AI代码解释 ibrary(ggplot2)ggplot(df,aes(x=year,y=auth_num,col=journal,fill=journal))+stat_summary(fun.data="mean_cl_boot",geom="ribbon",#width=.2,alpha=I(.5))+stat_summary(fun="mean",geom="line")+labs(x="Year",y="Mean number of authors per paper")+theme_bw()+theme(legend....
ggforceis great for extending ggplot2 with advanced features. But, you’ll need to learnggplot2to take full advantage. For these topics, I’ll use theUltimate R Cheat Sheetto refer toggplot2code in my workflow. Quick Example: Download the Ultimate R Cheat Sheet. ThenClick the “CS” hyper...
To visualize the distribution of a single variable and check if its mean is significantly different from a specified value with a one-sample test, gghistostats() can be used.set.seed(123) gghistostats( data = ggplot2::msleep, x = awake, title = "Amount of time spent awake", test....
A website that displays hundreds of R charts with their code - R-graph-gallery/95-violin-plot-with-ggplot2.html at cc85d0c4b016d9f7245df690da2b4619d1db739e · klao-thongchan/R-graph-gallery
library(ggplot2) ggplot(df, aes(x = depth, y = color, fill = stat(quantile))) + stat_density_ridges(quantile_lines = FALSE, calc_ecdf = TRUE, geom = "density_ridges_gradient") + scale_fill_brewer(name = "") Highlight the tails of the distribution ...
Here, the numeric variable calledcaratfrom thediamondsdataset in cut in 0.5 length bins thanks to thecut_widthfunction. Then, we just need to provide the newly created variable to the X axis ofggplot2. # librarylibrary(ggplot2)library(dplyr)library(hrbrthemes)# Start with the diamonds dataset...
A boxplot summarizes the distribution of a continuous variable. Different color scales can be apply to it, and this post describes how to do so using the ggplot2 library. It is notably described how to highlight a specific group of interest. ...
This article shows how to create density plots using the ggplot2 R package. A density plot is an alternative to Histogram for visualizing distribution.
ggstatsplot包是ggplot2包的扩展,其中包含来自信息丰富的图表本身的统计测试的详细信息。 在典型的探索性数据分析工作流程中,数据可视化和统计建模是两个不同的阶段:可视化为建模提供信息,而建模反过来可以使用不同的可视化方法。ggstatsplot的中心思想就是将这两个阶段以带有统计细节的图形形式合二为一,使数据探索更简...
for(i in 2:ncol(data)) { # Printing ggplot within for-loop print(ggplot(data, aes(x = x, y = data[ , i])) + geom_point()) Sys.sleep(2) }Figure 2: Showing ggplot2 Plots within for-Loop using print() Function.After running the previous R code, you will see three ggplot2 ...