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@meiqimichelle
meiqimichelle / USstates_avg_latLong
Created December 1, 2013 02:08
JSON of US states (full names) and their average lat/long
[
{
"state":"Alaska",
"latitude":61.3850,
"longitude":-152.2683
},
{
"state":"Alabama",
"latitude":32.7990,
"longitude":-86.8073
@meiqimichelle
meiqimichelle / USstates_avg_latLong_concat
Created December 1, 2013 02:13
JSON US states (full names) with average lat/long in one field
[
{
"state":"Alaska",
"latLong":"61.3850;-152.2683"
},
{
"state":"Alabama",
"latLong":"32.7990;-86.8073"
},
{
@meiqimichelle
meiqimichelle / sliderZoom.js
Last active June 27, 2017 20:04
elevateZoom combined with Webflow slider
<script type="text/javascript" src="http://code.jquery.com/jquery-latest.min.js"></script>
<script type="text/javascript" src="https://s3.amazonaws.com/Boorse/jquery.elevatezoom.js"></script>
<script>
if ($('#zoom_01.parentNode').css('visibility') !== 'hidden') {
$("#zoom_01").elevateZoom({
zoomWindowPosition: 11,
zoomWindowOffetx: -60,
zoomWindowFadeIn: 500,
zoomWindowFadeOut: 500
});
@meiqimichelle
meiqimichelle / indexer.py
Last active August 29, 2015 14:00
Index excel data to elasticsearch
# ############## Michelle: Excel to JSON to ES ##############
from xlrd import open_workbook
from pyelasticsearch import ElasticSearch
es = ElasticSearch('http://ec2-99-999-99-99.us-gov-west-1.compute.amazonaws.com:9200') # This is an example location. Change to local or other hosted location to use.
#create index first so you can set the mappings before you index data
es.create_index("unidatareport")
/* Styles for Natural Resource Revenue from U.S. Federal Lands */
/*srslyforreals*/
@import 'bourbon/bourbon';
@import 'custom';

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meiqimichelle / ipfs-in-4-hours.md
Last active February 22, 2018 18:48
A summary of the IPFS project in 4 hours

IPFS in 4 hours

I was given an opportunity to analyze the IPFS open source project, with the caveat that I should not spend no more than 4 hours, total, on this work. Of course, starting at only a basic understanding of the project to writing cogently on project patterns, strengths, and weaknesses in 4 hours is not a small request, and one that will be missing many pieces. But in the interest of sharing what I've learned and contributing back to the community, I am summarizing my thoughts here on GitHub. May this summary be helpful to someone else on their path to understanding.

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