title: Axis argument to .loc() to interpret the passed slicers on a axis=1
body: <p>The <a href="http://pandas.pydata.org/pandas-docs/stable/advanced.html#using-slicers" rel="noreferrer">documentation</a> suggests:</p>
  
  <blockquote>
    <p>You can also specify the axis argument to .loc to interpret the passed
    slicers on a single axis.</p>
  </blockquote>
  
  <p>However I get an error trying to slice along the column index.</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  
  cols= [(yr,m) for yr in [2014,2015] for m in [7,8,9,10]]
  df = pd.DataFrame(np.random.randint(1,100,(10,8)),index=tuple('ABCDEFGHIJ'))
  df.columns =pd.MultiIndex.from_tuples(cols)
  
  print df.head()
  
    2014             2015            
      7   8   9   10   7   8   9   10
  A   68  51   6  48   24   3   4  85
  B   79  75  68  62   19  40  63  45
  C   60  15  32  32   37  95  56  38
  D    4  54  81  50   13  64  65  13
  E   78  21  84   1   83  18  39  57
  
  
  #This does not work as expected
  print df.loc(axis=1)[(2014,9):(2015,8)]
  </code></pre>
  
  <pre class="lang-none prettyprint-override"><code>AssertionError: Start slice bound is non-scalar
  </code></pre>
  
  <pre class="lang-python prettyprint-override"><code>#but an arbitrary transpose and changing axis works!
  df = df.T
  print df.loc(axis=0)[(2014,9):(2015,8)]
  
            A   B   C   D   E   F   G   H   I   J
  2014 9    6  68  32  81  84  60  83  39  94  93
       10  48  62  32  50   1  84  18  14  92  33
  2015 7   24  19  37  13  83  69  31  91  69  90
       8    3  40  95  64  18   8  32  93  16  25
  </code></pre>
  
  <p>So I could always assign the slice and re-transpose. 
  That though feels like a hack and the axis=1 setting should have worked.</p>
  
  <pre><code>df = df.loc(axis=0)[(2014,9):(2015,8)]
  
  df = df.T
  
  
  print df
  
    2014     2015    
      9   10   7   8 
  A   64  98   99  87
  B   43  36   22  84
  C   32  78   86  66
  D   67   8   34  73
  E   83  54   96  33
  F   18  83   36  71
  G   13  25   76   8
  H   69   4   99  84
  I    3  52   50  62
  J   67  60    9  49
  </code></pre>