Kyle Walker walkerke

## index.html
<!DOCTYPE html>
<html>
  <head>
    <style>
      html, body, #map {
        height: 100%;
        padding: 0;
        margin: 0;
      }
    </style>

## autoloess.R
# autoloess.R: compute loess metaparameters automatically
# Kyle Gorman <gormanky@ohsu.edu>

aicc.loess <- function(fit) {
    # compute AIC_C for a LOESS fit, from:
    #
    # Hurvich, C.M., Simonoff, J.S., and Tsai, C. L. 1998. Smoothing
    # parameter selection in nonparametric regression using an improved
    # Akaike Information Criterion. Journal of the Royal Statistical
    # Society B 60: 271–293.

## oldfaithful
#combine elements with same name in two named lists (useful for combining layouts)
appendList <- function (x, val)
{
    stopifnot(is.list(x), is.list(val))
    xnames <- names(x)
    for (v in names(val)) {
        x[[v]] <- if (v %in% xnames && is.list(x[[v]]) && is.list(val[[v]]))
            appendList(x[[v]], val[[v]])
        else c(x[[v]], val[[v]])
    }

## code.R
#devtools::install("jeroenooms/V8")
library("V8")
library(pipeR)

ct = new_context("window")
# min.js gives me a call stack size error but non-min works fine
ct$source(
  "https://raw.githubusercontent.com/morganherlocker/turf/master/turf.js"
)
# one of the examples from turf API docs

## sql.sql

--  Convert your states (or other geometries id'd by state) to
--    display as with Alaska, Hawaii, and Puerto Rico transcaled
--
--  @param g: input geometry
--  @param state: column identifying the state (name, postal abbreviation, state FP)
--
--  output: geometries of states in albers projections of the states
--
-- Projections:

## nicar_15_mappingjs.md

      
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                / nicar_15_mappingjs.md
            
            
              Last active
              August 29, 2015 14:16
            
              
                NICAR 15 - Workshop
              
          
    Mapping JS: Building narrative with geo data + CartoDB

Aurelia Moser, Map Scientist, CartoDB
Workshop - NICAR Session Link
March 6, 2015, 3:20PM-4:20PM
Find this document here:

Stackedit:


## leaflet-county-explorer.r
# TODO: Add a Shiny dropdown to select demographic variable
library(leaflet)
library(noncensus)
library(dplyr)

data("counties", package="noncensus")
data("county_polygons", package="noncensus")
data("quick_facts", package="noncensus")

counties <- counties %>%

## Bokeh_test
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [

## README.md

      
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                hrbrmstr
                / README.md
            
            
              Created
              July 11, 2015 14:12
            
              
                Slight optimizations to http://rpubs.com/walkerke/txlege
              
          
    Main differences are:

All the initial data acquisition & munging is kept in one pipeline and the data structure is kept as a tbl_df
I ended up having to use html_session since the site was rejecting the access (login req'd) w/o it
The for loop is now an apply iteration and pbapply gives you a progress bar for free which is A Good Thing given how long that operation took :-)
The move to pbapply makes it possible to do the row-binding and left-joining in a single pipeline, which keeps everything in a tbl_df.
Your for solution can be made almost as efficient if you do a img_list <- vector("list", 150) so the list size is pre-allocated.

BTW: the popup code is brilliant and tigris is equally as brilliant!

  
## coord_proj.R
#' @export
coord_proj <- function(proj="+proj=robin +lon_0=0 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m +no_defs",
                       inverse = FALSE, degrees = TRUE,
                       ellps.default="sphere", xlim = NULL, ylim = NULL) {
  try_require("proj4")
  coord(
    proj = proj,
    inverse = inverse,
    ellps.default = ellps.default,
    degrees = degrees,
	<!DOCTYPE html>
	<html>
	<head>
	<style>
	html, body, #map {
	height: 100%;
	padding: 0;
	margin: 0;
	}
	</style>
	# autoloess.R: compute loess metaparameters automatically
	# Kyle Gorman <gormanky@ohsu.edu>

	aicc.loess <- function(fit) {
	# compute AIC_C for a LOESS fit, from:
	#
	# Hurvich, C.M., Simonoff, J.S., and Tsai, C. L. 1998. Smoothing
	# parameter selection in nonparametric regression using an improved
	# Akaike Information Criterion. Journal of the Royal Statistical
	# Society B 60: 271–293.
	#combine elements with same name in two named lists (useful for combining layouts)
	appendList <- function (x, val)
	{
	stopifnot(is.list(x), is.list(val))
	xnames <- names(x)
	for (v in names(val)) {
	x[[v]] <- if (v %in% xnames && is.list(x[[v]]) && is.list(val[[v]]))
	appendList(x[[v]], val[[v]])
	else c(x[[v]], val[[v]])
	}
	#devtools::install("jeroenooms/V8")
	library("V8")
	library(pipeR)

	ct = new_context("window")
	# min.js gives me a call stack size error but non-min works fine
	ct$source(
	"https://raw.githubusercontent.com/morganherlocker/turf/master/turf.js"
	)
	# one of the examples from turf API docs

	-- Convert your states (or other geometries id'd by state) to
	-- display as with Alaska, Hawaii, and Puerto Rico transcaled
	--
	-- @param g: input geometry
	-- @param state: column identifying the state (name, postal abbreviation, state FP)
	--
	-- output: geometries of states in albers projections of the states
	--
	-- Projections:
	# TODO: Add a Shiny dropdown to select demographic variable
	library(leaflet)
	library(noncensus)
	library(dplyr)

	data("counties", package="noncensus")
	data("county_polygons", package="noncensus")
	data("quick_facts", package="noncensus")

	counties <- counties %>%
	{
	"cells": [
	{
	"cell_type": "code",
	"execution_count": 1,
	"metadata": {
	"collapsed": true
	},
	"outputs": [],
	"source": [
	#' @export
	coord_proj <- function(proj="+proj=robin +lon_0=0 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m +no_defs",
	inverse = FALSE, degrees = TRUE,
	ellps.default="sphere", xlim = NULL, ylim = NULL) {
	try_require("proj4")
	coord(
	proj = proj,
	inverse = inverse,
	ellps.default = ellps.default,
	degrees = degrees,