Vinesh Kannan vingkan

Create Website for Analytics

I completed some fantasy football data analytics research in this repository.

Help me create a static HTML page to show off my results.

The HTML files should be under the /docs directory, which I will host using GitHub Pages.
The pages must be static HTML pages. We can load data by fetching files like images or JSON from /docs/assets.
There will be a /docs/index.html that acts as a portfolio of all articles and then individual sub-folders for each article.
Right now there is only one article, which will be at /docs/workloadnews/index.html.

A clinic receives a stream of appointment updates. Time is discrete: T = 0, 1, 2, ....

Each update happens at a time index t. Each appointment has a scheduled start time start.

type Status = "BOOKED" | "CANCELLED" | "CHECKED_IN";

type AppointmentId = string;

The event stream is an array of strings. Each string is one token:

The first time you use this script, you will have to give it permissions:

chmod 0777 split_database.sh
chmod 0777 combine_database.sh

Then you can run the scripts like this:

Run the Jupyter notebook in your browser with Binder:

Each trip has the following fields. See the descriptions below.

	<html>
	<head>
	<meta charset="UTF-8">
	<title>App</title>
	<script src="https://unpkg.com/react@17.0.2/umd/react.production.min.js"></script>
	<script src="https://unpkg.com/react-dom@17.0.2/umd/react-dom.production.min.js"></script>
	<script src="https://cdn.jsdelivr.net/npm/vue@2/dist/vue.js"></script>
	<script src="https://unpkg.com/@babel/standalone@7.13.12/babel.min.js"></script>
	<style>

	import discord
	import os
	import requests

	from discord.ext import commands


	DISCORD_BOT_TOKEN = os.environ["DISCORD_BOT_TOKEN"]
	RANDOM_CAT_URL = "https://cataas.com"

	-- The only properties with 10 or more full bathrooms are apartments.

	SELECT class
	WHERE fbath >= 10

	-- On average, properties designed from an architect's plan sold for twice as much as properties designed from a stock plan.

	SELECT tp_plan, AVG(sale_price)
	WHERE tp_plan IN (1, 2)
	GROUP BY tp_plan

	-- Most rides start and end in the Near North Side community area.

	SELECT
	pickup_community_area,
	COUNT(*) as trips
	GROUP BY pickup_community_area
	ORDER BY trips DESC

	-- On average, riders picked up in the Lincoln Square community area tip better than riders picked up in the Loop.