def itemfreq(a):
items, inv = np.unique(a, return_inverse=True)<EOL>freq = np.bincount(inv)<EOL>return np.array([items, freq]).T<EOL>
Returns a 2-D array of item frequencies.

Parameters
----------
a : (N,) array_like
    Input array.

Returns
-------
itemfreq : (K, 2) ndarray
    A 2-D frequency table.  Column 1 contains sorted, unique values from
    `a`, column 2 contains their respective counts.

Examples
--------
>>> a = np.array([1, 1, 5, 0, 1, 2, 2, 0, 1, 4])
>>> stats.itemfreq(a)
array([[ 0.,  2.],
       [ 1.,  4.],
       [ 2.,  2.],
       [ 4.,  1.],
       [ 5.,  1.]])
>>> np.bincount(a)
array([2, 4, 2, 0, 1, 1])

>>> stats.itemfreq(a/10.)
array([[ 0. ,  2. ],
       [ 0.1,  4. ],
       [ 0.2,  2. ],
       [ 0.4,  1. ],
       [ 0.5,  1. ]])