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"

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

# 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

Music to code by

All thanks to a tweet by Chris Albon

Bands

• Cut Copy (via Andrew Musselman)
• Com Truise (via Sean J. Taylor)
• Makkam (via Karissa McKelvey)
• Slow Magic (via Clare Corthell)

gjreda

"""
add grouped cumulative sum column to pandas dataframe

Add a new column to a pandas dataframe which holds the cumulative sum for a given grouped window

Desired output:
user_id,day,session_minutes,cumulative_minutes
516530,0,NaN,0
516530,1,0,0
516532,0,5,5

gjreda

# for creating a column like "days since last login"

df = pd.read_clipboard(index_col=['customer_id', 'days'])
(df
 .groupby(level='customer_id')
 .did_login
 .cumsum()
 .to_frame()
 .groupby(level='customer_id')
 .apply(lambda g: g.groupby('did_login').cumcount())

gjreda

from concurrent.futures import ProcessPoolExecutor
import concurrent.futures

from halas.parsers import boxscore

GAMES = [ ... ]

results = []
with ProcessPoolExecutor(max_workers=4) as executor:
    future_results = {executor.submit(boxscore, game):

gjreda

# Installing/upgrading old requirements.txt from python2 to python3
sed s/\=/\ /g requirements.txt | awk '{print $1}' | xargs -n1 pip3 install --upgrade

gjreda

[
  {
    "id": "805168201126518784",
    "text": "@ryanisaac this is the weirdest quarter of football I’ve seen in a while"
  },
  {
    "id": "804818096942968833",
    "text": "@SportsTribution I don't follow."
  },
  {

gjreda