title: fit_transform() takes 2 positional arguments but 3 were given with LabelBinarizer
body: <p>I am totally new to Machine Learning and I have been working with unsupervised learning technique.</p>
  <p>Image shows my sample Data(After all Cleaning) Screenshot :
  <a href="https://i.stack.imgur.com/sxXbT.png" rel="noreferrer">Sample Data</a></p>
  <p>I have this two Pipline built to Clean the Data:</p>
  <pre><code>num_attribs = list(housing_num)
  cat_attribs = [&quot;ocean_proximity&quot;]
  
  print(type(num_attribs))
  
  num_pipeline = Pipeline([
      ('selector', DataFrameSelector(num_attribs)),
      ('imputer', Imputer(strategy=&quot;median&quot;)),
      ('attribs_adder', CombinedAttributesAdder()),
      ('std_scaler', StandardScaler()),
  ])
  
  cat_pipeline = Pipeline([
      ('selector', DataFrameSelector(cat_attribs)),
      ('label_binarizer', LabelBinarizer())
  ])
  </code></pre>
  <p>Then I did the union of this two pipelines and the code for the same is shown below :</p>
  <pre><code>from sklearn.pipeline import FeatureUnion
  
  full_pipeline = FeatureUnion(transformer_list=[
          (&quot;num_pipeline&quot;, num_pipeline),
          (&quot;cat_pipeline&quot;, cat_pipeline),
      ])
  </code></pre>
  <p>Now I am trying to do fit_transform on the <a href="https://i.stack.imgur.com/HJ30l.png" rel="noreferrer">Data</a> But Its showing Me the Error.</p>
  <p>Code for Transformation:</p>
  <pre><code>housing_prepared = full_pipeline.fit_transform(housing)
  housing_prepared
  </code></pre>
  <p>Error message:</p>
  <blockquote>
  <p>fit_transform() takes 2 positional arguments but 3 were given</p>
  </blockquote>