title: Pandas MultiIndex: Selecting a column knowing only the second index?
body: <p>I'm working with the following DataFrame:</p>
  
  <pre><code>   age  height  weight  shoe_size
  0  8.0     6.0     2.0        1.0
  1  8.0     NaN     2.0        1.0
  2  6.0     1.0     4.0        NaN
  3  5.0     1.0     NaN        0.0
  4  5.0     NaN     1.0        NaN
  5  3.0     0.0     1.0        0.0
  </code></pre>
  
  <p>I added another header to the df in this way:</p>
  
  <pre><code>zipped = list(zip(df.columns, ["RHS", "height", "weight", "shoe_size"]))
  
  df.columns = pd.MultiIndex.from_tuples(zipped)
  </code></pre>
  
  <p>So this is the new DataFrame:</p>
  
  <pre><code>   age height weight shoe_size
     RHS height weight shoe_size
  0  8.0    6.0    2.0       1.0
  1  8.0    NaN    2.0       1.0
  2  6.0    1.0    4.0       NaN
  3  5.0    1.0    NaN       0.0
  4  5.0    NaN    1.0       NaN
  5  3.0    0.0    1.0       0.0
  </code></pre>
  
  <p>Now I know how to select the first column, by using the corresponding tuple <code>("age", "RHS")</code>:</p>
  
  <pre><code>df[("age", "RHS")]
  </code></pre>
  
  <p>but I was wondering about how to do this by using only the second index "RHS".
  Ideally something like:</p>
  
  <pre><code>df[(any, "RHS")]
  </code></pre>