

"""simple docstring"""






import itertools
from dataclasses import dataclass
from typing import Optional

import pandas as pd
import pyarrow as pa

import datasets
from datasets.table import table_cast
@dataclass
class        _lowercase					(     datasets.BuilderConfig     ):
     _lowerCamelCase     =       None


class        _lowercase					(     datasets.ArrowBasedBuilder     ):
     _lowerCamelCase     =       PandasConfig







     def 	lowerCAmelCase__    (      self       ):
      return datasets.DatasetInfo(features=self.config.features       )







     def 	lowerCAmelCase__    (      self ,						UpperCamelCase_       ):
      if not self.config.data_files:
       raise ValueError(f'''At least one data file must be specified, but got data_files={self.config.data_files}'''       )
      __magic_name__     =      dl_manager.download_and_extract(self.config.data_files       )
      if isinstance(UpperCamelCase_ ,						(str, list, tuple)       ):
       __magic_name__     =      data_files
       if isinstance(UpperCamelCase_ ,						UpperCamelCase_       ):
        __magic_name__     =      [files]
       # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
       __magic_name__     =      [dl_manager.iter_files(UpperCamelCase_       ) for file in files]
       return [datasets.SplitGenerator(name=datasets.Split.TRAIN ,						gen_kwargs={'''files''': files}       )]
      __magic_name__     =      []
      for split_name, files in data_files.items():
       if isinstance(UpperCamelCase_ ,						UpperCamelCase_       ):
        __magic_name__     =      [files]
       # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
       __magic_name__     =      [dl_manager.iter_files(UpperCamelCase_       ) for file in files]
       splits.append(datasets.SplitGenerator(name=UpperCamelCase_ ,						gen_kwargs={'''files''': files}       )       )
      return splits







     def 	lowerCAmelCase__    (      self ,						UpperCamelCase_       ):
      if self.config.features is not None:
       # more expensive cast to support nested features with keys in a different order
       # allows str <-> int/float or str to Audio for example
       __magic_name__     =      table_cast(UpperCamelCase_ ,						self.config.features.arrow_schema       )
      return pa_table







     def 	lowerCAmelCase__    (      self ,						UpperCamelCase_       ):
      for i, file in enumerate(itertools.chain.from_iterable(UpperCamelCase_       )       ):
       with open(UpperCamelCase_ ,						'''rb'''       ) as f:
        __magic_name__     =      pa.Table.from_pandas(pd.read_pickle(UpperCamelCase_       )       )
        yield i, self._cast_table(UpperCamelCase_       )




"""simple docstring"""






def 	lowercase      (   ) ->      int:
 return 1





def 	lowercase      (   __UpperCamelCase						) ->      int:
 return 0 if x < 0 else two_pence(x - 2						) + one_pence()





def 	lowercase      (   __UpperCamelCase						) ->      int:
 return 0 if x < 0 else five_pence(x - 5						) + two_pence(__UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase						) ->      int:
 return 0 if x < 0 else ten_pence(x - 10						) + five_pence(__UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase						) ->      int:
 return 0 if x < 0 else twenty_pence(x - 20						) + ten_pence(__UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase						) ->      int:
 return 0 if x < 0 else fifty_pence(x - 50						) + twenty_pence(__UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase						) ->      int:
 return 0 if x < 0 else one_pound(x - 100						) + fifty_pence(__UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase						) ->      int:
 return 0 if x < 0 else two_pound(x - 200						) + one_pound(__UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase = 200						) ->      int:
 return two_pound(__UpperCamelCase						)


if __name__ == "__main__":
 print(solution(int(input().strip())))

