class_docstr: Write out FeatureSets to files on disk.
  
  This is the base class used to create featureset writers for different
  file types.
  
  Parameters
  ----------
  path : :class:`skll.types.PathOrStr`
      A path to the feature file we would like to create. The suffix
      to this filename must be ``.arff``, ``.csv``, ``.jsonlines``,
      ``.libsvm``, ``.ndj``, or ``.tsv``. If ``subsets``
      is not ``None``, when calling the ``write()`` method, path is
      assumed to be a string containing the path to the directory to
      write the feature files with an additional file extension
      specifying the file type. For example ``/foo/.csv``.
  
  feature_set : :class:`skll.data.featureset.FeatureSet`
      The ``FeatureSet`` instance to dump to the file.
  
  quiet : bool, default=True
      Do not print "Writing..." status message to stderr.
  
  subsets : Optional[Dict[str, List[str]]], default=None
      A mapping from subset names to lists of feature names
      that are included in those sets. If given, a feature
      file will be written for every subset (with the name
      containing the subset name as suffix to ``path``).
      Note, since string- valued features are automatically
      converted into boolean features with names of the form
      ``FEATURE_NAME=STRING_VALUE``, when doing the
      filtering, the portion before the ``=`` is all that's
      used for matching. Therefore, you do not need to
      enumerate all of these boolean feature names in your
      mapping.
  
  logger : Optional[logging.Logger], default=None
      A logger instance to use to log messages instead of creating
      a new one by default.
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docstr: Write full data set in Writer's format using `pandas`, rather than row-by-row.
  
  Parameters
  ----------
  feature_set : Ignored
      Not used.
  
  output_file : Ignored
      Not used.
  
  filter_features : Ignored
      Not used.
  
  Raises
  ------
  NotImplementedError
docstr_tok: ["Write","full","data","set","in","Writer","'s","format","using","`","pandas","`",",","rather","than","row-by-row",".","Parameters","--","--","--","--","--","feature_set",":","Ignored","Not","used",".","output_file",":","Ignored","Not","used",".","filter_features",":","Ignored","Not","used",".","Raises","--","--","--","NotImplementedError"]
code: def _write_data(self, feature_set, output_file, filter_features):
      """
      Write full data set in Writer's format using `pandas`, rather than row-by-row.
  
      Parameters
      ----------
      feature_set : Ignored
          Not used.
  
      output_file : Ignored
          Not used.
  
      filter_features : Ignored
          Not used.
  
      Raises
      ------
      NotImplementedError
      """
      raise NotImplementedError
  
imports: import json
  import logging
  import sys
  from csv import DictWriter
  from decimal import Decimal
  from pathlib import Path
  from typing import IO, Any, Dict, List, Optional, Set, Tuple, Union
  import numpy
  import pandas
  from scipy.sparse import issparse
  from sklearn.feature_extraction import DictVectorizer, FeatureHasher
  from skll.data import FeatureSet
  from skll.types import FeatGenerator, FeatureDict, IdType, LabelType, PathOrStr
label_desc: Use image node_id 7 for calling the Writer obj's underlying member method code with example usage: obj._write_data(feature_set, output_file, filter_features) without return types