code: def sparse_var(X):
      """
      Compute variance from
      :param X:
      :return:
      """
      Xc = X.copy()
      Xc.data **= 2
      return np.array(Xc.mean(axis=0) - np.power(X.mean(axis=0), 2))[0]
  
imports: from abc import ABCMeta, abstractmethod
  from typing import Tuple
  import numpy
  import pandas
  from scattertext.ParsedCorpus import ParsedCorpus
  from scipy import stats
  from scipy.sparse import vstack
  from scattertext.util import inherits_from
  from scattertext.termranking import AbsoluteFrequencyRanker
  from scattertext.termranking.TermRanker import TermRanker
label_desc: Use image node_id 1 for calling a global function with example usage: sparse_var(X) and returns: np