netmute

Game of Life

An implementation of Conway's Game of Life in 140 characters of Ruby.

Author

Created by Simon Ernst (@sier).

hadley

I think the two most important messages that people can get from a short course are:

a) the material is important and worthwhile to learn (even if it's challenging), and b) it's possible to learn it!

For those reasons, I usually start by diving as quickly as possible into visualisation. I think it's a bad idea to start by explicitly teaching programming concepts (like data structures), because the pay off isn't obvious. If you start with visualisation, the pay off is really obvious and people are more motivated to push past any initial teething problems. In stat405, I used to start with some very basic templates that got people up and running with scatterplots and histograms - they wouldn't necessary understand the code, but they'd know which bits could be varied for different effects.

Apart from visualisation, I think the two most important topics to cover are tidy data (i.e. http://www.jstatsoft.org/v59/i10/ + tidyr) and data manipulation (dplyr). These are both important for when people go off and apply

stevebowman

console.log('Loading event');

// Twilio Credentials 
var accountSid = '';
var authToken = '';
var fromNumber = '';

var https = require('https');
var queryString = require('querystring');

dannguyen

Iowa Liquor Sales dataset via Socrata/data.iowa.gov

(preliminary exploration)

The state of Iowa has released an 800MB+ dataset of more than 3 million rows showing weekly liquor sales, broken down by liquor category, vendor, and product name, e.g. STRAIGHT BOURBON WHISKIES, Jim Beam Brands, Maker's Mark

This dataset contains the spirits purchase information of Iowa Class “E” liquor licensees by product and date of purchase from January 1, 2014 to current. The dataset can be used to analyze total spirits sales in Iowa of individual products at the store level.

You can view the dataset via Socrata

mikermcneil

Toggle MacOS X Notification Center on or off

This gist is to remind me (and anyone else who it helps) how to quickly disable and re-enable Notification Center.

Set Up Bash Aliases

Installation

1. Open your terminal (<⌘ + ␣ (spacebar)>, then type "terminal", then press <↩ (enter)>).

kovetskiy

#!/bin/bash
###
### my-script — does one thing well
###
### Usage:
###   my-script <input> <output>
###
### Options:
###   <input>   Input file to read.
###   <output>  Output file to write. Use '-' for stdout.

pncnmnp

Current events of September 3, 1995 (1995-09-03) (Sunday) :
eBay is founded.
Current events of September 6, 1995 (1995-09-06) (Wednesday) :
NATO air strikes against Bosnian Serb forces continue, after repeated attempts at a solution to the Bosnian War fail.
Current events of September 19, 1995 (1995-09-19) (Tuesday) :
The Washington Post and The New York Times publish the Unabomber's manifesto.
Current events of September 22, 1995 (1995-09-22) (Friday) :
American millionaire Steve Forbes announces his candidacy for the 1996 Republican presidential nomination.
Current events of September 23, 1995 (1995-09-23) (Saturday) :
Argentine national Guillermo "Bill" Gaede is arrested in Phoenix, Arizona, on charges of industrial espionage. His sales to Cuba, China, North Korea and Iran are believed to have involved Intel and AMD trade secrets worth US$10–20 million.

chrismdp

# You don't need Fog in Ruby or some other library to upload to S3 -- shell works perfectly fine
# This is how I upload my new Sol Trader builds (http://soltrader.net)
# Based on a modified script from here: http://tmont.com/blargh/2014/1/uploading-to-s3-in-bash

S3KEY="my aws key"
S3SECRET="my aws secret" # pass these in

function putS3
{
  path=$1

IanColdwater

Mute these words in your settings here: https://twitter.com/settings/muted_keywords

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conormm

R to python data wrangling snippets

The dplyr package in R makes data wrangling significantly easier. The beauty of dplyr is that, by design, the options available are limited. Specifically, a set of key verbs form the core of the package. Using these verbs you can solve a wide range of data problems effectively in a shorter timeframe. Whilse transitioning to Python I have greatly missed the ease with which I can think through and solve problems using dplyr in R. The purpose of this document is to demonstrate how to execute the key dplyr verbs when manipulating data using Python (with the pandas package).

dplyr is organised around six key verbs: