title: Why does sklearn Imputer need to fit?
body: <p>I'm really new in this whole machine learning thing and I'm taking an online course on this subject. In this course, the instructors showed the following piece of code:</p>
  
  <pre><code>imputer = Inputer(missing_values = 'Nan', strategy = 'mean', axis=0)
  imputer = Imputer.fit(X[:, 1:3])
  X[:, 1:3] = imputer.transform(X[:, 1:3])
  </code></pre>
  
  <p>I don't really get why this imputer object needs to <code>fit</code>. I mean, I´m just trying to get rid of missing values in my columns by replacing them with the column mean. From the little I know about programming, this is a pretty simple, iterative procedure, and wouldn´t require a model that has to train on data to be accomplished.</p>
  
  <p>Can someone please explain how this imputer thing works and why it requires training to replace some missing values by the column mean?
  I have read sci-kit's documentation, but it just shows how to use the methods, and not why they´re required.</p>
  
  <p>Thank you.</p>