kaggle_rankavg.py

from __future__ import division
from collections import defaultdict
from glob import glob
import sys

glob_files = sys.argv[1]
loc_outfile = sys.argv[2]

def kaggle_bag(glob_files, loc_outfile):
  with open(loc_outfile,"w") as outfile:
    all_ranks = defaultdict(list)
    for i, glob_file in enumerate( glob(glob_files) ):
      file_ranks = []
      print("parsing: {}".format(glob_file))
      # sort glob_file by first column, ignoring the first line
      lines = open(glob_file).readlines()
      lines = [lines[0]] + sorted(lines[1:])
      for e, line in enumerate( lines ):
        if e == 0 and i == 0:
          outfile.write( line )
        elif e > 0:
          r = line.strip().split(",")
          file_ranks.append( (float(r[1]), e, r[0]) )
      for rank, item in enumerate( sorted(file_ranks) ):
        all_ranks[(item[1],item[2])].append(rank)
    average_ranks = []
    for k in sorted(all_ranks):
      average_ranks.append((sum(all_ranks[k])/len(all_ranks[k]),k))
    ranked_ranks = []
    for rank, k in enumerate(sorted(average_ranks)):
      ranked_ranks.append((k[1][0],k[1][1],rank/(len(average_ranks)-1)))
    for k in sorted(ranked_ranks):
      outfile.write("%s,%s\n"%(k[1],k[2]))
    print("wrote to {}".format(loc_outfile))

kaggle_bag(glob_files, loc_outfile)