对于上面的例子,函数可能是这样的:discrete_distr_data<-function(x){ tibble::tibble( value=names(x), probability=as.numeric(x) ) } discrete_distr_data(mpg_drv_dist) #>#Atibble:3x2 #>valueprobability #><chr><dbl> #>140.440 #>2f0.453 #>3r0.107 通常,plot()的使用者调用它是为了它的副作...
mpg_drv_summary<-function(){ggplot(ggplot2::mpg)+geom_bar(aes(x=.data$drv))+coord_flip()} 如果你的列名是字符串向量(例如,col = "drv"),使用.data[[col]]这种方式: 代码语言:javascript 复制 col_summary<-function(df,col){ggplot(df)+geom_bar(aes(x=.data[[col]]))+coord_flip()}col_...
If you’d like to take an online course, tryData Visualization in R With ggplot2by Kara Woo. If you’d like to follow a webinar, tryPlotting Anything with ggplot2by Thomas Lin Pedersen. If you want to dive into making common graphics as quickly as possible, I recommendThe R Graphics ...
(p0 <- ggplot(data.frame(x = c(-6,6)), aes(x = x)) + stat_function(fun = dt, args = list(df = 18), geom = "line", linewidth = 0.4) + labs(tag = "p0", x = expression(t[0]), y = "Probability Density", caption = "R_ggplot绘图:基础技能(1)-绘制第二坐标轴", tit...
另一种就是高大上的R包ggplot了,其实这个在技能树也是有教程ggplot-in-R 的,但是大神不喜欢注释,还是需要bioplanet学习小组的协助啦,好了,废话不多说,开始练习。 首先看到教程这么写“据框是变量(列)和观测(行)的矩形集合。mpg是ggplot2的内置数据框。”,然后我就打开一个R.proj,输入mgp先查看数据情况 ...
An implementation of the Grammar of Graphics in R. Contribute to tidyverse/ggplot2 development by creating an account on GitHub.
ggplot(data=<DATA>,mapping=aes(<MAPPINGS>))+<GEOM_FUNCTION>(mapping=aes(<MAPPINGS>),stat=<STAT>,position=<POSITION>)+<SCALE_FUNCTION>+<COORDINATE_FUNCTION>+<FACET_FUNCTION>+<THEME_FUNCTION> 3.1.2 数据、映射、几何对象 数据(data) 数据:用于绘图的数据,需要是整洁的数据框。本节用 ggplot2 自带...
我们通过调用前面的函数将欧洲河流 shapefile 读入 R 中,以获取要导入的文件列表。然后,我们将st_read应用于它并检索列表对象。由于我们想要 sf 对象,因此获取列表的第一个组件就足够了,我们的愿望将得到满足。 代码语言:javascript 复制 get_rivers<-function(filenames,list_riv,eu_riv){filenames<-get_data(...
Each type of geom accepts only a subset of all aesthetics-refer to the geom help pages to see what mappings each geom accepts. Aesthetic mappings are set with the aes() function. Scale scales map values in the data space to values in the aesthetic space(color, size, shape ...). scales...
dunn.test(Figure_2b$Value, g = Figure_2b$Group, method = "sidak")# 计算不同组的均数和标准差# 自定义函数data_summary <-function(data, varname, groupnames){require(plyr)summary_func <-function(x, col){c(mean = mea...