code: def _get_normalized_X(self, X, doc_lengths):
      return csr_matrix(X.astype(np.float32) / doc_lengths)
  
imports: from scipy.sparse import csr_matrix
  import numpy
  from scattertext.termranking.DocLengthNormalizedFrequencyRanker import DocLengthNormalizedFrequencyRanker
label_desc: Use image node_id 1 for calling the DocLengthDividedFrequencyRanker obj's underlying member method code with example usage: obj._get_normalized_X(X, doc_lengths) and returns: csr_matrix