I\'ve got a dictionary with data of the same length (but different types), something like:
data = {
\"id\": [1,1,2,2,1,2,1,2],
\"info\": [\"info1\",
For working with records, I personally like numpy.recarray.
In [3]: import numpy as np
In [4]: fields = data.keys()
In [8]: recs = zip(*[ lst for k, lst in data.iteritems() ])
In [9]: recs[0]
Out[9]: ('info1', 1, 1)
In [10]: recs[1]
Out[10]: ('info2', 1, 2)
In [21]: ra = np.rec.fromrecords(recs, names = fields )
In [17]: ra
rec.array([('info1', 1, 1), ('info2', 1, 2), ('info3', 2, 3), ('info4', 2, 4),
('info5', 1, 5), ('info6', 2, 6), ('info7', 1, 7), ('info8', 2, 8)],
dtype=[('info', 'S5'), ('id', '
If you want to group the records by id in a dict, do:
{ id: ra[ra.id == id] for id in set(ra.id) }