title: Assigning NaN to -1 after performing StandardScaler
body: <p>I want to <strong>StandardScaler</strong> (Through SK learn) certain DataFrame, which contains a lot of <strong>NaN</strong> values and after performing this scaler shift I want to assign all <code>NaN</code> to -1. How this is possible as we know that StandardScaler doesn't work with NaN values? </p>
  
  <p>If there is any other solution (Which is not dependent on <strong>Scikit Learn</strong>) also please mention that. </p>
  
  <pre><code>df = pd.DataFrame(StandardScaler().fit_transform(values_to_scale.values))
  </code></pre>
  
  <p>I get the following error message:    </p>
  
  <pre><code>ValueError: Input contains NaN, infinity or a value too large for dtype('float64').
  </code></pre>