R (2)

Data Science

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2016/10/17()

. CC --

3.0 http://shouzo.github.io/

Agenda() Prepare() Basic() Theme() Reference

() Prepare

() Prepare

() Prepare

"RStudio"

() Basic

() Basic

() Basic 1.

1.

R rvest

https://blog.gtwang.org/r/rvest-web-scraping-with-r/

() Basic 1.

Xpath

() Basic

Google (Chrome) -

1.

() Basic

Mozilla Firefox - FireBug

1.

() Basic 1.

Xpath

https://github.com/aweimeowaweimeow

() Basic 1.

() Basic 1.

() Basic 1.

() Basic 1.

() Basic 1.

Xpath

() Basic 1.

() Basic 1.

() Basic 1.

() Basic 1.

TAG

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2.

2.

() Basic 2.

(1) CSV(2) XML(3) JSON(4) DB ()(5) RData(6) SPSSStataSASOctave ...

CSV

() BasicCSV STEP1read.table()

CSV ( tab )

read.csv2()

read.delim2()

[ ]

read.table (file= , header= TRUE or FALSE, sep= "")[ ]

file header sep

#()theUrl

() BasicCSV

STEP2head()[ ] head()

STEP3data.frame()[ ] data.frame (1 = 1, 2 = 2, 3 = 3, ......,stringsAsFactors=TRUE or False)[ ] stringsAsFactors character () factor character

2.

() BasicSTEP2STEP3

>head(tomato) #RoundTomatoPriceSourceSweetAcidColorTextureOverall 11SimpsonSM 3.99WholeFoods 2.82.83.73.43.421Tuttorosso(blue) 2.99Pioneer 3.32.83.43.02.931Tuttorosso(green) 0.99Pioneer 2.82.63.32.82.941LaFedeSMDOP 3.99ShopRite 2.62.83.02.32.852CentoSMDOP 5.49DAgostino 3.33.12.92.83.162CentoOrganic 4.99DAgostino 3.22.92.93.12.9Avg.of.TotalsTotal.of.Avg 1 16.116.12 15.315.33 14.314.34 13.413.45 14.415.26 15.515.1>>xy#"q"character>q>theDFtheDF$Sport [1]"Hockey""Football" "Baseball" "Curling""Rugby""Lacrosse" [7]"Basketball" "Tennis""Cricket""Soccer"

2.

() Theme

() Theme

() Theme

(1) ""

(2)

(3)

() Theme

1.

1.

() Theme 1.

STEP 1STEP 2STEP 3""STEP 4""STEP 5""

Text mining and word cloud fundamentals in R5 simple steps you should know

https://goo.gl/snM2nZ

() Theme 1. STEP 1

http://www.technewsworld.com/story/83998.htmlBig Data and Analytics: Creating New Value

() Theme 1. STEP 1

() Theme 1. STEP 2

#install.packages("rvest")#""install.packages("tm")#""install.packages("SnowballC")#Textstemminginstall.packages("wordcloud")#""install.packages("RColorBrewer")#Colorpalettes

#library("rvest")library("tm")library("SnowballC")library("wordcloud")library("RColorBrewer")

RStudio

() Theme 1. STEP 3""

Chrome "" ( "F12")

() Theme 1.

"Copy Xpath"

2

2

1

STEP 3""

() Theme 1. STEP 3""

Xpath ()

//*[@id="storybody"] Xpath

() Theme 1. STEP 3""

#"source.page"source.page

() Theme 1. STEP 3""

#""docs

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""

#""toSpace

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dtm

() Theme 1. STEP 5""

#set.seed(1000)

#wordcloud(words=d$word,freq=d$freq,min.freq= 2,max.words=30,random.order=FALSE,rot.per=0.35,colors=brewer.pal( 8,"Dark2"))

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2.

2.

() Theme 2.

STEP 1STEP 2STEP 3""STEP 4""STEP 5""

http://andrew.ga/works/TextMining/

() Theme 2. STEP 1

http://www.appledaily.com.tw/realtimenews/arti

cle/life/20161016/968938/

() Theme 2. STEP 1

() Theme 2. STEP 2

RStudio#install.packages("rvest")#""install.packages("jiebaR")#""install.packages("tm")#""install.packages("wordcloud2")#""

#library("rvest")library("jiebaR")library("tm")library("wordcloud2")

() Theme 2. STEP 3""

Chrome "" ( "F12")

() Theme 2. STEP 3""

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2

"Copy Xpath"

() Theme 2. STEP 3""

Xpath ()

//*[@id="summary"] Xpath

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#"source.page"source.page

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space_tokenizer= function(x){unlist(strsplit(as.character(x[[ 1]]),'[[:space:]]+' ))}

jieba_tokenizer= function(d){unlist(segment(d[[ 1]],mixseg)) }

#CNCorpus####CNCorpusFunctionStart#### CNCorpus= function(d.vec){doc

() Theme 2.

content.corpus=CNCorpus(list(content.vec))#CNCorpuscontent.corpus

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frequency

() Reference

() Reference

http://datascienceandr.org/

() Reference

1. R - Wush WuChih Cheng LiangJohnson Hsieh

2. R - &http://goo.gl/18mwug

3. R - https://goo.gl/NPdzzP

1. DataCamphttps://www.datacamp.com/

2. R for Data Sciencehttp://r4ds.had.co.nz/

R

Jared P. Lander

() Reference

Taiwan R User Grouphttps://www.facebook.com/Tw.R.User/

https://www.facebook.com/twdsconf/

/ Data Visualizationhttps://www.facebook.com/data.visualize/

() Reference

Q & A