Python rank benchmarking

python_rank_benchmarking.py

"""
Benchmarking the methods at
http://stackoverflow.com/questions/5284646/rank-items-in-an-array-using-python-numpy
"""

import timeit
from scipy.stats import rankdata
import pandas as pd
import numpy as np


def rank_arange(array):
    temp = array.argsort()
    ranks = np.empty(len(array), int)
    ranks[temp] = np.arange(len(array))
    return(ranks)


def rank_argsort(array):
    ranks = array.argsort().argsort()
    return(ranks)

ns = [5, 10, 50, 100, 500, 1000, 5000, 10000]
funcs = ['rank_arange', 'rank_argsort', 'rankdata']

results = pd.DataFrame(np.full((len(ns), 1 + len(funcs)), np.nan))
results.columns = ['n'] + funcs
results['n'] = ns

for n in ns:
    array = np.random.rand(n)
    for f in funcs:
        r = timeit.timeit('%s(array)' % f,
                          setup="from __main__ import array,%s" % f,
                          number=1000)
        results.ix[results.n == n, f] = r

results

"""Results:
       n  rank_arange  rank_argsort  rankdata
0      5     0.008286      0.002283  0.020194
1     10     0.004828      0.001600  0.019356
2     50     0.007560      0.002222  0.019348
3    100     0.004734      0.003443  0.016481
4    500     0.012260      0.022422  0.033053
5   1000     0.035825      0.097287  0.062478
6   5000     0.443329      0.754238  0.492829
7  10000     0.951714      1.658155  1.028654
"""