- Create a front-end project & name index.html
- cd into the project in terminal
- Run
git init
to initialize the git repo in the project - Create & switch to branch called gh-pages -
git checkout -b gh-pages
- Go to github.com the website and create a new repo
- Do not add a readme..
- Use the cheatsheat to add the remote -
git add remote....
- Run
git add .
to add & stage all your files
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<!DOCTYPE html> | |
<html> </html> | |
Making Comments: | |
<--! Make me into a comment --> | |
Font Size: | |
<p style = "font-size: 12px"> | |
Font Color: | |
<h2 style="color:red"> | |
Font Color & Size: | |
<h2 style="color: green; font-size:12px"> |
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with | |
dau as ( | |
-- This part of the query can be pretty much anything. | |
-- The only requirement is that it have three columns: | |
-- dt, user_id, inc_amt | |
-- Where dt is a date and user_id is some unique identifier for a user. | |
-- Each dt-user_id pair should be unique in this table. | |
-- inc_amt represents the amount of value that this user created on dt. | |
-- The most common case is | |
-- inc_amt = incremental revenue from the user on dt |
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SELECT license, count(*) FROM [bigquery-public-data:github_repos.licenses] GROUP BY 1 ORDER BY 2 DESC LIMIT 10 |
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-- Active issues | |
-- Count of total active issues in the specified time frame | |
-- Source: githubarchive public data set via Google BigQuery http://githubarchive.org/ | |
SELECT | |
COUNT(DISTINCT JSON_EXTRACT_SCALAR(events.payload, '$.issue.id')) AS events_issue_count | |
FROM (SELECT * FROM TABLE_DATE_RANGE([githubarchive:day.],TIMESTAMP('2015-09-01'),TIMESTAMP('2016-08-31'))) | |
AS events | |
-- 10,723,492 active issues |
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height: 800 |
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license: mit | |
height: 620 | |
border: no |
Snowman image via: https://thenounproject.com/marvdrock/
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<!DOCTYPE html> | |
<meta charset="utf-8"> | |
<style> | |
</style> | |
<div id='marquee'> | |
</div> | |
<script src="https://d3js.org/d3.v4.min.js"></script> | |
<script> |
A simple example demonstrating how Coördinator could be used to intersperse relevant, non-data-driven elements into a data story. The runner and Olympic logo are comprised of the circles representing relevant athletes.
Olympic data from: https://www.teamusa.org/road-to-rio-2016/team-usa/athletes
Runner icon by Christian Brunner: https://thenounproject.com/chbrunne/
Olympic logo: https://commons.wikimedia.org/wiki/File:United_States_Olympic_Committee_logo_2.svg