虛擬貨幣分析
擷取2016/01/01到2017/12/20的三個虛擬貨幣資訊 分別是ether,bitcoin,ripple
將三種貨幣的價格作為折線圖資料(合併)
ggplot(my.df, aes(x = x)) +
geom_line(aes(y = y1)) +
geom_line(aes(y = y2)) +
geom_line(aes(y = y3))
因為發現價格差距過大,無法從圖片中看出同時的漲跌狀況,因此改為分開來看
xyplot(x=y1~x ,
data=data,
panel=function(x,y){
panel.fill(col="black")
panel.xyplot(x, y)
panel.lmline(x, y, col="red")
}
)
xyplot(x=y2~x ,
data=data,
panel=function(x,y){
panel.fill(col="black")
panel.xyplot(x, y)
panel.lmline(x, y, col="red")
}
)
xyplot(x=y3~x ,
data=data,
panel=function(x,y){
panel.fill(col="black")
panel.xyplot(x, y)
panel.lmline(x, y, col="red")
}
)
從以上3張圖可以清楚看到在400以前幾乎沒有起伏2017/02/03
因此以下將從400天之後開始分析
x1=data$num[c(400:720)]
y4=data$ether[c(400:720)]
y5=data$bitcoin[c(400:720)]
y6=data$ripple[c(400:720)]
my.df2 <- data.frame(y4,y5,y6)
ggplot(my.df2, aes(x = x1)) +
geom_line(aes(y = y4)) +
geom_line(aes(y = y5)) +
geom_line(aes(y = y6))
xyplot(x=y4~x1 ,
data=data,
panel=function(x,y){
panel.fill(col="black")
panel.xyplot(x, y)
panel.lmline(x, y, col="red")
}
)
xyplot(x=y5~x1 ,
data=data,
panel=function(x,y){
panel.fill(col="black")
panel.xyplot(x, y)
panel.lmline(x, y, col="red")
}
)
xyplot(x=y6~x1 ,
data=data,
panel=function(x,y){
panel.fill(col="black")
panel.xyplot(x, y)
panel.lmline(x, y, col="red")
}
)
後續發展只有ether持續往上漲,其他2個皆有下滑的趨勢
蒐集新聞資料
從Factiva.com 道瓊社及路透社新聞資料庫 關鍵字:china；USA；america 2017年 6/277/16 9/59/14 選擇網路新聞資料
匯入資料並做成文字雲
coin = readLines("remove.txt")
docs = Corpus(VectorSource(coin))
docs <- tm_map(docs, removeWords, stopwords("english"))
a = c("the","com","can","journal","can","morning","china","new","daily","sign","follow","newsletter","good","download","chinese","letter")
docs1<- tm_map(docs, removeWords,a)
docs <- tm_map(docs,removeWords,"shares")
docs <- tm_map(docs,removeWords,"week")
docs <- tm_map(docs,removeWords,"will")
docs <- tm_map(docs,removeWords,"get")
wordcloud(docs1,
scale=c(5,0.1),min.freq=10,max.words=150,
random.order=TRUE, random.color=FALSE,
rot.per=.1, colors=brewer.pal(8, "Dark2"),
ordered.colors=FALSE,use.r.layout=FALSE,
fixed.asp=TRUE)## Warning in wordcloud(docs1, scale = c(5, 0.1), min.freq = 10, max.words =
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