class_docstr: Class which returns from a check with result that can later be used for automatic pipelines and display value.
  
  Class containing the result of a check
  
  The class stores the results and display of the check. Evaluating the result in an IPython console / notebook
  will show the result display output.
  
  Parameters
  ----------
  json_data: Union[str, Dict]
      Json data
class_docstr_tok: ["Class","which","returns","from","a","check","with","result","that","can","later","be","used","for","automatic","pipelines","and","display","value",".","Class","containing","the","result","of","a","check","The","class","stores","the","results","and","display","of","the","check",".","Evaluating","the","result","in","an","IPython","console","\/","notebook","will","show","the","result","display","output",".","Parameters","--","--","--","--","--","json_data",":","Union","[","str",",","Dict","]","Json","data"]
docstr: Conditions are already processed it is to prevent errors.
docstr_tok: ["Conditions","are","already","processed","it","is","to","prevent","errors","."]
code: def process_conditions(self) -> List[Condition]:
      """Conditions are already processed it is to prevent errors."""
      pass
  
imports: import base64
  import io
  from typing import Any, Dict, List, Union
  import jsonpickle
  import pandas
  import plotly
  from deepchecks.core.check_result import CheckFailure, CheckResult, DisplayMap
  from deepchecks.core.condition import Condition, ConditionCategory, ConditionResult
  from deepchecks.utils.html import imagetag
label_desc: Use image node_id 2 for calling the CheckResultJson obj's underlying member method code with example usage: obj.process_conditions() without return types