多系列数据核密度图

ggridges包提供了geom_density_ridges_gradient()函数，用于画核密度估计峰峦图

1数据结构

这里我们用到的是ggridges内了数据lincoln_weather，该数据是关于每个月各种天气指标，包括温度湿度等等，其中我们要用到的两列为平均温度mt和月份mon,这是我简化后的数据，便于展示

与单数据系列不同的是这里要提供两个变量，x轴对应温度，即统计变量，y轴为分类变量

2绘制峰峦图代码

library(ggplot2)

library(ggridges)

library(RColorBrewer)

ggplot(lincoln_weather, aes(x = `Mean Temperature [F]`, y = `Month`, fill = ..density..)) + # ..density.. 指按照计算出来的density填充颜色

#rel_min_height：relative to heightest point,指定去掉尾部的范围，一般0.01会比较好

# scale ;The extent to which the different densities overlap can be controlled with the parameter.该参数控制的是密度图之间重叠的程度,值越小越分开，越大月重叠

geom_density_ridges_gradient(scale =3, rel_min_height = 0.00,size = 0.3) +

scale_fill_gradientn(colours = colorRampPalette(rev(brewer.pal(11,'Spectral')))(32))

rel_min_height=0.00

rel_min_height=0.01

scale=1

3 fill = stat(x)根据计算出来的密度大小着色

library(ggplot2)

library(ggridges)

library(RColorBrewer)

ggplot(lincoln_weather, aes(x = `Mean Temperature [F]`, y = `Month`, fill = stat(x)) + # 指定按照x轴大小填充

geom_density_ridges_gradient(scale =3, rel_min_height = 0.00,size = 0.3) +

scale_fill_gradientn(colours = colorRampPalette(rev(brewer.pal(11,'Spectral')))(32))

4用stat_density_ridfes()画峰峦图，其实它是geom_density_ridges_gradient所要调用的函数，这里可以用stat参数

library(ggplot2)

library(ggridges)

library(RColorBrewer）

ggplot(lincoln_weather, aes(x = `Mean Temperature [F]`, y = `Month`, fill = factor(stat(quantile)))) +

stat_density_ridges(

geom = "density_ridges_gradient",

calc_ecdf = TRUE,

quantiles = c(0.025, 0.975)

) +

scale_fill_manual(

name = "Probability", values = c("#FF0000A0", "#A0A0A0A0", "#0000FFA0"),

labels = c("(0, 0.025]", "(0.025, 0.975]", "(0.975, 1]")

)

5用stat中计算的累积概率值填色

library(ggplot2)

library(ggridges)

library(RColorBrewer)

panel_scaling = T

ggplot(lincoln_weather, aes(x = `Mean Temperature [F]`, y = `Month`, fill = 0.5-abs(0.5-stat(ecdf)))) +

# fill = 0.5-abs(0.5-stat(ecdf)))图形在累积概率达到50%颜色最深，并且两边颜色对称

stat_density_ridges(

geom = "density_ridges_gradient",

calc_ecdf = TRUE

) +

scale_fill_viridis_c(

name = "Probability", direction=-1)

6jittered_point绘制带点的概率分布图

library(ggplot2)

library(ggridges)

library(RColorBrewer)

panel_scaling = T

ggplot(lincoln_weather, aes(x = `Mean Temperature [F]`, y = `Month`, fill = 0.5-abs(0.5-stat(ecdf)))) +

stat_density_ridges(

geom = "density_ridges_gradient",

calc_ecdf = TRUE,

jittered_points = T,

point_size=0.5,

point_shape=19

) +

scale_fill_viridis_c(

name = "Probability", direction=-1)