Movie Club Borda Count Voting

borda.py

import csv
import os
import sys
from collections import defaultdict

rows = []

filename = sys.argv[1] 

_, ext = os.path.splitext(filename)

if ext == '.csv':
  delimiter = ','
elif ext == '.tsv':
  delimiter = '\t'
else:
  raise NotImplementedError("Unknown file extension.")

with open(filename, 'r') as csvfile:
  votereader = csv.reader(csvfile, delimiter=delimiter, quotechar=None)
  for row in votereader:
        rows.append(row)

headers = rows.pop(0)
voter_names = headers[:1] # MOVIES NAME_1 NAME_2 etc

num_candidates = len(rows)
tabulations = defaultdict(int)

for movie in rows:
  title = movie[0]
  votes = movie[1:]
  for vote in votes:
    if vote == '':
      vote = num_candidates
    vote = int(vote)

    assert 0 <= vote <= num_candidates, "{} / {}".format(vote, num_candidates)
    
    tabulations[title] += num_candidates - vote

winning_value = max(tabulations.values())
winners = [ title for title, total in tabulations.items() if total == winning_value ]

if len(winners) > 1:
  print "TIE BETWEEN " + ", ".join(winners)
else:
  print "CONGRATULATIONS " + winners[0] + " WITH {} POINTS".format(winning_value)

sortable = [ (title, pts) for title, pts in tabulations.items() ]
sortable = sorted(sortable, key=lambda item: item[1])
sortable.reverse()

total_pts = sum(map(lambda x: x[1], sortable))

print "----"

def fixed_width_sprint(ct, title, pts):
  pts = str(pts)
  spaces = ct - len(title) - len(pts)
  return title + (' ' * spaces) + pts

for index, movie in enumerate(sortable):
  title, points =  movie

  percent = float(points) / float(total_pts) * 100
  movie_rank = str(index+1) + ": " + title
  text = fixed_width_sprint(80, movie_rank, points)
  print fixed_width_sprint(100, text, '%2.2f%%' % percent)

Movie Club Borda Count Voting

This script is to facilitate tabulating votes for movie club. The voting system is ranked Borda counts. Each movie gets a single numerical vote (1,2,3,..) or no vote and gets assigned points based on the ranking or zero points if no ranking is provided.

Preparing the Votes

1. In Google Sheets, go to the sheet with the current vote markings. Go to File > Download as... > Tab-separated values (tsv, current sheet)

2. Open the file in a local spreadsheet editor (e.g. Microsoft Excel, Libreoffice Sheets, etc., even another Google Sheets file) and delete any extraneous markings including directions such that the only data are the labels of movies and voters, and the votes themselves.

3. Save this sheet as another csv or tsv and run the script against it (see below).

Running the Script

Both tab separated values (tsv) and comma separated values (csv) files are supported.

python borda.py VOTING_FILE.csv

This will for example output:

CONGRATULATIONS Brick WITH 64 POINTS
----
1: Brick                                                                      64              19.75%
2: Death of Stalin                                                            50              15.43%
3: Millennium Actress                                                         40              12.35%
4: Grand Budapest Hotel                                                       38              11.73%
5: The Seventh Seal                                                           32               9.88%
6: Her                                                                        32               9.88%
7: F for Fake                                                                 32               9.88%
8: Ghost in the Shell (1995)                                                  12               3.70%
9: Matrix                                                                     10               3.09%
10: The 13th Warrior                                                           7               2.16%
11: Dredd                                                                      7               2.16%
12: 11:14                                                                      0               0.00%
13: Lucky # Slevin                                                             0               0.00%