R语言数据可视化—交互式图表recharts包

REmap包的github链接地址：https://github.com/taiyun/recharts几个样例demo：http://xwj.565tech.com/jianshu/recharts/ring.htmlhttp://xwj.565tech.com/jianshu/recharts/dashboard.htmlhttp://xwj.565tech.com/jianshu/recharts/bubble.html
一.安装方式if (!require(devtools)) library(devtools)install_github(“madlogos/recharts”)
二.使用方法：1.散点图/气泡图echartr(iris, x=SepalWidth, y=PetalWidth)多个维度：series控制echartr(iris, x=SepalWidth, y=PetalWidth, series=Species)
气泡图：type:标签控制echartr(iris, SepalWidth, PetalWidth,series = Species, weight=PetalLength, type=’bubble’)

2.管道操作echartr(iris, SepalWidth, PetalWidth, weight=PetalLength) %>%    setDataRange(calculable=TRUE, splitNumber=0, labels=c(‘Big’,’Small’),                 color=c(‘red’, ‘yellow’, ‘green’), valueRange=c(0, 2.5))
3.折线图先改造下内置数据集：aq <- airqualityaq$Date <- as.Date(paste(‘1973′, aq$Month, aq$Day, sep=’-‘))aq$Day <- as.character(aq$Day)aq$Month <- factor(aq$Month, labels=c(“May”, “Jun”, “Jul”, “Aug”, “Sep”))
echartr(aq, Date, Temp, type=’line’) %>%    setTitle(‘NY Temperature May – Sep 1973’) %>% setSymbols(‘none’)
含有分类属性：echartr(aq, Day, Temp, Month, type=’line’) %>%    setTitle(‘NY Temperature May – Sep 1973, by Month’) %>%     setSymbols(’emptycircle’)
带有时间轴（带有动态效果哦~~~）：echartr(aq, Day, Temp, t=Month, type=’line’) %>%    setTitle(‘NY Temperature May – Sep 1973, by Month’) %>%     setSymbols(’emptycircle’)
也可画面积图：type属性控制echartr(aq, Day, Temp, Month, type=’area’, subtype=’stack’) %>%    setTitle(‘NY Temperature May – Sep 1973, by Month’) %>%     setSymbols(’emptycircle’)

4.饼图重构内置数据集titanic <- data.table::melt(apply(Titanic, c(1,4), sum))names(titanic) <- c(‘Class’, ‘Survived’, ‘Count’)knitr::kable(titanic)画饼图，可以和漏斗图切换echartr(titanic, Class, Count, type=’pie’) %>%    setTitle(‘Titanic: N by Cabin Class’)
多个饼图：echartr(titanic, Survived, Count, facet=Class, type=’pie’) %>%    setTitle(‘Titanic: Survival Outcome by Cabin Class’)
环图：echartr(titanic, Survived, Count, facet=Class, type=’ring’) %>%    setTitle(‘Titanic: Survival Outcome by Cabin Class’)
信息图样环图：ds <- data.frame(q=c(‘68% feel good’, ‘29% feel bad’, ‘3% have no feelings’),              a=c(68, 29, 3))g <- echartr(ds, q, a, type=’ring’, subtype=’info’) %>%     setTheme(‘macarons’, width=800, height=600) %>%    setTitle(‘How do you feel?’,’ring_info’,              pos=c(‘center’,’center’, ‘horizontal’))g
南丁格尔玫瑰图：echartr(titanic, Class, Count, facet=Survived, type=’rose’, subtype=’radius’) %>%     setTitle(‘Titanic: Survival Outcome by Cabin Class’)

5.雷达图：重构内置数据集cars = mtcars[c(‘Merc 450SE’,’Merc 450SL’,’Merc 450SLC’),              c(‘mpg’,’disp’,’hp’,’qsec’,’wt’,’drat’)]cars$model <- rownames(cars)cars <- data.table::melt(cars, id.vars=’model’)names(cars) <- c(‘model’, ‘indicator’, ‘Parameter’)knitr::kable(cars)
单个雷达图echartr(cars, indicator, Parameter, model, type=’radar’, sub=’fill’) %>%    setTitle(‘Merc 450SE  vs  450SL  vs  450SLC’)
多个雷达图：echartr(cars, indicator, Parameter, facet=model, type=’radar’) %>%        setTitle(‘Merc 450SE  vs  450SL  vs  450SLC’)

6.比较有趣的dashboard构造一个数据集：data = data.frame(x=rep(c(‘KR/min’, ‘Kph’), 2), y=c(3.3, 56, 9.5, 88),                   z=c(rep(‘t1’, 2), rep(‘t2’, 2)))knitr::kable(data)
echartr(data, x, y, type=’gauge’)多个dashboard：echartr(data, x, y, facet=x, type=’gauge’)带时间轴：echartr(data, x, y, facet=x, t=z, type=’gauge’)


基本上常用的数据图表展示recharts都可以很方便和很酷炫的展示，作者只是挑选了几个比较常用的图表类型做了抛砖迎玉.具体的细节各位可以去查看具体的文档：https://madlogos.github.io/recharts/index_cn.html#-en
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