class_docstr: Removes features.
  
  This can be used in a pipeline when you want to remove certain features. The `transform_one`
  method is pure, and therefore returns a fresh new dictionary instead of removing the specified
  keys from the input.
  
  Parameters
  ----------
  keys
      Key(s) to discard.
  
  Examples
  --------
  
  >>> from river import compose
  
  >>> x = {'a': 42, 'b': 12, 'c': 13}
  >>> compose.Discard('a', 'b').transform_one(x)
  {'c': 13}
  
  You can chain a discarder with any estimator in order to apply said estimator to the
  desired features.
  
  >>> from river import feature_extraction as fx
  
  >>> x = {'sales': 10, 'shop': 'Ikea', 'country': 'Sweden'}
  
  >>> pipeline = (
  ...     compose.Discard('shop', 'country') |
  ...     fx.PolynomialExtender()
  ... )
  >>> pipeline.transform_one(x)
  {'sales': 10, 'sales*sales': 100}
class_docstr_tok: ["Removes","features",".","This","can","be","used","in","a","pipeline","when","you","want","to","remove","certain","features",".","The","`","transform_one","`","method","is","pure",",","and","therefore","returns","a","fresh","new","dictionary","instead","of","removing","the","specified","keys","from","the","input",".","Parameters","--","--","--","--","--","keys","Key","(","s",")","to","discard",".","Examples","--","--","--","--",">",">",">","from","river","import","compose",">",">",">","x","=","{","'","a","'",":","42",",","'","b","'",":","12",",","'","c","'",":","13","}",">",">",">","compose.Discard","(","'","a","'",",","'","b","'",")",".transform_one","(","x",")","{","'","c","'",":","13","}","You","can","chain","a","discarder","with","any","estimator","in","order","to","apply","said","estimator","to","the","desired","features",".",">",">",">","from","river","import","feature_extraction","as","fx",">",">",">","x","=","{","'sales","'",":","10",",","'shop","'",":","'Ikea","'",",","'country","'",":","'Sweden","'","}",">",">",">","pipeline","=","(","...","compose.Discard","(","'shop","'",",","'country","'",")","|","...","fx.PolynomialExtender","(",")","...",")",">",">",">","pipeline.transform_one","(","x",")","{","'sales","'",":","10",",","'sales","*","sales","'",":","100","}"]
code: def __init__(self, *keys: tuple[base.typing.FeatureName]):
      self.keys = set(keys)
  
imports: from __future__ import annotations
  from river import base
label_desc: Use image node_id 1 to create a new Discard object from inherited base classes: base with example: obj = Discard()