AI代码解释 p3<-ggscatter(mydf,x="DPS",y="ISG",add="reg.line",conf.int=T)+labs(y="Mean ISG module score",x="Days post-symptom onset") 添加相关系数和p值 代码语言:javascript 代码运行次数:0 运行 AI代码解释 p4<-ggscatter(mydf,x="DPS",y="ISG",add="reg.line",conf.int=T)+labs...
p14 <- ggbarplot(df3, x = "dose", y = "len", add = "mean_se", error.plot = "upper_errorbar") p14 1 2 3 4 # Change error.plot to "pointrange" p15 <- ggbarplot(df3, x = "dose", y = "len", add = "mean_s...
Display the result of a linear model and its confidence interval on top of a scatterplot. A ggplot2 implementation with reproducible code. Scatter section About scatter Linear trend Adding a linear trend to a scatterplot helps the reader in seeing patterns. ggplot2 provides the geom_smooth() ...
- scatter plots (geom_point()) and jittered scatter plot (geom_jitter())- lines (geom_line())- confidence intervals (geom_interval())- bars plots (geom_bar())- raster plots (geom_raster())- point counts (point_count()) - Multiple ways of plotting statistical visualizations of the ...
R语言中ggplot函数系统中涉及到线条的地方有很多，最常见的场景就是我们做geom_line()（折线图）、geom...
小提琴图(Violin Plot)用于显示数据分布及其概率密度,因其形状酷似小提琴而得名。 图1 小提琴图示例 这种图表结合了箱线图和密度图的特征,主要用来显示数据的分布形状。中间的黑色粗条表示四分位数范围,从其延伸的幼细黑线代表95% 置信区间,而白点则为中位数。如果需要,中间的箱线图还可以替换为误差条图。
geom_density(alpha=.2, fill="#FF6666") # Overlay with transparent density plot 3.5、直方图添加均值线 ggplot(dat, aes(x=rating)) + geom_histogram(binwidth=.5, colour="black", fill="white") + geom_vline(aes(xintercept=mean(rating, na.rm=T)), # Ignore NA values for mean ...
# Confidence interval multiplier for standard error # Calculate t-statistic for confidence interval: # e.g., if conf.interval is .95, use .975 (above/below), and use df=N-1 ciMult <- qt(conf.interval/2 + .5, datac$N-1)
ggtitle("Scatter Plot of wt and mpg") #添加曲线拟合 ggplot(mtcars,aes(x=wt,y=mpg)) + geom_point() + geom_smooth(method=lm,se=FALSE) + ggtitle("Line of Best Fit with no Confidence Interval") #添加置信区间 ggplot(mtcars,aes(x=wt,y=mpg)) + geom_point() + geom_smooth(method=lm...
在主题设置中,rect设置主要用于设置图例和面板 element_rect(fill = NULL, colour = NULL, size = NULL, linetype = NULL, color = NULL) 参数也相对简单,基本上是常用的参数,从设置来看,灵活性还是很高的. 下面看些例子: library(ggplot2) p<-ggplot(mtcars,aes(mpg,hp,colour=factor(cyl)))+geom_point...