class_docstr: Exception raised for errors in the input data.
  
  Appropriate for data which is not convertible to the input feature type, columns with all missing values,
  categorical columns with only one category, etc...
  
  Attributes:
      column - The name of the input column which caused the error
      feature_type - The Ludwig feature type which caused the error (number, binary, category...).
      message - An error message describing the situation.
class_docstr_tok: ["Exception","raised","for","errors","in","the","input","data",".","Appropriate","for","data","which","is","not","convertible","to","the","input","feature","type",",","columns","with","all","missing","values",",","categorical","columns","with","only","one","category",",","etc","...","Attributes",":","column","-","The","name","of","the","input","column","which","caused","the","error","feature_type","-","The","Ludwig","feature","type","which","caused","the","error","(","number",",","binary",",","category","...",")",".","message","-","An","error","message","describing","the","situation","."]
code: def __str__(self):
      return f'Column "{self.column_name}" as {self.feature_type} feature: {self.message}'
  
file_path: ludwig/ludwig/error.py
imports: from ludwig.api_annotations import PublicAPI
label_desc: Use image node_id 2 for calling the InputDataError obj's underlying member method code with example usage: obj.__str__() and returns: str, self, str, self, str, self