gjreda

# When you're sure of the format, it's much quicker to explicitly convert your dates than use `parse_dates`
# Makes sense; was just surprised by the time difference.
import pandas as pd
from datetime import datetime
to_datetime = lambda d: datetime.strptime(d, '%m/%d/%Y %H:%M')

%time trips = pd.read_csv('data/divvy/Divvy_Trips_2013.csv', parse_dates=['starttime', 'stoptime'])
# CPU times: user 1min 29s, sys: 331 ms, total: 1min 29s
# Wall time: 1min 30s

gjreda

# OSX 10.7.5
# python 2.7.5
# pandas 0.13.0
# numpy 1.8.0

import pandas as pd
import numpy as np
from StringIO import StringIO

d = """row1,'2013-10-01'

gjreda

from bs4 import BeautifulSoup
from urllib2 import urlopen
from datetime import datetime, timedelta
from time import sleep
import sys
import csv

# CONSTANTS
ESPN_URL = "http://scores.espn.go.com"