title: Selecting sublevels of Multiindex columns in pandas
body: <p>I generate a multiindex dataframe like this example</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  
  iterables = [ ['co1', 'co2', 'co3', 'co4'], ['age','weight'] ]
  multi = pd.MultiIndex.from_product(iterables, names= ["Spread", "attribute"])
  
  df = pd.DataFrame(np.random.rand(80).reshape(10,8),index = range(0,10), columns = multi)
  </code></pre>
  
  <p>The columns each have a sublevel attribute called 'weight'</p>
  
  <p>I need to generate a list or (preferably) Series that contains, for a given row, all the 'weight' sub-columns in that row.  In the example picture, I'd want a Series that gave me 0.02, 0.46, 0.33, 0.47.  </p>
  
  <p>Can anyone suggest a nice way to do this? The solutions I've thought of are all gross, and I suspect I have an incomplete understanding of the indexing capabilities of pandas.</p>
  
  <p><a href="https://i.stack.imgur.com/li1TZ.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/li1TZ.png" alt="enter image description here"></a></p>