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<!DOCTYPE html>
<html>
<head>
<title>Introduction to R markdown</title>
<meta charset="utf-8">
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<meta http-equiv="X-UA-Compatible" content="chrome=1">
<meta name="generator" content="pandoc" />
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="apple-mobile-web-app-capable" content="yes">
<base target="_blank">
<script type="text/javascript">
var SLIDE_CONFIG = {
// Slide settings
settings: {
title: 'Introduction to R markdown',
subtitle: 'Dynamic documents for R',
useBuilds: true,
usePrettify: true,
enableSlideAreas: true,
enableTouch: true,
},
// Author information
presenters: [
{
name: 'DSP作者群' ,
company: '',
gplus: '',
twitter: '',
www: '',
github: ''
},
]
};
</script>
<link href="R_markdown_files/ioslides-13.5.1/fonts/fonts.css" rel="stylesheet" />
<link href="R_markdown_files/ioslides-13.5.1/theme/css/default.css" rel="stylesheet" />
<link href="R_markdown_files/ioslides-13.5.1/theme/css/phone.css" rel="stylesheet" />
<script src="R_markdown_files/ioslides-13.5.1/js/modernizr.custom.45394.js"></script>
<script src="R_markdown_files/ioslides-13.5.1/js/prettify/prettify.js"></script>
<script src="R_markdown_files/ioslides-13.5.1/js/prettify/lang-r.js"></script>
<script src="R_markdown_files/ioslides-13.5.1/js/prettify/lang-yaml.js"></script>
<script src="R_markdown_files/ioslides-13.5.1/js/hammer.js"></script>
<script src="R_markdown_files/ioslides-13.5.1/js/slide-controller.js"></script>
<script src="R_markdown_files/ioslides-13.5.1/js/slide-deck.js"></script>
<style type="text/css">
b, strong {
font-weight: bold;
}
em {
font-style: italic;
}
summary {
display: list-item;
}
slides > slide {
-webkit-transition: all 0.4s ease-in-out;
-moz-transition: all 0.4s ease-in-out;
-o-transition: all 0.4s ease-in-out;
transition: all 0.4s ease-in-out;
}
.auto-fadein {
-webkit-transition: opacity 0.6s ease-in;
-webkit-transition-delay: 0.4s;
-moz-transition: opacity 0.6s ease-in 0.4s;
-o-transition: opacity 0.6s ease-in 0.4s;
transition: opacity 0.6s ease-in 0.4s;
opacity: 0;
}
</style>
<link rel="stylesheet" href="css/dsp.css" type="text/css" />
</head>
<body style="opacity: 0">
<slides class="layout-widescreen">
<slide class="title-slide segue nobackground">
<!-- The content of this hgroup is replaced programmatically through the slide_config.json. -->
<hgroup class="auto-fadein">
<h1 data-config-title><!-- populated from slide_config.json --></h1>
<h2 data-config-subtitle><!-- populated from slide_config.json --></h2>
<p data-config-presenter><!-- populated from slide_config.json --></p>
<p style="margin-top: 6px; margin-left: -2px;">2019-05</p>
</hgroup>
</slide>
<slide class=""><hgroup><h2>What does data analyst do?</h2></hgroup><article id="what-does-data-analyst-do">
<center>
<img src='img/analyst.png' style='max-width: 67%;max-height: 67%'></img><br/><small><a href='http://goo.gl/52THNf' title=''>http://goo.gl/52THNf</a></small>
</center>
</article></slide><slide class=""><hgroup><h2>What does data analyst actually do</h2></hgroup><article id="what-does-data-analyst-actually-do">
<center>
<img src='img/ResearchPipeline.png' style='max-width: 84%;max-height: 84%'></img><br/><small><a href='https://www.coursera.org/course/repdata' title=''>https://www.coursera.org/course/repdata</a></small>
</center>
</article></slide><slide class=""><hgroup><h2>Why you need R Markdown?</h2></hgroup><article id="why-you-need-r-markdown">
<div style="float:right; margin: 200px;">
<p><img src='img/one1.jpg' style='height: 250px'></img></p></div>
<ul>
<li><strong>資料分析</strong>做不完<br><br/></li>
<li><strong>說明文件</strong>沒空寫<br><br/></li>
<li><strong>教授</strong>要求換方法<br><br/></li>
<li><strong>老闆</strong>說要改流程<br><br/></li>
<li><strong>客戶</strong>要我做做看<br><br/></li>
<li>年度報告要總結<br></li>
</ul>
</article></slide><slide class=""><hgroup><h2>Why you need R Markdown</h2></hgroup><article id="why-you-need-r-markdown-1">
<center>
<img src='img/zikannai2.png' style='max-width: 100%;max-height: 100%'></img><br/><small><a href='http://goo.gl/YiJrlI' title=''>http://goo.gl/YiJrlI</a></small>
</center>
</article></slide><slide class=""><hgroup><h2>What is R Markdown?</h2></hgroup><article id="what-is-r-markdown">
<p>A convenient tool to generate reproducible documents.</p>
<ul>
<li><a href='http://daringfireball.net/projects/markdown/basics' title=''>Markdown</a>
<ul>
<li>Lightweight markup language</li>
<li>Remove HTML tag for higher readibility.</li>
<li>Inline HTML is avaliable.</li>
</ul></li>
<li>R markdown
<ul>
<li>Markdown + embedded R code chunks</li>
<li>(.Rmd) -> (.md) -> (.html, .docx, .pdf)</li>
</ul></li>
</ul>
</article></slide><slide class=""><hgroup><h2>Why R Markdown</h2></hgroup><article id="why-r-markdown">
<ul>
<li>製作reproducible的報告、投影片: <code>document</code> 、 <code>slides</code></li>
<li>想寫數學式子好展現自己的專業 \(e=mc^2\): <code>mathjax</code></li>
<li>只有一份source code，不需要額外複製圖片到報告中: <code>.rmd</code></li>
<li>需求更改時，可以動態改變報告內容: <code>integrated shiny</code></li>
<li>增加資料分析演算法的可讀性: <code>code and text</code></li>
<li>HTML的報告和投影片的格式方便瀏覽: <code>html</code></li>
<li>IDE? RStudio提供支援: <code>Knit Button</code></li>
</ul>
</article></slide><slide class=""><hgroup><h2>Installation</h2></hgroup><article id="installation">
<ul>
<li>最新版的RStudio已經包含R Markdown功能<br/></li>
<li>你也可以透過以下指令安裝R Markdown套件：</li>
</ul>
<pre class = 'prettyprint lang-r'>install.packages("rmarkdown")</pre>
</article></slide><slide class="segue dark nobackground level1"><hgroup class = 'auto-fadein'><h2>R Markdown 快速導覽</h2></hgroup><article id="r-markdown-">
</article></slide><slide class=""><hgroup><h2>Overview</h2></hgroup><article id="overview">
<center>
<img src='img/RmdOverview.png' style='max-width: 77%;max-height: 77%'></img>
</center>
</article></slide><slide class=""><hgroup><h2>Markdown</h2></hgroup><article id="markdown">
<center>
<img src='img/markdownOverview.png' style='max-width: 200%;max-height: 200%'></img>
</center>
</article></slide><slide class=""><hgroup><h2>R Code Chunks</h2></hgroup><article id="r-code-chunks">
<center>
<img src='img/markdownChunk.png' style='max-width: 70%;max-height: 70%'></img>
</center>
</article></slide><slide class=""><hgroup><h2>Inline R Code</h2></hgroup><article id="inline-r-code">
<ul>
<li>利用 `r` 在markdown中插入R程式</li>
</ul>
<pre >- 這是DSP推出的第 `ｒ 3+1`門課程 </pre>
<ul>
<li>這是DSP推出的第 4門課程</li>
</ul>
<pre >- 鳶尾花資料集(iris dataset)有 `ｒ levels(iris$Species)` 等種類，
總共有 `ｒ length(levels(iris$Species))` 種</pre>
<ul>
<li>鳶尾花資料集(iris dataset)有 setosa, versicolor, virginica 等種類，<br/>總共有 3 種</li>
</ul>
</article></slide><slide class=""><hgroup><h2>Inline R Equations</h2></hgroup><article id="inline-r-equations">
<ul>
<li>插入 LaTeX 公式的方法：<br/></li>
<li>行內<code>$ equation $</code><br/></li>
<li>段落 <code>$$ equation $$</code></li>
</ul>
<pre >熵指標的公式為 $-\sum{p_i \log{p_i}}$ ，表示系統的亂度 </pre>
<p>熵指標的公式為 \(-\sum{p_i \log{p_i}}\) ，表示系統的亂度</p>
<pre >請計算高斯分佈 $$f(x;\mu,\sigma^2) = \frac{1}{\sigma\sqrt{2\pi}}
e^{ -\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2 }$$ </pre>
<p>請計算高斯分佈 \[f(x;\mu,\sigma^2) = \frac{1}{\sigma\sqrt{2\pi}} e^{ -\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2 }\]</p>
</article></slide><slide class=""><hgroup><h2>Rendering Output</h2></hgroup><article id="rendering-output">
<ul>
<li>RStudio: "Knit" command:
<ul>
<li>(Win:Ctrl+Shift+K / OSX:Command+Shirt+K)<br/></li>
</ul></li>
<li>Command line: rmarkdown::render function</li>
</ul>
<pre class = 'prettyprint lang-r'>rmarkdown::render("input.Rmd")</pre>
</article></slide><slide class="segue dark nobackground level1"><hgroup class = 'auto-fadein'><h2>Markdown Basics</h2></hgroup><article id="markdown-basics">
</article></slide><slide class=""><hgroup><h2>Markdown Quick Reference</h2></hgroup><article id="markdown-quick-reference">
在RStudio中，在UI界面中點選<code>help (?)</code>可以查閱Markdown語法<br/>
<center>
<img src='img/MdRef.png' style='max-width: 75%;max-height: 75%'></img>
</center>
</article></slide><slide class="segue dark nobackground level1"><hgroup class = 'auto-fadein'><h2>R Code Chunks</h2></hgroup><article id="r-code-chunks-1">
</article></slide><slide class=""><hgroup><h2>Overview</h2></hgroup><article id="overview-1">
<p>R code will be evaluated and printed</p>
<pre class="markdown"><code>```{r}
summary(cars$dist)
```
</code></pre>
<pre class = 'prettyprint lang-r'>summary(cars$dist)</pre>
<pre > Min. 1st Qu. Median Mean 3rd Qu. Max.
2 26 36 43 56 120 </pre>
</article></slide><slide class=""><hgroup><h2>Overview (cont.)</h2></hgroup><article id="overview-cont.">
draw graphics
<pre class="markdown"><code>```{r}
plot(women)
```
</code></pre>
<pre class = 'prettyprint lang-r'>plot(women) </pre>
<p><img src="R_markdown_files/figure-html/plot1-1.png" width="768" /></p>
</article></slide><slide class=""><hgroup><h2>Named R code chunk.</h2></hgroup><article id="named-r-code-chunk.">
<pre class="markdown"><code>```{r plot}
summary(cars)
plot(cars)
```
</code></pre>
<ul>
<li>Easy Navigation in RStudio</li>
</ul>
<p><img src='img/chunk_name.png' style='max-width: 70%;max-height: 70%'></img></p>
</article></slide><slide class=""><hgroup><h2>Basic Chunk Options</h2></hgroup><article id="basic-chunk-options">
<ul>
<li><code>echo</code>(TRUE): whether to include R source code in the output file<br/></li>
<li><code>eval</code>(TRUE): whether to evaluate the code chunk<br/></li>
<li><code>message</code>(TRUE): whether to preserve messages emitted by message()<br/></li>
<li><code>results</code>('hide','asis'): hide output ; asis treats the output of your R code as literal Markdown (when using like kable function)<br/><br></li>
<li><code>include</code>(TRUE): whether to be written into the output document, but the code is still evaluated and plot files are generated<br/></li>
<li><code>warning</code>(TRUE): whether to preserve warnings in the output</li>
<li><code>comment</code>("##"): set to comment notation</li>
</ul>
</article></slide><slide class=""><hgroup><h2>Basic Chunk Options (cont.)</h2></hgroup><article id="basic-chunk-options-cont.">
<p>Set global chunk options at code chunks header:</p>
<pre class = 'prettyprint lang-r'>knitr::opts_chunk$set(echo=FALSE, results='hide')</pre>
</article></slide><slide class=""><hgroup><h2>Exercise：</h2></hgroup><article id="exercise">
<p>利用R Markdown 製作《一周天氣預報》書面報告。<a href='https://dspim.github.io/A1-basic-data-analysis/RMD-example/RmdExAns.html' title=''>範例</a><br/>* <a href='http://www.cwb.gov.tw/V7/forecast/taiwan/Taipei_City.htm' title=''>原始出處</a><br/>* <a href='https://github.com/dspim/a1-basic-data-analysis-course/blob/master/RmdExQue.Rmd' title=''>參考範本</a><br/>* <a href='https://github.com/dspim/a1-basic-data-analysis-course/blob/master/data/weather-utf8.csv' title=''>範例資料</a></p>
</article></slide><slide class=""><hgroup><h2>Exercise: Original：</h2></hgroup><article id="exercise-original">
<p><img src='img/forecast_tpe1.png' style='max-width: 100%;max-height: 100%'></img></p>
</article></slide><slide class=""><hgroup><h2>Exercise: After：</h2></hgroup><article id="exercise-after">
<p><img src='img/exam_q1.png' style='max-width: 60%;max-height: 60%'></img></p>
</article></slide><slide class=""><hgroup><h2>Exercise Q1</h2></hgroup><article id="exercise-q1">
<p>利用R Markdown 製作《一周天氣預報》書面報告。 - 計算01/28日當日的最高溫與最低溫度</p>
<pre class = 'prettyprint lang-r'># Hint：
# 1. 下載weather-utf8.csv到自己的電腦上
# 2. 在R chunk中，利用read.csv()讀取檔案進行分析
# Windows: read.csv(,fileEncoding="UTF-8")
# 3. 找出01/28當日最高溫 max()
# 4. 找出01/28當日最低溫 min()
# 5. use inline R chunk `r max(...)` </pre>
</article></slide><slide class=""><hgroup><h2>Exercise A1</h2></hgroup><article id="exercise-a1">
<p>利用R Markdown 製作《一周天氣預報》書面報告。 - 計算01/28日當日的最高溫與最低溫度</p>
<pre class = 'prettyprint lang-r'># Hint for Linux & Mac：
dat <- read.csv("data/weather-utf8.csv")
max(dat[1:2, 4:5])
min(dat[1:2, 4:5])
# 預測高溫約`r max(dat[1:2,4:5])`度，低溫約`r min(dat[1:2,4:5])`度</pre>
<pre class = 'prettyprint lang-r'># Hint for Windows：
dat <- read.csv("data/weather-utf8.csv", fileEncoding="UTF-8")
max(dat[1:2, 4:5])
min(dat[1:2, 4:5])
# 預測高溫約`r max(dat[1:2,4:5])`度，低溫約`r min(dat[1:2,4:5])`度</pre>
</article></slide><slide class=""><hgroup><h2>Table Output</h2></hgroup><article id="table-output">
<ul>
<li>Print data directly:</li>
</ul>
<pre class = 'prettyprint lang-r'>print(head(women))</pre>
<pre > height weight
1 58 115
2 59 117
3 60 120
4 61 123
5 62 126
6 63 129</pre>
</article></slide><slide class=""><hgroup><h2>Table Output (cont.)</h2></hgroup><article id="table-output-cont.">
<ul>
<li>Using <code>knitr::kable</code> :
<ul>
<li>Set <code>results='asis'</code> to write raw results from R into the output document<br/>
<pre class="markdown"><code>```{r, results='asis'}
knitr::kable(women)
```
</code></pre></li>
</ul></li>
</ul>
<table class = 'rmdtable'>
<tr class="header">
<th align="right">height</th>
<th align="right">weight</th>
</tr>
<tr class="odd">
<td align="right">58</td>
<td align="right">115</td>
</tr>
<tr class="even">
<td align="right">59</td>
<td align="right">117</td>
</tr>
<tr class="odd">
<td align="right">60</td>
<td align="right">120</td>
</tr>
<tr class="even">
<td align="right">61</td>
<td align="right">123</td>
</tr>
<tr class="odd">
<td align="right">62</td>
<td align="right">126</td>
</tr>
<tr class="even">
<td align="right">63</td>
<td align="right">129</td>
</tr>
</table>
</article></slide><slide class=""><hgroup><h2>Exercise Q2</h2></hgroup><article id="exercise-q2">
<p>利用R Markdown 製作《一周天氣預報》書面報告。 - 製作未來七天天氣預報表</p>
<pre class = 'prettyprint lang-r'># Hint：
# 你可能需要dplyr套件
# 可以先用filter把白天、晚上分開處理
# 利用 paste(低溫,高溫,sep="-") 來製作溫度區間, i.e. 16-17
# 利用colnames, rownames來對整理好的資料表的行與列命名</pre>
</article></slide><slide class=""><hgroup><h2>Exercise A2</h2></hgroup><article id="exercise-a2">
<p>利用R Markdown 製作《一周天氣預報》書面報告。 - 製作未來七天天氣預報表</p>
<pre class = 'prettyprint lang-r'>library(dplyr)
day1 <- filter(dat, 早晚=="白天")
day2 <- mutate(day1, 溫度=paste(高溫,低溫,sep="-"))
day3 <- select(day2, 天氣, 溫度)
night1 <- filter(dat, 早晚=="晚上")
night2 <- mutate(night1, 溫度=paste(高溫,低溫,sep="-"))
night3 <- select(night2, 天氣, 溫度)
out <- data.frame(t(bind_cols(day3, night3)))
colnames(out) <- day1$日期
rownames(out) <- c("白天天氣","白天溫度","晚上天氣","晚上溫度")</pre>
</article></slide><slide class=""><hgroup><h2>Exercise A2 (conti.)</h2></hgroup><article id="exercise-a2-conti.">
<p>利用R Markdown 製作《一周天氣預報》書面報告。 - 製作未來七天天氣預報表</p>
<pre class="prettyprint lang-r"><code>```{r results='asis', echo=FALSE}
knitr::kable(out)
```</code></pre>
</article></slide><slide class=""><hgroup><h2>Exercise Q3</h2></hgroup><article id="exercise-q3">
<p>利用R Markdown 製作《一周天氣預報》書面報告。 - 製作未來七天天氣預報圖</p>
<pre class = 'prettyprint lang-r'># Hint：
# 你可能需要ggplot2套件
# Mac顯示中文需設置字型
# http://equation85.github.io/blog/graph-font-of-r-in-mac-os-x/
# par(family='STHeiti')</pre>
</article></slide><slide class=""><hgroup><h2>Exercise A3</h2></hgroup><article id="exercise-a3">
<p>利用R Markdown 製作《一周天氣預報》書面報告。 - 製作未來七天天氣預報圖</p>
<pre class = 'prettyprint lang-r'>library(ggplot2);library(reshape2)
dat1 <- mutate(dat, 時間=paste(日期,早晚,sep="\n"))
dat2 <- select(dat1, 時間, 高溫, 低溫)
colnames(dat2)[1] <- "時間" # for Windows user
dat3 <- melt(dat2)
g <- ggplot(dat3, aes(x=時間, y=value, group=variable, colour=variable)) +
geom_line() +
labs(x="時間", y="溫度") </pre>
<pre class = 'prettyprint lang-r'># 顯示中文字 Mac user only
g + theme_gray(base_family="STHeiti") </pre>
</article></slide><slide class=""><hgroup><h2>Exercise</h2></hgroup><article id="exercise-1">
<p>利用R Markdown 製作《一周天氣預報》書面報告。</p>
<ul>
<li><a href='http://www.cwb.gov.tw/V7/forecast/taiwan/Taipei_City.htm' title=''>原始出處</a></li>
<li><a href='https://github.com/dspim/a1-basic-data-analysis-course/blob/master/RmdExQue.Rmd' title=''>參考範本</a></li>
<li><a href='https://github.com/dspim/a1-basic-data-analysis-course/blob/master/data/weather-utf8.csv' title=''>範例資料</a></li>
<li><a href='https://github.com/dspim/a1-basic-data-analysis-course/blob/master/RmdExAns.Rmd' title=''>參考解答</a></li>
</ul>
</article></slide><slide class="segue dark nobackground level1"><hgroup class = 'auto-fadein'><h2>Appendiex</h2></hgroup><article id="appendiex">
</article></slide><slide class=""><hgroup><h2>About Document Content</h2></hgroup><article id="about-document-content">
You can add R Markdown and HTML in the YAML content.
<pre class="prettyprint lang-yaml"><code>
---
title: "Introduction to R Markdown"
author: "DSP作者群"
date: "2019-05"
output: html_document
---
</code></pre>
</article></slide><slide class=""><hgroup><h2>YAML metadata</h2></hgroup><article id="yaml-metadata">
<center>
<img src='img/Cover.png' style='max-width: 80%;max-height: 80%'></img><br/>Cover by Wush
</center>
</article></slide><slide class=""><hgroup><h2>Some Useful HTML</h2></hgroup><article id="some-useful-html">
<ul>
<li><p><a href='http://www.w3schools.com/tags/tag_iframe.asp' title=''>iframe</a>: displaying a web page within a web page</p>
<pre class = 'prettyprint lang-html'><iframe src="http://dsp.im/" height=600 width=800></iframe></pre></li>
<li><p><a href='http://www.w3schools.com/tags/tag_img.asp' title=''>img</a>: inserting images into an HTML document. Much easier for adjusting width and height.</p>
<pre class = 'prettyprint lang-html'><img src="img/dsp-logo.png" alt="logo"></pre>
<p><img src="img/dsp-logo.png" alt="logo"></p></li>
</ul>
</article></slide><slide class=""><hgroup><h2>Interactive Documents</h2></hgroup><article id="interactive-documents">
It’s possible to embed a Shiny application within a document.
<div style="float: left; width: 50%;">
<p><img src='img/shiny-cars-table.gif' style='max-width: 90%;max-height: 90%'></img></p></div>
<div style="float: right; width: 50%;">
<p><img src='img/shiny-hist-plot.gif' style='max-width: 90%;max-height: 90%'></img></p></div>
</article></slide><slide class=""><hgroup><h2>Publish to the web</h2></hgroup><article id="publish-to-the-web">
<p>Using R packages::slidify to publish your slides to the web</p>
<pre >library(slidify)
publish_github("repo", username="user_name")
publish_rpubs("title","file_name.html")
publish_dropbox(dir_name)
publish_gist("title",file="file_name.html",publish=TRUE)</pre>
</article></slide><slide class=""><hgroup><h2>Publish to the web: Github</h2></hgroup><article id="publish-to-the-web-github">
<ol>
<li>sign up or login in Github.com at browser</li>
<li>find button: New repository to add new one.</li>
<li>select a name for repository, then created.</li>
<li>the link of your new repository would be like:<br/><a href='https://github.com/your_name/repo_name.git' title=''>https://github.com/"your_name"/"repo_name".git</a></li>
<li>find Settings in your profile at top-right corner</li>
<li>select SSH Keys and add SSH Key</li>
<li>upload your SSH key which created by your own PC/notebook.</li>
<li>at RStudio, using Rcommand:<br/>slidify::publish_github("repo_name", username="your_name")</li>
<li>your new page will be ready in 5~10 min and link:<br/><a href='https://your_name.github.io/repo_name/index.html' title=''>https://"your_name".github.io/"repo_name"/index.html</a></li>
</ol>
</article></slide><slide class=""><hgroup><h2>References</h2></hgroup><article id="references">
<ul>
<li><a href='http://mansunkuo.github.io/rmd_tutorial/' title=''>An Introduction to R Markdown*</a> by Mansun Kuo @ <a href='http://taiwanrusergroup.github.io/DSC2014Tutorial/' title=''>DSC2014</a></li>
<li><a href='http://shiny.rstudio.com/articles/rm-cheatsheet.html' title=''>R Markdown Cheat Sheet</a></li>
<li><a href='http://rmarkdown.rstudio.com/' title=''>R Markdown</a></li>
<li><a href='http://yihui.name/knitr/' title=''>knitr</a></li>
<li><a href='https://support.rstudio.com/hc/en-us/categories/200035113-Documentation' title=''>RStudio Documentation</a></li>
<li><a href='https://www.coursera.org/course/repdata' title=''>Reproducible Research</a></li>
<li><a href='http://shiny.rstudio.com/articles/' title=''>Shiny Articles</a></li>
<li><a href='http://slidify.org/publish.html' title=''>Publish to Github Pages/Dropbox/Rpubs</a></li>
</ul>
</article></slide><slide class=""><hgroup><h2>Wush 教學影片</h2></hgroup><article id="wush-">
<p><a href='https://www.youtube.com/watch?v=P97udK2ktuY' title=''>Slidify簡介</a> by Wush Wu<br/><a href='https://www.youtube.com/watch?v=P97udK2ktuY' title=''>https://www.youtube.com/watch?v=P97udK2ktuY</a></p>
<p><a href='https://www.youtube.com/watch?v=OHKZLeKlUsM' title=''>20121203 MLDM Monday:markdown + knitr (Hangout 轉播)</a> by Wush Wu<br/><a href='https://www.youtube.com/watch?v=OHKZLeKlUsM' title=''>https://www.youtube.com/watch?v=OHKZLeKlUsM</a></p></article></slide>
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