Mark Silverberg marks

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This is a d3.js visualization of US zip codes.

Original zip code dataset from Geocommons.

5MB shapefile with properties such as zipcode, state, name, population, area, more.

INPUT: ["open.whitehouse.gov","rcp4-3y7g","select * order by salary desc limit 100"]

OUTPUT:

{
    "duration": 1.131406922,
    "result": {

	# Requires official IBM SPSS extension to be installed [https://www.ibm.com/developerworks/community/wikis/home?lang=en#!/wiki/We70df3195ec8_4f95_9773_42e448fa9029/page/Downloads%20for%20IBM%C2%AE%20SPSS%C2%AE%20Statistics]


	* Encoding: UTF-8.

	BEGIN PROGRAM Python.

	# Import python dependencies
	import urllib2
	import csv

	{
	"version": "2",
	"header": {
	"title": "Crime Incidents in Chicago",
	"description": "This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2001 to present, minus the most recent seven days. Data is extracted from the Chicago Police Department's CLEAR (Citizen Law Enforcement Analysis and Reporting) system. In order to protect the privacy of crime victims, addresses are shown at the block level only and specific locations are not identified.",
	"navigation": [{
	"label": "Download",
	"url": "https://data.cityofchicago.org/api/views/ijzp-q8t2/rows.csv?accessType=DOWNLOAD&bom=true"
	}]
	},

	filename datain url
	'http://open.whitehouse.gov/resource/i9g8-9web.csv?$limit=50000';

	proc import datafile=datain out=whsalaries dbms=csv replace;
	getnames=yes;

	/* proc print data=whsalaries; */

	proc means;

	// Use Gists to store code you would like to remember later on
	console.log(window); // log the "window" object to the console