Finding the mode of an array/iterable
Originally I thought you must have been doing something wrong, but no: the scipy.stats implementation of mode scales with the number of unique elements, and so will behave very badly for your test case.

As long as your objects are hashable (which includes your three listed object types of strings, floats, and ints), then probably the simplest approach is to use collections.Counter and the most_common method:

In [33]: import scipy.stats

In [34]: li = range(50000); li[1] = 0

In [35]: scipy.stats.mode(li)
Out[35]: (array([ 0.]), array([ 2.]))

In [36]: timeit scipy.stats.mode(li)
1 loops, best of 3: 10.7 s per loop


but

In [37]: from collections import Counter

In [38]: Counter(li).most_common(1)
Out[38]: [(0, 2)]

In [39]: timeit Counter(li).most_common(1)
10 loops, best of 3: 34.1 ms per loop