3dscatter

1.ggplot2畫三維點(diǎn)圖

很輕松找到了R包，然鵝不是很完美的樣子。

#devtools::install_github("AckerDWM/gg3D")library("gg3D") library(ggplot2)data(iris) ggplot(iris, aes(x=Petal.Width, y=Sepal.Width, z=Petal.Length, color=Species)) + theme_void() +axes_3D() +stat_3D()

2.scatterplot3d

一個不屬于ggplot2體系的特立獨(dú)行的R包，畫起來還算簡單。

參數(shù)pch表示形狀，不同形狀可以以數(shù)字1-24來代表。顏色的指定不支持映射，只能是把每個點(diǎn)的顏色設(shè)置好，傳遞給color參數(shù)。圖例需要單獨(dú)畫，不能自動生成，但最終出土的顏值我還是喜歡的。sthda上面也有關(guān)于這個包的漂亮代碼：?http://www.sthda.com/english/wiki/scatterplot3d-3d-graphics-r-software-and-data-visualization

#install.packages("scatterplot3d") library(scatterplot3d) my_color = c("#66C2A5FF", "#FC8D62FF", "#8DA0CBFF")colors = my_color[as.numeric(iris$Species)]p1 = scatterplot3d(iris[,1:3],color = colors,main="iris",pch = 16)legend(p1$xyz.convert(8.5, 2.5, 5), legend = levels(iris$Species),col = my_color, pch = 16)

p2 = scatterplot3d(iris[,1:3],color = "black",main="iris",pch = 21,bg = colors) legend(p2$xyz.convert(8.5, 2.5, 5),col = "black", legend = levels(iris$Species),pt.bg = my_color, pch = 21)

3.三維PCA圖

PCA已經(jīng)有好幾個可視化的R包啦，把前三個主成分提取出來畫三維點(diǎn)圖也挺好看~

library(FactoMineR) dat = iris[,1:4] dat.pca = PCA(dat,graph = F) a = dat.pca[["ind"]][["coord"]] p3 = scatterplot3d(a[,1:3],color = "black",main="iris",pch = 21,bg = colors) legend("bottom",col = "black", legend = levels(iris$Species),pt.bg = my_color, pch = 21,inset = -0.2, xpd = TRUE, horiz = TRUE)

my_pch = 22:24 pchs = my_pch[as.numeric(iris$Species)]p4 = scatterplot3d(a[,1:3],color = "black",main="iris",pch = pchs,bg = colors) legend("bottom",col = "black", legend = levels(iris$Species),pt.bg = my_color, pch = my_pch,inset = -0.2, xpd = TRUE, horiz = TRUE)

總結(jié)

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