index.Rmd

---
title       : This is R:esult
subtitle    : Of course this doucment made from R.
author      : Yuri Ohno
job         : Free
framework   : io2012        # {io2012, html5slides, shower, dzslides, ...}
highlighter : highlight.js  # {highlight.js, prettify, highlight}
hitheme     : tomorrow      # 
widgets     : [bootstrap, quiz, shiny, interactive]            # {mathjax, quiz, bootstrap}
mode        : selfcontained # {standalone, draft}
ext_widgets : {rCharts: [libraries/nvd3, libraries/highcharts]}
knit        : slidify::knit2slides
--- .quote .nobackground .segue .dark

<center>
  <q>I hope this is helpful.</q>
</center>

---

# Agenda

* Demonstrate Interactive Document with R and buddies
* And how will you share it ?
* rCharts Capabilites
* GoogleViz Capabilities

---

## Preliminary

You prepare RStudio(newer is better) and R(>3.0).

<img src="http://shiny.rstudio.com/tutorial/lesson2/www/bigorb.png" width="100" height="100">

First of all, I'm sorry to say: you need Proxy...
Type setting on RStudio console following manner.

```r
Sys.setenv("http_proxy"="http://(your ID):(your PW)@proxy.xxxx.com:8080/")
```

And also if you use ```devtools::install_github(package)``` command, you should below setting.

```r
library(httr)
set_config(
  use_proxy(url="proxy.xxxx.com", port=8080, username="your ID",password="your PW")
)
```

---

## Caracters - Slidify

<img src="./assets/img/slidify_logo.png">

> Slidify helps you create and publish beautiful HTML5 presentations from RMarkdown.

* Install

```r
require(devtools)
install_github(c('slidify', 'slidifyLibraries'), 'ramnathv')
```

---

## Caracters - rCharts

<img src="./assets/img/rcharts_logo.png">

> rCharts is an R package to create, customize and publish interactive javascript visualizations from R using a familiar lattice style plotting interface.

* Install

```r
require(devtools)
install_github('rCharts', 'ramnathv')
```

---

## Caracters - Shiny

> A web application framework for R. Trurn your analyses into interactive web applications. No HTML, CSS, or JavaScript knowledge required.

* Install

```r
require(devtools)
install_github('shiny', 'rstudio')
```

---

## Sub Caracters - GoogleViz

> The googleVis package provides an interface between R and the Google Charts API.
It allows users to create web pages with interactive charts based on R data frames, using the Google Charts API and to display them either via the local R HTTP help server or within their own sites, without uploading the data to Google. A modern browser with Internet connection is required and for some charts Flash.

```r
install.packages('googleVis')
```

---

## Sub Caracters - SPARQL

> SPARQL is a kind of query language regarding with RDF(Resource Description Framework). R has plug-in support [SPARQL client](http://cran.r-project.org/web/packages/SPARQL/index.html)

* Install

```r
install.packages("SPARQL")
```

--- .segue .dark

## Dive into Dynamic Document

---

## いんたらくてぃぶ　ちゃーと

Japanse also goes well.<br>
日本語でも大丈夫 (Windowsはむりー！)

```{r echo = F, results = 'asis'}
# require(rCharts)
haireye <- as.data.frame(HairEyeColor)
n1 <- nPlot(Freq ~ Hair, group = 'Eye', type = 'multiBarChart',
    data = subset(haireye, Sex == "Male")
)
n1$print('chart1')
```

---

## SPARQL

<img src="./assets/img/aitc_logo_small.png">

Get Start with "Disaster Prevention Information from Japan Meteorological Agency".
Endpoint is "http://api.aitc.jp/ds/sparql". Because of lack of authetication, we should not hit it many times....

```
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX atom: <http://www.w3.org/2005/Atom#>
PREFIX jma: <http://cloud.projectla.jp/jma/>
PREFIX area: <http://cloud.projectla.jp/jma/area#>
PREFIX link2: <http://cloud.projectla.jp/jma/link2/>
SELECT ?title ?mon (COUNT(?id) as ?c) 
WHERE { ?id atom:title ?title . ?id atom:updated ?updated } 
GROUP BY ?title (CONCAT(STR(YEAR(xsd:dateTime(?updated))), '/', STR(MONTH(xsd:dateTime(?updated))), '/01') AS ?mon)
```

---

## And then done

Unfortunatly API is very very fragile. So I stored data to CSV file(met.csv).

```r
# implement library
require(SPARQL)
require(rCharts)

# set endpoint
endpoint <- "http://api.aitc.jp/ds/sparql"

# set query with SPARQL
q <- "(I mentioned before.)""

# Get Result
result <- SPARQL(url=endpoint, query=q, ns=prefix, extra=list(output="csv"), format="csv")
write.csv(result$result, file = "met.csv", row.names = T)
```

---

## Visualization

Let's go on to the visualization with Highcharts.

<center>
```{r echo = F, results='asis'}
require(rCharts)
result <- read.csv('met.csv', header=T, encoding="utf-8")
result <- transform(result, date=as.Date(mon))
reuslt <- result[order(result$title, result$date),]
reuslt <- result[as.Date("2013/01/01")<=result$date,]

# Visualize with Highchart
result = transform(result, date = as.numeric(as.POSIXct(date))*1000)
p1 <- hPlot(c ~ date, data=result, group="title")
p1$xAxis(type='datetime', labels=list(format='{value:%Y-%m}'))
p1$print("chart2")
```
</center>

---

## And More

Including Shiny, we can dive into data (If shiny server doesn't run, you can't see below chart.)

```{r opts.label = 'shiny'}
slidifyUI(
  sidebarPanel(
    selectInput('title', 'Choose Data', c('気象特別警報・警報・注意報', '土砂災害警戒情報', '震源に関する情報')),
    selectInput('type', 'Choose Type',
                c('line', 'scatter')
    )
  ),
  mainPanel(
    tags$div(id = 'metplot', class='shiny-html-output rChart')  
  )
)
```

--- .segue .dark

## And how will you share it ?

--- .quote

## Unfortunatly that might be quit difficult !

Shiny apps need to run above shiny server.
In this case, back logic cann't be packed into client app.
I mean that with only iPad you cann't view it.

<q>In conclusion, you should create iOS app like shiny server.</q>

--- .segue .dark

## rCharts Capabilities

---

* So many JavaScript Vizualization Tool include in.
  * Polycharts
  * Morris
  * NVD3
  * xCharts
  * HighCharts
  * Leaflet
  * Rickshaw
  * end more !
* You can play in [here](http://ramnathv.github.io/rCharts/).

--- .segue .dark

## GoogleVis Capabilities

---

* Below official document is very helpful at first time
  * [GoogleVis](http://decastillo.github.io/googleVis_Tutorial/#14)

---

## Reference

* [Interactive Doucments](http://slidify.github.io/dcmeetup/demos/interactive/)
* [気象庁XMLのSPARQL APIを利用してデータを俯瞰しよう](http://www.slideshare.net/yasuyukisugai/20144-aitc)
* [rCharts](http://ramnathv.github.io/rCharts/)
* [GoogleVis](https://github.com/mages/googleVis)