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t = np.array([['one','two','three'],['four','five','six']], dtype=object)
np.min(t)
# gives 'five'
np.max(t)
# gives 'two'

# Vectorize takes a Python function and converts it into a Numpy
# vector function that operates on arrays
np_len = np.vectorize(lambda x: len(x))

np_len(t)
# gives array([[3, 3, 5], [4, 4, 3]])

idx = np_len(t).argmin(0) # get the index along the 0th axis
# gives array([0, 0, 1])

result = t
for i in idx[1:]:
    result = result[i]
print result
# gives "two", the string with the smallest length