title: Pandas - subsetting dataframe - getting all values of the outermost index level
body: <p>Consider this dataframe:</p>
  
  <pre><code>np.random.seed(0)
  index = pd.MultiIndex.from_product([['a', 'b'], ['c', 'd'], ['e', 'f']], names=['first', 'second', 'third'])
  df = pd.DataFrame(data=np.random.randint(0,10,size=(8, 3)), index=index, columns=['foo', 'bar', 'baz'])
  </code></pre>
  
  <pre><code>                    foo  bar  baz
  first second third               
  a     c      e        5    0    3
               f        3    7    9
        d      e        3    5    2
               f        4    7    6
  b     c      e        8    8    1
               f        6    7    7
        d      e        8    1    5
               f        9    8    9
  </code></pre>
  
  <p><code>df.loc[['a', 'b'], :, 'e']</code> works and returns</p>
  
  <pre><code>                    foo  bar  baz
  first second third               
  a     c      e        5    0    3
        d      e        3    5    2
  b     c      e        8    8    1
        d      e        8    1    5
  </code></pre>
  
  <p>But <code>df.loc[:, : 'e']</code> gives an error.</p>
  
  <p>So how do I get all values of the outermost index level with the <code>:</code> syntax?</p>