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: Check if the columns are in the dataframe.
docstr_tok: ["Check","if","the","columns","are","in","the","dataframe","."]
code: def check_missing_columns_df(self):
      """Check if the columns are in the dataframe."""
      missing_cols = {}
      df_colnames = set(self.df.columns)
  
      # pytype: disable=attribute-error
      try:
          label_columns = self.label.columns
      except AttributeError:
          pass
      else:
          type_label = type(self.label).__name__
          missing_cols[type_label] = label_columns - df_colnames
  
      try:
          tag_columns = self.tag.columns
      except AttributeError:
          pass
      else:
          missing_cols["tag"] = tag_columns - df_colnames
      # pytype: enable=attribute-error
  
      all_features = [
          feature
          for namespace in self.namespaces
          for feature in namespace.features
      ]
      missing_features_cols = set()
      for feature in all_features:
          missing_features_cols.update(feature.columns - df_colnames)
  
      missing_cols["Feature"] = missing_features_cols
  
      missing_cols = {
          key: sorted(list(value))
          for (key, value) in missing_cols.items()
          if len(value) > 0
      }
      if missing_cols:
          self.raise_missing_col_error(missing_cols)
  
imports: import warnings
  import numpy
  import pandas
  from typing import Any, Hashable, List, Optional, Tuple, Type, Union
label_desc: Use image node_id 8 for calling the DFtoVW obj's underlying member method code with example usage: obj.check_missing_columns_df() without return types