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.
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code: def __init__(self, column_name: str, feature_type: str, message: str):
      self.column_name = column_name
      self.feature_type = feature_type
      self.message = message
      super().__init__(message)
  
file_path: ludwig/ludwig/error.py
imports: from ludwig.api_annotations import PublicAPI
label_desc: Use image node_id 1 to create a new InputDataError object from inherited base classes: LudwigError, ValueError with example: obj = InputDataError(column_name, feature_type, message)