@@ -0,0 +1,702 @@
+import numpy as np%0Aimport pandas as pd%0Afrom scipy.stats import kendalltau%0A%0A%0Adef borda_ordering(rankings):%0A    n, k = rankings.shape%0A    borda_scores = np.zeros(n)%0A    for ranking in rankings:%0A        for idx, paper in enumerate(ranking):%0A            borda_scores%5Bpaper - 1%5D += idx + 1%0A%0A    borda_scores = pd.Series(borda_scores)%0A    borda_ranking = np.array(borda_scores.sort_values().index, dtype='int') + 1%0A    return borda_ranking%0A%0A%0Aif __name__ == '__main__':%0A    truth_ranking = list(range(1, 1000 + 1))%0A    rankings = np.genfromtxt('data_n_1000_k_6.csv', delimiter=',', dtype='int')%0A%0A    global_ranking = borda_ordering(rankings)%0A    res = kendalltau(global_ranking, truth_ranking)%0A    print(res)%0A

Add Borda ordering.