1.plotly包

动态散点图

library(plotly)

# 交互散点图
plot_ly(data=iris,
         x=~Sepal.Length,
         y=~Petal.Length,
         marker=list(size=10,
                     color='rgba(255,182,193,.9)',
                     line=list(color='rgba(152,0,0,.8)',
                               width=2))) %>% 
  layout(title='Styled Scatter',
         yaxis=list(zeroline=FALSE),
         xaxis=list(zeroline=FALSE))

#多维数据，添加标签
plot_ly(mpg,x=~hwy,y=~displ,color=~factor(cyl),
        text=~paste('Model:',model)) %>% 
  layout(title='MPG data',font=list(family='Times New Roman',
                                    size=13,color='forestgreen'))


#参数
plot_ly(data=iris,x=~Sepal.Length,y=~Petal.Length,
        type = 'scatter',#lines/markers/text/none
        mode='makers',
        symbol = ~Species,
        #点类型
        symbols = c('circle','x','o'),color = I('black'),
        marker=list(size=10))

#点连线形式
trace0 <- rnorm(100,mean=5)
trace1 <- rnorm(100,mean=0)
trace2 <- rnorm(100,mean=-5)
x <- c(1:100)
data <- data.frame(x,trace0,trace1,trace2)

#第一张散点图以线图形式展示
plot_ly(data,x=~x,y=~trace0,
        name = 'trace 0',type = 'scatter',
        mode='lines') %>%  
  #第二张以点连线形式展示
  add_trace(y=~trace1,name='trace 1',
            mode='lines+markers') %>% 
  #第三张普通散点图
  add_trace(y=~trace2,name='trace 2',
            mode='markers') %>% 
  layout(xaxis=list(zeroline=FALSE))

#add_trace/add_histogram/add_boxplot/add_text

其他动态图

#动态气泡图
# 动态线图 
# 动态条形图
# 动态直方图
# 动态盒形图
# 动态误差条图
# 动态饼图和戒指图

2. recharts包

接近基础绘图语法。

散点图

#devtools::install_github('taiyun/recharts')
library(recharts)

#散点图
ePoints(iris[,3:5],series = ~Species)

ePoints(iris[,3:5],
        xvar=~Petal.Length,
        yvar=~Petal.Width,
        series = ~Species,
        xlab.name = 'Petal Length',
        ylab.name = 'Petal Width',
        xlab.namePosition = 'end',
        ylab.namePosition = 'end',
        title = 'IRIS data',
        title.x = 'center',
        title.y = 'top',
        legend.orient = 'vertical',
        legend.x = 'right',
        legend.y = 'center')

其他动态图

#线图
names(mtcars)
eLine(mtcars,xvar = ~cyl,yvar = ~mpg,series = ~gear)

#条形图
eBar(mtcars,xvar = ~cyl,yvar = ~mpg,series = ~gear)

#饼图
x=runif(6)
names(x)=LETTERS[1:6]
ePie(x,type='pie',title = 'PIE')
#玫瑰图
ePie(x,type = 'rose',roseType = 'radias',title = 'Rose plot')

#雷达图
eRadar(mtcars,xvar = ~cyl,yvar = ~mpg,series = ~gear)

#漏斗图、面积图等。。。

3. rChart包

语法近似于lattice绘图系统。在R中实现Polychart、Morris、NVD3等多个js绘图库。
https://github.com/ramnathv/rCharts
没安装上

Ploychart

4.threejs包

3D显示功能。

#install.packages('threejs')
library(threejs)

#三维散点图
N <- 100
i <- sample(3,N,replace = TRUE)
x <- matrix(rnorm(N*3),ncol=3)
lab <- c('small','bigger','biggest')
scatterplot3js(x,color = rainbow(N),labels=lab[i],
               size=i,renderer = "canvas")

#三维地图
library(maps)
data("world.cities",package = 'maps')
cities <- world.cities[order(world.cities$pop,decreasing = TRUE)[1:1000],]
value <- 100*cities$pop/max(cities$pop)
col <- colorRampPalette(c('cyan','lightgreen'))(10)[floor(10*value/100)+1]
threejs::globejs(lat = cities$lat,
                 long=cities$long,
                 value=value,
                 color = col,
                 atmosphere = TRUE)

5.timevis包

#绘制动态时间轴，展示时间节点事件
library(timevis)
timevis(data.frame(id=1:3,
                   content=c('one','two','three'),
                   start=c('2016-01-10','2016-01-14','2016-01-19'),
                   end=c(NA,'2016-01-18',NA),
                   type=c('point','background','box')))

6.dygraphs包

#动态时间序列
library(dygraphs)
lungDeaths <- cbind(mdeaths,fdeaths)
dygraph(lungDeaths)
#选择特定时间
dygraph(lungDeaths) %>% 
  dyRangeSelector(dateWindow = c('1975-06-01','1978-12-31'))

7.leaflet包

js开源交互式地图包，在R中利用哦html5显示。

#install.packages('leaflet')
library(leaflet)

f <- leaflet() #初始化
y <- addTiles(f) #调用地图底图
addMarkers(y,
           lng = 121.445,
           lat=31.1980,
           popup = '复旦大学上海医学院') #添加标记

#用管道符
leaflet() %>% addTiles() %>% 
  addMarkers(lng = 121.445,lat = 31.1980,popup = '复旦大学医学院')

功能强大，不再演示。