# library library(ggplot2) # create a data frame variety=rep(LETTERS[1:7], each=40) treatment=rep(c("high","low"),each=20) note=seq(1:280)+sample(1:150, 280, replace=T) data=data.frame(variety, treatment , note)
library(ggplot2)library(gridExtra)library(gapminder)library(dplyr)p5<-ggplot(gapminder,aes(x=continent,y=lifeExp,fill=continent))+facet_wrap(~year)+geom_boxplot()+scale_y_continuous(name="Average Life Expectancy")+scale_x_discrete(labels=abbreviate,name="Continent")p5 ...
A website that displays hundreds of R charts with their code - R-graph-gallery/violin_grouped_ggplot2.html at cc85d0c4b016d9f7245df690da2b4619d1db739e · klao-thongchan/R-graph-gallery
The ggplot2 function scale_y_continuous(expand = expansion(mult = c(0, 0.1))) is used to add more spaces between labels and the plot top border # Box plots with p-values stat.test <- stat.test %>% add_xy_position(x = "supp", dodge = 0.8) bxp + stat_pvalue_manual( stat.test...
In this section, we’ll show to plot a grouped continuous variable using box plot, violin plot, strip chart and alternatives. We’ll also describe how to add automatically p-values comparing groups. In this section, we’ll set the theme theme_bw() as the default ggplot theme:...
(dpi = 300) # Plot p <- ggplot(data = df, aes(x = Jahr, y = AntBev, fill = reorder(Bildungsstand, -rang))) + geom_bar(stat = "identity", position = position_dodge(width = 0.7), width = 0.6) + geom_errorbar(aes(x = Jahr, ymin = untAntBevKI, ymax = obAntBevKI), ...
library(ggpubr) library(rstatix) # Transform `dose` into factor variable df <- ToothGrowth df$dose <- as.factor(df$dose) head(df, 3) # Box plots bxp <- ggboxplot( df, x = "supp", y = "len", fill = "dose", palette = "npg" ) bxp 1 2 3 4 5 6 7 8 9 10 11 12...
ggplot(ToothGrowth, aes(x = supp, y = len, fill = supp)) + geom_boxplot() + geom_jitter(width = 0.2, alpha = 0.5) + labs( title = "Tooth Growth Analysis", x = "Supplement", y = "Tooth Length" ) + theme(legend.position = "none") ...
It wasn’t as easyfor me as the plot function but ggplot is quite versatile and probably a goodpackage to have in your back pocket for complicated graphing. Next up was the gplots package for theplotCI function. > library(gplots) > > plotCI( + x = refmCount$mo.yr, + y = refm...
The ggplot2 function scale_y_continuous(expand = expansion(mult = c(0, 0.1))) is used to add more spaces between labels and the plot top border # Box plots with p-values stat.test <- stat.test %>% add_xy_position(x = "supp", dodge = 0.8) bxp + stat_pvalue_manual( ...