class_docstr: Convert a pandas DataFrame to a suitable VW format.
  Instances of this class are built with classes such as SimpleLabel,
  MulticlassLabel, Feature or Namespace.
  
  The class also provided a convenience constructor to initialize the class
  based on the target/features column names only.
class_docstr_tok: ["Convert","a","pandas","DataFrame","to","a","suitable","VW","format",".","Instances","of","this","class","are","built","with","classes","such","as","SimpleLabel",",","MulticlassLabel",",","Feature","or","Namespace",".","The","class","also","provided","a","convenience","constructor","to","initialize","the","class","based","on","the","target\/features","column","names","only","."]
docstr: Raises error if some columns are missing.
  
  Raises:
      ValueError: If one or more columns are not in the dataframe.
docstr_tok: ["Raises","error","if","some","columns","are","missing",".","Raises",":","ValueError",":","If","one","or","more","columns","are","not","in","the","dataframe","."]
code: def raise_missing_col_error(self, missing_cols_dict):
      """Raises error if some columns are missing.
  
      Raises:
          ValueError: If one or more columns are not in the dataframe.
      """
      error_msg = ""
      for attribute_name, missing_cols in missing_cols_dict.items():
          missing_cols_str = repr(missing_cols)[1:-1]
          if len(error_msg) > 0:
              error_msg += " "
          error_msg += "In '{attribute}': column(s) {colnames} not found in dataframe.".format(
              attribute=attribute_name,
              colnames=missing_cols_str,
          )
      raise ValueError(error_msg)
  
imports: import warnings
  import numpy
  import pandas
  from typing import Any, Hashable, List, Optional, Tuple, Type, Union
label_desc: Use image node_id 9 for calling the DFtoVW obj's underlying member method code with example usage: obj.raise_missing_col_error(missing_cols_dict) without return types