title: Statsmodels seasonal_decompose - what is naive about it?
body: <p>Have been working with time series in Python, and using <code>sm.tsa.seasonal_decompose</code>. In the <a href="http://www.statsmodels.org/stable/release/version0.6.html?highlight=seasonal#seasonal-decomposition" rel="noreferrer">docs</a> they introduce the function like this:</p>
  
  <blockquote>
    <p>We added a naive seasonal decomposition tool in the same vein as R’s <code>decompose</code>.</p>
  </blockquote>
  
  <p>Here is a copy of the code from the docs and its output:</p>
  
  <pre><code>import statsmodels.api as sm
  
  dta = sm.datasets.co2.load_pandas().data
  # deal with missing values. see issue
  dta.co2.interpolate(inplace=True)
  
  res = sm.tsa.seasonal_decompose(dta.co2)
  res.plot()
  </code></pre>
  
  <p><a href="https://i.stack.imgur.com/LyUln.png" rel="noreferrer"><img src="https://i.stack.imgur.com/LyUln.png" alt="seasonal decomposition plot"></a></p>
  
  <p>They say it is <em>naive</em> but there is no disclaimer about what is wrong with it. Does anyone know?</p>