數(shù)據(jù)可視化能夠很好地展示我們數(shù)據(jù)分析的結果，對于平常工作中，一份酷炫的可視化圖表也能成為我們在工作匯報時的加分項，可是很多小伙伴對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向圖，?；鶊D、樹圖、弦圖的制作方法，特來分享給大家。

以下文章來源于： AI入門學習公眾號

作者：伍正祥

給大家分享4種很厲害的圖，基于R語言networkD3包實現(xiàn)，學會了可以大大提高可視化水平，R語言實現(xiàn)非常簡單，幾行代碼就搞定，先看圖。

1、力導向圖（force Network）

2、?；鶊D（Sankey diagrams） 

3、輻射狀網(wǎng)絡圖（Radial networks）

4、弦圖（chord Diagram）  

下面一步步實現(xiàn)其中的每個圖

#工作空間設置

setwd("C:/Users/wuzhengxiang/Desktop/networkD3")

#包加載

library(networkD3)

#http://christophergandrud.github.io/networkD3/#simple

1、力導向圖（force Network）

1）簡單網(wǎng)絡圖

#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)

#直接一個函數(shù)即可畫出簡單圖，下面第一個圖

simpleNetwork(networkData)

#換個顏色和字體大小，下面第二個圖

simpleNetwork(networkData,nodeColour = "#FF69B4",fontSize = 12)

2）復雜網(wǎng)絡圖

#載入數(shù)據(jù)

data(MisLinks)

data(MisNodes)

#創(chuàng)建一個簡單的力圖

forceNetwork(Links = MisLinks, Nodes = MisNodes, Source = "source", Target = "target", Value = "value", NodeID = "name",Group = "group", opacity = 1, zoom = F, bounded = T)

# 當鼠標點擊變大大的圖

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 )

#動態(tài)

#靜態(tài)

3、樹狀圖  （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）其他類型的樹圖（不會翻譯，彎的樹圖？）

diagonalNetwork(List = Flare, fontSize = 10, opacity = 0.9, margin=0)

diagonalNetwork(as.radialNetwork(hc), height = 700, margin = 50)

3）dendroNetwork（不會翻譯，直的樹圖？）

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')