title: Rank Pandas dataframe by quantile
body: <p>I have a Pandas dataframe in which each column represents a separate property, and each row holds the properties' value on a specific date:</p>
  
  <pre><code>import pandas as pd
  
  dfstr = \
  '''         AC        BO         C       CCM        CL       CRD        CT        DA        GC        GF
  2010-01-19  0.844135 -0.194530 -0.231046  0.245615 -0.581238 -0.593562  0.057288  0.655903  0.823997  0.221920
  2010-01-20 -0.204845 -0.225876  0.835611 -0.594950 -0.607364  0.042603  0.639168  0.816524  0.210653  0.237833
  2010-01-21  0.824852 -0.216449 -0.220136  0.234343 -0.611756 -0.624060  0.028295  0.622516  0.811741  0.201083'''
  df = pd.read_csv(pd.compat.StringIO(dfstr), sep='\s+')
  </code></pre>
  
  <p>Using the <code>rank</code> method, I can find the percentile rank of each property with respect to a specific date:</p>
  
  <pre><code>df.rank(axis=1, pct=True)
  </code></pre>
  
  <p>Output:</p>
  
  <pre><code>             AC   BO    C  CCM   CL  CRD   CT   DA   GC   GF
  2010-01-19  1.0  0.4  0.3  0.7  0.2  0.1  0.5  0.8  0.9  0.6
  2010-01-20  0.4  0.3  1.0  0.2  0.1  0.5  0.8  0.9  0.6  0.7
  2010-01-21  1.0  0.4  0.3  0.7  0.2  0.1  0.5  0.8  0.9  0.6
  </code></pre>
  
  <p>What I'd like to get instead is the quantile (eg quartile, quintile, decile, etc) rank of each property. For example, for quintile rank my desired output would be:</p>
  
  <pre><code>             AC   BO    C  CCM   CL  CRD   CT   DA   GC   GF
  2010-01-19   5    2     2  4     1   1     3    4    5    3
  2010-01-20   2    2     5  1     1   3     4    5    3    4
  2010-01-21   5    2     2  4     1   1     3    4    5    3
  </code></pre>
  
  <p>I might be missing something, but there doesn't seem to a built-in way to do this kind of quantile ranking with Pandas. What's the simplest way to get my desired output?</p>