ggplot2是一个用于数据可视化的R语言包,它提供了丰富的绘图功能。在直方图上添加多个垂直线(vline)可以用于标记特定的数值或者阈值。下面是使用ggplot2在直方图上添加多个vline的步骤:...
在ggplot2中,axis.line主题用于控制轴线的绘制。 axis.line主题可以用于以下目的: 轴线的连接:axis.line可以控制轴线是否连接到原点。当axis.line为TRUE时,轴线会连接到原点;当axis.line为FALSE时,轴线不会连接到原点。 axis.line主题的分类: axis.line主题属于ggplot2的图形主题,用于定制轴线的绘制。 axis.line主题...
"none") + scale_fill_manual(values = c(A = "white", B = "red", C = "white", D = "blue"), guide = "none") + geom_errorbar(aes(x = E, ymin = avg-se, ymax = avg+se, color = NULL, linetype = NULL), width=.1, position=position_dodge(width = .1)) ggplotly(p)...
ggplot2提供了多种linetype类型,下面简单介绍一下指定线型的不同方式 一、使用数字或名称直接指定 ggplot2使用数字及字符串预定义好了几种线型,可以直接使用。 0 = "blank" 1 = "solid" 2 = "dashed" 3 = "dotted" 4 = "dotdash" 5 = "longdash" 6 = "twodash" lty <- c("solid", "dashed",...
library(ggplot2)主要函数及参数 • Key functions: geom_line(), geom_step(), geom_path()• Key arguments to customize the plot: alpha, color, linetype and size.绘图数据 df <- data.frame(dose=c("D0.5", "D1", "D2"), len=c(4.2, 10, 29.5))head(df)df2 <- data.frame...
ggplot(economics, aes(x=date)) + geom_line(aes(y = psavert), color = "darkred") + geom_line(aes(y = uempmed), color="steelblue", linetype="twodash") + theme_minimal()require(reshape2)df <- melt(economics[, c("date", "psavert", "uempmed")], id="date")ggplot(df,...
8)Example 7: Add Line Segments to Specific Facets in ggplot2 Facet Plot 9)Video & Further Resources Let’s dive into it: Exemplifying Data, Add-On Packages & Basic Graphic Let’s first create some example data. data<-data.frame(x=1:6,# Create example data framey=c(5,3,4,8,2,3...
ggplot2,R Base | 1 This R graphics tutorial describes how to changeline types in Rfor plots created using either the R base plotting functions or the ggplot2 package. In R base plot functions, the optionsltyandlwdare used to specify the line type and the line width, respectively. In g...
Let’s assume that we want to create a ggplot2 barchart with a line on top, where the bars represent the sample column and the line represents the responses column. In order to use the functions of theggplot2 package, we also need to install and load ggplot2. ...
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") + ...