Fan Li lifan0127

Comprehensive Introduction to @ngrx/store

Also check out my lesson @ngrx/store in 10 minutes on egghead.io!

Update: Non-middleware examples have been updated to ngrx/store v2. More coming soon!

Table of Contents

If you were to give recommendations to your "little brother/sister" on things that they need to do to become a data scientist, what would those things be?

I think the "Data Science Venn Diagram" (http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram) is a great place to start. You need three things to be a good data scientist:

Statistical knowledge
Programming/hacking skills
Domain expertise

Statistical knowledge

category	value	sector
UK production emissions	632	UK
Carbon flows from EU	88	EU
Carbon flows to EU	-61	EU
Carbon flows from other Annex 1	82	Annex 1
Carbon flows to other Annex 1	-39	Annex 1
Carbon flows from non-Annex 1	104	Other non-Annex 1
Carbon flows from non-Annex 1	64	China
Carbon flows to non-Annex 1	-25	Non-Annex 1
UK consumption emissions	845	UK

I think the two most important messages that people can get from a short course are:

a) the material is important and worthwhile to learn (even if it's challenging), and b) it's possible to learn it!

For those reasons, I usually start by diving as quickly as possible into visualisation. I think it's a bad idea to start by explicitly teaching programming concepts (like data structures), because the pay off isn't obvious. If you start with visualisation, the pay off is really obvious and people are more motivated to push past any initial teething problems. In stat405, I used to start with some very basic templates that got people up and running with scatterplots and histograms - they wouldn't necessary understand the code, but they'd know which bits could be varied for different effects.

Apart from visualisation, I think the two most important topics to cover are tidy data (i.e. http://www.jstatsoft.org/v59/i10/ + tidyr) and data manipulation (dplyr). These are both important for when people go off and apply

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

	val n = 9
	val s = Math.sqrt(n).toInt
	type Board = IndexedSeq[IndexedSeq[Int]]

	def solve(board: Board, cell: Int = 0): Option[Board] = (cell%n, cell/n) match {
	case (r, `n`) => Some(board)
	case (r, c) if board(r)(c) > 0 => solve(board, cell + 1)
	case (r, c) =>
	def guess(x: Int) = solve(board.updated(r, board(r).updated(c, x)), cell + 1)
	val used = board.indices.flatMap(i => Seq(board(r)(i), board(i)(c), board(s(r/s) + i/s)(s(c/s) + i%s)))

	@import url(http://fonts.googleapis.com/css?family=Roboto+Slab:700\|Exo+2:300,600);

	/* Eric Meyer's Reset CSS v2.0 - http://cssreset.com */
	html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,img,ins,kbd,q,s,samp,small,strike,strong,sub,sup,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td,article,aside,canvas,details,embed,figure,figcaption,footer,header,hgroup,menu,nav,output,ruby,section,summary,time,mark,audio,video{border:0;font-size:100%;font:inherit;vertical-align:baseline;margin:0;padding:0}article,aside,details,figcaption,figure,footer,header,hgroup,menu,nav,section{display:block}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:none}table{border-collapse:collapse;border-spacing:0}

	/* Solarized Palette - http://ethanschoonover.com/solarized ---------
	lightgray : #819090;
	gray : #70


	library(shiny)
	library(dplyr)
	library(lubridate)

	# Load libraries and functions needed to create SQLite databases.
	library(RSQLite)
	library(RSQLite.extfuns)
	saveSQLite <- function(data, name){
	path <- dplyr:::db_location(filename=paste0(name, ".sqlite"))