
數(shù)據(jù)可視化能夠很好地展示我們數(shù)據(jù)分析的結(jié)果,對(duì)于平常工作中,一份酷炫的可視化圖表也能成為我們?cè)诠ぷ鲄R報(bào)時(shí)的加分項(xiàng),可是很多小伙伴對(duì)于怎樣制作吸引人眼球可視化圖表卻不知曉,今天小編終于為大家找到了集中好看的力導(dǎo)向圖,?;鶊D、樹(shù)圖、弦圖的制作方法,特來(lái)分享給大家。
以下文章來(lái)源于: AI入門(mén)學(xué)習(xí)公眾號(hào)
作者:伍正祥
給大家分享4種很厲害的圖,基于R語(yǔ)言networkD3包實(shí)現(xiàn),學(xué)會(huì)了可以大大提高可視化水平,R語(yǔ)言實(shí)現(xiàn)非常簡(jiǎn)單,幾行代碼就搞定,先看圖。
1、力導(dǎo)向圖(force Network)
2、?;鶊D(Sankey diagrams)
3、輻射狀網(wǎng)絡(luò)圖(Radial networks)
4、弦圖(chord Diagram)
下面一步步實(shí)現(xiàn)其中的每個(gè)圖
#工作空間設(shè)置
setwd("C:/Users/wuzhengxiang/Desktop/networkD3")
#包加載
library(networkD3)
#http://christophergandrud.github.io/networkD3/#simple
1、力導(dǎo)向圖(force Network)
1)簡(jiǎn)單網(wǎng)絡(luò)圖
#創(chuàng)建數(shù)據(jù)
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)
#直接一個(gè)函數(shù)即可畫(huà)出簡(jiǎn)單圖,下面第一個(gè)圖
simpleNetwork(networkData)
#換個(gè)顏色和字體大小,下面第二個(gè)圖
simpleNetwork(networkData,nodeColour = "#FF69B4",fontSize = 12)
2)復(fù)雜網(wǎng)絡(luò)圖
#載入數(shù)據(jù)
data(MisLinks)
data(MisNodes)
#創(chuàng)建一個(gè)簡(jiǎn)單的力圖
forceNetwork(Links = MisLinks, Nodes = MisNodes, Source = "source", Target = "target", Value = "value", NodeID = "name",Group = "group", opacity = 1, zoom = F, bounded = T)
# 當(dāng)鼠標(biāo)點(diǎn)擊變大大的圖
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)
# 節(jié)點(diǎn)大小賦值
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、?;鶊D(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 )
#動(dòng)態(tài)
#靜態(tài)
3、樹(shù)狀圖 (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)其他類型的樹(shù)圖(不會(huì)翻譯,彎的樹(shù)圖?)
diagonalNetwork(List = Flare, fontSize = 10, opacity = 0.9, margin=0)
diagonalNetwork(as.radialNetwork(hc), height = 700, margin = 50)
3)dendroNetwork(不會(huì)翻譯,直的樹(shù)圖?)
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、弦圖(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"))
#保存為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')
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