Script to convert Dow Jones index CSV from Yahoo into prices over Q4 during presdential election years

dji_pres_election_q4.py

#!/usr/bin/env python

import csv
from collections import namedtuple

PriceRecord = namedtuple("PriceRecord", "date open high low close volume adjusted_close")

def parse_date(ymd):
    return map(int, ymd.split('-'))

def fiscal_quarter(r):
    year, month, _ = r.date
    q = ((month-1) / 3) + 1
    return (q, year)

def from_quarter(rs, q, y):
    for r in rs:
        quarter, year = fiscal_quarter(r)
        if quarter == q and year == y:
            yield r

def by_pres_election_quarters(rs):
    q = 4
    years = range(1988, 2017, 4)
    doy = {}
    for y in years:
        for r in from_quarter(rs, q, y):
            _, m, d = r.date
            k = (m, d)
            if not doy.has_key(k):
                doy[k] = {}
            doy[k][y] = r
            
    print "Day of year,%s" % (','.join(map(str, years)))
    for d,ys in doy.iteritems():
        row = []
        for y in years:
            r = ys.get(y)
            if r == None:
                row.append('')
            else:
                row.append(r.high)
        month, day = d
        print "%s-%s,%s" % (month, day, ','.join(row))
    

# assumes CSV has no header and rows are in ascending chronological order
with open('dji_prices.csv', 'rb') as f:
    dji = csv.reader(f)
    records = []
    for row in dji:
        row[0] = parse_date(row[0])
        records.append(PriceRecord._make(row))
    by_pres_election_quarters(records)