数据可视化能够很好地展示我们数据分析的结果,对于平常工作中,一份酷炫的可视化图表也能成为我们在工作汇报时的加分项,可是很多小伙伴对于怎样制作吸引人眼球可视化图表却不知晓,今天小编终于为大家找到了集中好看的力导向图,桑基图、树图、弦图的制作方法,特来分享给大家。
以下文章来源于: AI入门学习公众号
作者:伍正祥
给大家分享4种很厉害的图,基于R语言networkD3包实现,学会了可以大大提高可视化水平,R语言实现非常简单,几行代码就搞定,先看图。
1、力导向图(force Network)
2、桑基图(Sankey diagrams)
3、辐射状网络图(Radial networks)
4、弦图(chord Diagram)
下面一步步实现其中的每个图
#工作空间设置
setwd("C:/Users/wuzhengxiang/Desktop/networkD3")
#包加载
library(networkD3)
#http://christophergandrud.github.io/networkD3/#simple
1、力导向图(force Network)
1)简单网络图
#创建数据
src = c("A", "A", "A", "A", "B", "B", "C", "C", "D",'I')
target = c("B", "C", "D", "J", "E", "F", "G", "H", "I",'A')
networkData = data.frame(src, target)
#直接一个函数即可画出简单图,下面第一个图
simpleNetwork(networkData)
#换个颜色和字体大小,下面第二个图
simpleNetwork(networkData,nodeColour = "#FF69B4",fontSize = 12)
2)复杂网络图
#载入数据
data(MisLinks)
data(MisNodes)
#创建一个简单的力图
forceNetwork(Links = MisLinks, Nodes = MisNodes, Source = "source", Target = "target", Value = "value", NodeID = "name",Group = "group", opacity = 1, zoom = F, bounded = T)
# 当鼠标点击变大大的图
MyClickScript = 'd3.select(this).select("circle").transition().duration(750).attr("r", 30)'
forceNetwork(Links = MisLinks, Nodes = MisNodes, Source = "source",Target = "target", Value = "value", NodeID = "name",Group = "group", opacity = 1, zoom = F, bounded = T,
clickAction = MyClickScript)
# 节点大小赋值
forceNetwork(Links = MisLinks, Nodes = MisNodes, Source = "source",Target = "target", Value = "value", NodeID = "name", Nodesize = 'size', radiusCalculation = "d.nodesize",
Group = "group", opacity = 1, legend = T, bounded = F)
2、桑基图(Sankey diagrams)
URL <- 'https://raw.githubusercontent.com/christophergandrud/d3Network/sankey/JSONdata/energy.json'
Energy <- jsonlite::fromJSON(URL)
# Plot
sankeyNetwork(Links = Energy$links, Nodes = Energy$nodes, Source = "source",Target = "target", Value = "value", NodeID = "name",fontSize = 12, nodeWidth = 30 )
#动态
#静态
3、树状图 (Tree networks)
1)radialNetwork
Flare <- jsonlite::fromJSON(
"https://gist.githubusercontent.com/mbostock/4063550/raw/a05a94858375bd0ae023f6950a2b13fac5127637/flare.json",simplifyDataFrame = FALSE)
hc <- hclust(dist(USArrests), "ave")
radialNetwork(List = Flare, fontSize = 10, opacity = 0.9, margin=0)
radialNetwork(as.radialNetwork(hc))
2)其他类型的树图(不会翻译,弯的树图?)
diagonalNetwork(List = Flare, fontSize = 10, opacity = 0.9, margin=0)
diagonalNetwork(as.radialNetwork(hc), height = 700, margin = 50)
3)dendroNetwork(不会翻译,直的树图?)
hc <- hclust(dist(USArrests), "ave")
dendroNetwork(hc, height = 600)
dendroNetwork(hc, treeOrientation = "vertical")
dendroNetwork(hc, height = 600, linkType = "diagonal")
dendroNetwork(hc, treeOrientation = "vertical", linkType = "diagonal")
dendroNetwork(hc, textColour = c("red", "green", "orange")[cutree(hc, 3)],height = 600)
dendroNetwork(hc, textColour = c("red", "green", "orange")[cutree(hc, 3)], treeOrientation = "vertical")
4、弦图(chordDiagram)
hairColourData = matrix(c(11975, 1951, 8010, 1013,5871, 10048, 16145, 990,8916, 2060, 8090, 940, 2868, 6171, 8045, 6907), nrow = 4)
chordNetwork(hairColourData, width = 500, height = 500,colourScale = c("#000000", "#FFDD89", "#957244", "#F26223"))
#保存为html文件saveNetwork
library(magrittr)
simpleNetwork(networkData) %>% saveNetwork(file = 'Net1.html')
forceNetwork(Links = MisLinks, Nodes = MisNodes, Source = "source",Target = "target", Value = "value", NodeID = "name",Nodesize = 'size', radiusCalculation = " Math.sqrt(d.nodesize)+6",Group = "group", opacity = 1, legend = T, bounded = T) %>%
saveNetwork(file = 'forceNetwork_01.html')