hughdbrown

import ConfigParser
import os.path


def get_creds():
    botofile = os.path.expanduser("~/.boto")
    with open(botofile) as f:
        c = ConfigParser.ConfigParser()
        c.readfp(f)
        return tuple(

hughdbrown

#!/usr/bin/env python

import os
import sys
import time
import subprocess
import urllib2

import boto

hughdbrown

Keybase proof

I hereby claim:

• I am hughdbrown on github.
• I am hughdbrown (https://keybase.io/hughdbrown) on keybase.
• I have a public key whose fingerprint is 9CD4 F942 05BA F9CC 4ABD CB31 A9D2 7566 110A B89D

To claim this, I am signing this object:

hughdbrown

Dates

date_range

date_series = pd.date_range("start_date", "end_date")

CSV files

df = pd.read_csv("filename.csv", parse_dates=["column1"], index_col=["column2"])

hughdbrown

Day	Time	Total
Friday		2.00 hours
Saturday	10:00 - 18:00	8.00 hours
Saturday	19:30 - 21:30	2.00 hours
Sunday		4.00 hours
Monday	10:00 - 17:30	7.50 hours
Tuesday	09:00 - 17:00	8.00 hours

31.5 hours total

hughdbrown

Selection

where

>>> import numpy as np
>>> a = np.array([[7, 4, 3, 7],
...  [7, 2, 5, 4],
...  [1, 7, 5, 1]])
>>> for (i, j) in zip(*np.where(a % 2 == 0)):
...     print("[{0}, {1}]: {2}".format(i, j, a[i, j]))
... 

hughdbrown

Denver drivers

Description

Since arriving in Denver, I have noticed that Denver drivers do a whole range of semi-dangerous things on the road:

• Changing lane with insufficient space
• Lefthand turns in front of oncoming traffic
• Running orange/red lights
• Driving through totally red lights
• Passing on the right on the highway

hughdbrown

Real estate factors

Description

Real estate prices within an area can be predicted from past sales in an area with the addition of various factors:

• number of bedrooms
• number of bathrooms
• square footage of house
• square footage of lot

In addition, we might speculate that a couple of other factors that are not commonly recorded at at play:

hughdbrown

Movie factors

Description

Movies are released and have varying levels of financial success. Can we figure out how successful a film will be by assessing its factors before its release?

Data sources

• IMDB for movie particulars (genre, actors, director, etc.)
• movie revenue source?

hughdbrown

How to put your project online

This is a short description of the infrastructure you need to set up to get your project reachable on the web.

Github hosting

AWS hosting

Heroku hosting