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": {

	{
	"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;

	$ ckanapi dump datasets -r http://data.noaa.gov --all -O json.json
	Traceback (most recent call last):
	File "/usr/local/bin/ckanapi", line 9, in <module>
	load_entry_point('ckanapi==3.3', 'console_scripts', 'ckanapi')()
	File "/Library/Python/2.7/site-packages/ckanapi/cli/main.py", line 95, in main
	return dump_things(ckan, thing[0], arguments)
	File "/Library/Python/2.7/site-packages/ckanapi/cli/dump.py", line 33, in dump_things
	return dump_things_worker(ckan, thing, arguments)
	File "/Library/Python/2.7/site-packages/ckanapi/cli/dump.py", line 135, in dump_things_worker
	'include_datasets': False})

	var codes_to_category = {}
	codes_to_category['100'] = "Fire, Other"
	codes_to_category['110'] = "Structure fire, Other (conversion only)"
	codes_to_category['111'] = "Building fire"
	codes_to_category['112'] = "Fires in structure other than in a building"
	codes_to_category['113'] = "Cooking fire, confined to container"
	codes_to_category['114'] = "Chimney or flue fire, confined to chimney or flue"
	codes_to_category['115'] = "Incinerator overload or malfunction, fire confined"
	codes_to_category['116'] = "Fuel burner/boiler malfunction, fire confined"
	codes_to_category['117'] = "Commercial Compactor fire, confined to rubbish"

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

	(function(){
	var uStatePaths=[
	{id:"HI",n:"Hawaii",d:"M233.08751,519.30948L235.02744,515.75293L237.2907,515.42961L237.61402,516.23791L235.51242,519.30948L233.08751,519.30948ZM243.27217,515.59127L249.4153,518.17784L251.51689,517.85452L253.1335,513.97465L252.48686,510.57977L248.28366,510.09479L244.24213,511.87306L243.27217,515.59127ZM273.9878,525.61427L277.706,531.11074L280.13092,530.78742L281.26255,530.30244L282.7175,531.59573L286.43571,531.43407L287.40568,529.97912L284.49577,528.20085L282.55584,524.48263L280.45424,520.92609L274.63444,523.83599L273.9878,525.61427ZM294.19545,534.50564L295.48874,532.5657L300.17691,533.53566L300.82356,533.05068L306.96668,533.69732L306.64336,534.99062L304.05678,536.44556L299.69193,536.12224L294.19545,534.50564ZM299.53027,539.67879L301.47021,543.55866L304.54176,542.42703L304.86509,540.81041L303.24848,538.70882L299.53027,538.3855L299.53027,539.67879ZM306.4817,538.54716L308.74496,535.63726L313.43313,538.06218L317.79798,539.19381L322.16284,541.94205L322.16284,543.88198L318.6063,545.6