Xander Johnson metasyn

## splunk_app_info_scraper.py
# Splunk App Information Scraper
# Note, it also scapes TAs

# Alexander Johnson
# xander@splunk.com
# @metasyn

# requires lxml

import re

## gist:8baa2500d8e2bb6d96b9
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [

## gist:51bc4f49af0d32df3c6a
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# [Linguistic Diversity Index](http://en.wikipedia.org/wiki/Linguistic_diversity_index)\n",
    "\n",
    ">Greenberg's Diversity Index (LDI) is the probability that two people selected from the population at random will have different mother tongues; it therefore ranges from 0 (everyone has the same mother tongue) to 1 (no two people have the same mother tongue).\n",
    "\n",

## gist:5b1224c273bb9ceef3e3
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# [Linguistic Diversity Index](http://en.wikipedia.org/wiki/Linguistic_diversity_index)\n",
    "\n",
    ">Greenberg's Diversity Index (LDI) is the probability that two people selected from the population at random will have different mother tongues; it therefore ranges from 0 (everyone has the same mother tongue) to 1 (no two people have the same mother tongue).\n",
    "\n",

## splgeneral
# SPL General Practices

1.) Filter by time first.

>“. . . time is the most efficient filter”

2.) Use host, source, sourcetype

>“After time, the most powerful keywords are host, source, sourcetype”

## visualization.js
define(function(require, exports, module) {
 // STEP 1.) Initalization of your setup

  // Add your dependenciences here,
  // Note, no .js extension when using require
  // e.g.
  var d3 = require("../d3/d3");
  var d3 = require("../d3plus/d3plus");
  var underscore = require("../underscore");

## gist:b38e8c3143961e48af9f
define(function(require, exports, module) {
    // We have a few dependencies; namely, d3, and d3plus
    // In order for d3plus to get loaded, we need to load it into
    // the name var, d3
    var d3 = require("../d3/d3");
    var d3 = require("../d3plus/d3plus");
    var _ = require("underscore");
    var SimpleSplunkView = require("splunkjs/mvc/simplesplunkview");

    var TreeMap= SimpleSplunkView.extend({

## gist:a9e4552da84f25659d12
// prism languages for splunk searches.

	Prism.languages.mcurve = {
		'comment': {
			pattern: /(^|[^\\])#.*?(\r?\n|$)/g,
			lookbehind: true
		},
		'saf' : /\|?\s*(search|where)[^\|]*/,
		'munge' : /\|\s*(eval|eventstats|streamstats)[^\|]*/,
		'report' : /\|\s*(stats|timechart|chart)[^\|]*/,

## city_population.csv

          
            City / Urban area
            Country
            Population
            Land area
            Density

            
              Tokyo/Yokohama
              Japan
              33,200,000
              6,993
              4,750

            
              New York Metro
              USA
              17,800,000
              8,683
              2,050

            
              Sao Paulo
              Brazil
              17,700,000
              1,968
              9,000

            
              Seoul/Incheon
              South Korea
              17,500,000
              1,049
              16,700

            
              Mexico City
              Mexico
              17,400,000
              2,072
              8,400

            
              Osaka/Kobe/Kyoto
              Japan
              16,425,000
              2,564
              6,400

            
              Manila
              Philippines
              14,750,000
              1,399
              10,550

            
              Mumbai
              India
              14,350,000
              484
              29,650

            
              Delhi
              India
              14,300,000
              1,295
              11,050

## index.html
<!doctype html>
<meta charset="utf-8">

<!--

fatal police shootings
This data came from the Washington Post's repo
https://github.com/washingtonpost/data-police-shootings
It is a database of every fatal shooting in the United States
by a police officer in the line of duty in 2015.
	# Splunk App Information Scraper
	# Note, it also scapes TAs

	# Alexander Johnson
	# xander@splunk.com
	# @metasyn

	# requires lxml

	import re
	{
	"cells": [
	{
	"cell_type": "code",
	"execution_count": 2,
	"metadata": {
	"collapsed": false
	},
	"outputs": [],
	"source": [
	{
	"cells": [
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"# [Linguistic Diversity Index](http://en.wikipedia.org/wiki/Linguistic_diversity_index)\n",
	"\n",
	">Greenberg's Diversity Index (LDI) is the probability that two people selected from the population at random will have different mother tongues; it therefore ranges from 0 (everyone has the same mother tongue) to 1 (no two people have the same mother tongue).\n",
	"\n",
	# SPL General Practices

	1.) Filter by time first.

	>“. . . time is the most efficient filter”

	2.) Use host, source, sourcetype

	>“After time, the most powerful keywords are host, source, sourcetype”
	define(function(require, exports, module) {
	// STEP 1.) Initalization of your setup

	// Add your dependenciences here,
	// Note, no .js extension when using require
	// e.g.
	var d3 = require("../d3/d3");
	var d3 = require("../d3plus/d3plus");
	var underscore = require("../underscore");
	define(function(require, exports, module) {
	// We have a few dependencies; namely, d3, and d3plus
	// In order for d3plus to get loaded, we need to load it into
	// the name var, d3
	var d3 = require("../d3/d3");
	var d3 = require("../d3plus/d3plus");
	var _ = require("underscore");
	var SimpleSplunkView = require("splunkjs/mvc/simplesplunkview");

	var TreeMap= SimpleSplunkView.extend({
	// prism languages for splunk searches.

	Prism.languages.mcurve = {
	'comment': {
	pattern: /(^\|[^\\])#.*?(\r?\n\|$)/g,
	lookbehind: true
	},
	'saf' : /\\|?\s(search\|where)[^\\|]/,
	'munge' : /\\|\s(eval\|eventstats\|streamstats)[^\\|]/,
	'report' : /\\|\s(stats\|timechart\|chart)[^\\|]/,
City / Urban area	Country	Population	Land area	Density
Tokyo/Yokohama	Japan	33,200,000	6,993	4,750
New York Metro	USA	17,800,000	8,683	2,050
Sao Paulo	Brazil	17,700,000	1,968	9,000
Seoul/Incheon	South Korea	17,500,000	1,049	16,700
Mexico City	Mexico	17,400,000	2,072	8,400
Osaka/Kobe/Kyoto	Japan	16,425,000	2,564	6,400
Manila	Philippines	14,750,000	1,399	10,550
Mumbai	India	14,350,000	484	29,650
Delhi	India	14,300,000	1,295	11,050
	<!doctype html>
	<meta charset="utf-8">

	<!--

	fatal police shootings
	This data came from the Washington Post's repo
	https://github.com/washingtonpost/data-police-shootings
	It is a database of every fatal shooting in the United States
	by a police officer in the line of duty in 2015.