Creating percentile buckets in pandas

Question

I am trying to classify my data in percentile buckets based on their values. My data looks like,

a = pnd.DataFrame(index = ['a','b','c','d','e','f','g','h','i','j'], columns=['data'])
a.data = np.random.randn(10)
print a
print '\nthese are ranked as shown'
print a.rank()

       data
a -0.310188
b -0.191582
c  0.860467
d -0.458017
e  0.858653
f -1.640166
g -1.969908
h  0.649781
i  0.218000
j  1.887577

these are ranked as shown
   data
a     4
b     5
c     9
d     3
e     8
f     2
g     1
h     7
i     6
j    10

To rank this data, I am using the rank function. However, I am interested in the creating a bucket of the top 20%. In the example shown above, this would be a list containing labels ['c', 'j']

desired result : ['c','j']

How do I get the desired result

Answer 1

In [13]: df[df > df.quantile(0.8)].dropna()
Out[13]: 
       data
c  0.860467
j  1.887577

In [14]: list(df[df > df.quantile(0.8)].dropna().index)
Out[14]: ['c', 'j']