class_docstr: A lightweight pipeline to chain transformers.
  
  Parameters
  ----------
  transformers : list
      A list of Transformer instances.
class_docstr_tok: ["A","lightweight","pipeline","to","chain","transformers",".","Parameters","--","--","--","--","--","transformers",":","list","A","list","of","Transformer","instances","."]
code: def transform(self, X):
      for transformer in self.transformers:
          X = transformer.transform(X)
      return X
  
imports: from __future__ import division
  import numpy
  from sklearn.preprocessing import LabelBinarizer
  from sklearn.utils import column_or_1d
label_desc: Use image node_id 3 for calling the Pipeline obj's underlying member method code with example usage: obj.transform(X) and returns: X