base classes: BaseTransformer with example: obj = CountryHolidaysTransformer(country, subdiv, years, expand, observed, categories, name)