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R语言数据可视化---交互式图表recharts包

2018-01-29 11:28 489 查看
知乎专栏:https://www.zhihu.com/people/wu-shu-hao-67/activities 

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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 <- airquality
aq$Date <- as.Date(paste('1973', aq$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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