ggplot2包中绘制点图的函数有两个:geom_point和 geom_dotplot,当使用geom_dotplot绘图时,point的形状是dot,不能改变点的形状,因此,geom_dotplot 叫做散点图(Scatter Plot),通过绘制点来呈现数据的分布,对点分箱的方法有两种:点密度(dot-density )和直方点(histodot)。当使用点密度分箱(bin)方式时,分箱的位...
ggplot2包中绘制点图的函数有两个:geom_point和 geom_dotplot,当使用geom_dotplot绘图时,point的形状是dot,不能改变点的形状,因此,geom_dotplot 叫做散点图(Scatter Plot),通过绘制点来呈现数据的分布,对点分箱的方法有两种:点密度(dot-density )和直方点(histodot)。当使用点密度分箱(bin)方式时,分箱的位...
3、{ggblanket}将ggplot2包中的col和fill参数合并到一个col参数中,通过col参数控制图形颜色填充: penguins %>% gg_histogram( x = body_mass_g, col = species) 4、{ggblanket}通过pal和alpha参数实现自定义颜色和其透明度: penguins %>% mutate(sex = stringr::str_to_sentence(sex)) %>% group_by(s...
ggplot(birthwt,aes(x=bwt,fill=smoke))+ geom_histogram(position = 'identity',alpha=0.4) #3.2.2 使用分面 #各声部歌手身高的分布,根据voice.part因子水平进行颜色填充 p414 #str(singer) data(singer,package='lattice') ggplot(singer,aes(x=height,fill=voice.part))+ geom_histogram()+ facet_wrap(...
library(ggpubr)#> Loading required package: ggplot2#> Loading required package: magrittr# Create some data format# :::set.seed(1234)wdata = data.frame( sex = factor(rep(c("F", "M"), each=200)), weight = c(rnorm(200, 55), rnorm(200, 58)))head(wdata, 4)#> sex ...
ggplot(mapping = aes(x = num %>% factor(), # num转化为因子变量,横坐标变为离散数据 y = value, col = type, fill = type, # 为geom_col group = type)) + # 为geom_line scale_x_discrete("type_month", labels = a$type_month) # 用融合后的字符向量覆盖原刻度标签 ...
ggplot() + geom_boxplot( aes( x = .panel_x, y = .panel_y, fill = island, group = interaction(.panel_x, island) ) ) + facet_matrix( cols = vars(sex, species), rows = vars(bill_depth_mm:body_mass_g) ) 结果图 03
Histogram plots Empirical cumulative density function Quantile - Quantile plot library(ggpubr)set.seed(1234)wdata=data.frame(sex=factor(rep(c("F","M"),each=200)),weight=c(rnorm(200,55),rnorm(200,58)))#200个随机数,平均数是55head(wdata,4)# sex weight#1 F 53.79293#2 F 55.27743#3 ...
下面是一个简单的画直方图的例子,使用的是R中的ggplot()和geom_histogram()函数。 ggplot(train, aes(Item_MRP)) + geom_histogram(binwidth = 2)+scale_x_continuous("Item MRP", breaks = seq(0,270,by = 30))+scale_y_continuous("Count", breaks = seq(0,200,by = 20))+labs(title = "His...
p3<-ggplot(data=dat01,aes(x=`Variance Explained`*100))+geom_histogram(bins=30,color="black",fill="grey")+scale_x_continuous(breaks=seq(0,0.006,by=0.001))+scale_y_continuous(breaks=seq(0,6000,by=2000))+theme_classic()+guides(x=guide_axis_truncated(trunc_lower=0,trunc_upper=0.006),...