1. 載入軟件包這里使用R語言的 library(ggplot2)library(data.table)2. 生成模擬數(shù)據(jù)生成示例數(shù)據(jù) library(data.table)library(ggplot2)dat <- data.table(Spring = c(runif(9,0,1),2), Summer = runif(10,0,1), Autumn = runif(10,0,1), Winter = runif(10,0,1))dat1 = melt(dat)數(shù)據(jù)如下: variable value 1: Spring 0.35080952 2: Spring 0.54117242 3: Spring 0.57099138 4: Spring 0.69833364 5: Spring 0.17191075 6: Spring 0.63691289 7: Spring 0.40214424 8: Spring 0.97314831 9: Spring 0.8395677810: Spring 2.0000000011: Summer 0.4784080412: Summer 0.7955413513: Summer 0.1592947614: Summer 0.4545910615: Summer 0.3667024316: Summer 0.0221140317: Summer 0.2891866318: Summer 0.6383328919: Summer 0.8030753920: Summer 0.8959408021: Autumn 0.9084373322: Autumn 0.4316380123: Autumn 0.2539882524: Autumn 0.6649632625: Autumn 0.2947191326: Autumn 0.5718252827: Autumn 0.5199808628: Autumn 0.4803617029: Autumn 0.3576327830: Autumn 0.3607939431: Winter 0.5030135232: Winter 0.8036745433: Winter 0.9226086134: Winter 0.2509871735: Winter 0.6701092236: Winter 0.8158710937: Winter 0.1694603138: Winter 0.4186841639: Winter 0.0333325640: Winter 0.40031857 variable value注意， 這里data.table的melt函數(shù)，完全可以代替reshape2的melt函數(shù)，速度更快。3. 生成分組箱線圖要點
為不同的箱線圖添加顏色 ggplot(data=dat1,aes(x=variable,y=value,colour=variable)) +geom_boxplot()近期熱文： 2019年統(tǒng)計遺傳學(xué)暑期學(xué)校通知 |
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來自： 育種數(shù)據(jù)分析 > 《待分類》
