class_docstr: Search in column[s] for values that contains only special characters.
  
  Parameters
  ----------
  columns : Union[Hashable, List[Hashable]] , default: None
      Columns to check, if none are given checks all columns except ignored ones.
  ignore_columns : Union[Hashable, List[Hashable]] , default: None
      Columns to ignore, if none given checks based on columns variable.
  n_most_common : int , default: 2
      Number of most common special-only samples to show in results
  n_top_columns : int , optional
      amount of columns to show ordered by feature importance (date, index, label are first)
  n_samples: int = 10_000_000,
      random_state: int = 42,
class_docstr_tok: ["Search","in","column","[","s","]","for","values","that","contains","only","special","characters",".","Parameters","--","--","--","--","--","columns",":","Union","[","Hashable",",","List","[","Hashable","]","]",",","default",":","None","Columns","to","check",",","if","none","are","given","checks","all","columns","except","ignored","ones",".","ignore_columns",":","Union","[","Hashable",",","List","[","Hashable","]","]",",","default",":","None","Columns","to","ignore",",","if","none","given","checks","based","on","columns","variable",".","n_most_common",":","int",",","default",":","2","Number","of","most","common","special-only","samples","to","show","in","results","n_top_columns",":","int",",","optional","amount","of","columns","to","show","ordered","by","feature","importance","(","date",",","index",",","label","are","first",")","n_samples",":","int","=","10_000_000",",","random_state",":","int","=","42",","]
code: def __init__(
      self,
      columns: Union[Hashable, List[Hashable], None] = None,
      ignore_columns: Union[Hashable, List[Hashable], None] = None,
      n_most_common: int = 2,
      n_top_columns: int = 10,
      n_samples: int = 10_000_000,
      random_state: int = 42,
      **kwargs,
  ):
      super().__init__(**kwargs)
      self.columns = columns
      self.ignore_columns = ignore_columns
      self.n_most_common = n_most_common
      self.n_top_columns = n_top_columns
      self.n_samples = n_samples
      self.random_state = random_state
  
file_path: deepchecks/deepchecks/tabular/checks/data_integrity/special_chars.py
imports: from collections import defaultdict
  from typing import List, Union
  import pandas
  from pandas.api.types import infer_dtype
  from deepchecks.core import CheckResult, ConditionCategory, ConditionResult
  from deepchecks.tabular import Context, SingleDatasetCheck
  from deepchecks.tabular.utils.feature_importance import N_TOP_MESSAGE, column_importance_sorter_df
  from deepchecks.tabular.utils.messages import get_condition_passed_message
  from deepchecks.utils.dataframes import select_from_dataframe
  from deepchecks.utils.strings import format_percent, string_baseform
  from deepchecks.utils.typing import Hashable
label_desc: Use image node_id 1 to create a new SpecialCharacters object from inherited base classes: SingleDatasetCheck with example: obj = SpecialCharacters(columns, ignore_columns, n_most_common, n_top_columns, n_samples, random_state)