Andrew Powers powersa

Find a tutorial that works for you: AWS Jupyter Notebook

I got burned on this one, watch the fine print and stick with it if it doesn't work right away

Key Pair

Create
chmod 0400

Launch in a way that works for you: Command Line or Console

Configure Your Cluster

Goal

Identify Seattle bus stops that are within 1 hour of the Food Bank on public transportation.

From where in the city is the Food Bank accessible within 1 hour?
Where in the city is accessible from the Food Bank within 1 hour?

Data

GTFS: https://developers.google.com/transit/gtfs/

Grab data from data portal: http://www5.kingcounty.gov/gisdataportal/

Explore in QGIS

Export busstop.shp as geojson: busstop-layer.geojson

Generate routes.txt:

jq -r '.features | .[] | .properties | .ROUTES | split(",") | .[]' busstop-layer.geojson | sort -u >routes.txt

Mapping for Health: Opportunities and Obstacles in Open Source

Anna Clements & Isabel Shaw, Broad Street Maps

In the developing world, physical access to health care can be the number one factor in the utilization of services, and consequently, the health of a population. At Broad Street Maps, we believe that where you live shouldn't determine if you live.

Anna and Isabel will give a brief overview of Broad Street Maps’ current work, introduce some exciting opportunities emerging in the open source world for global health, and reflect on what it is like for non-developers engaging with open-source technology and communities.

	64 65 35235 28th Ave NE and NE 125th St
	41 795 35233 NE 125th St and 25th Ave NE
	41 64 35230 NE 125th St and Lake City Way NE
	41 65 35230 NE 125th St and Lake City Way NE
	41 795 35230 NE 125th St and Lake City Way NE
	64 65 35230 NE 125th St and Lake City Way NE
	64 795 35230 NE 125th St and Lake City Way NE
	65 795 35230 NE 125th St and Lake City Way NE
	41 795 35231 NE 125th St and 28th Ave NE
	41 994 35231 NE 125th St and 28th Ave NE


	<!doctype html>
	<html lang="en">

	<head>
	</head>

	<body>
	<svg width="720" height="120">
	<circle cx="40" cy="60" r="10"></circle>

	import csv
	# out_file is a file path and out is an array of arrays of the data you want to write
	def write_data_to_csv(out_file, out):
	with open(out_file, "w") as f:
	wr = csv.writer(f, delimiter='\t')
	for row in out:
	wr.writerow(row)