library(plotly) df <- data.frame(trt = c("a", "b", "c"), outcome = c(2.3, 1.9, 3.2)) p <- ggplot(df, aes(trt, outcome)) + geom_point() ggplotly(p) You can also use geom_bar() with continuous data, in which case
ggplot2.barplot is a function, to plot easily bar graphs using R software and ggplot2 plotting methods. This function is from easyGgplot2 package. An R script is available in the next section to install the package. The aim of this tutorial is to show you step by step, how to plot an...
Bar graphs Line graphs Finished examples With a numeric x-axis With x-axis treated as continuous With x-axis treated as categoricalProblemYou want to do make basic bar or line graphs.SolutionTo make graphs with ggplot2, the data must be in a data frame, and in “long” (as opposed to...
Stacked Bar ChartThe general plots of bar graphs and histogram can be created as below −> p <- ggplot(mpg, aes(class)) > p + geom_bar() > p + geom_bar() This plot includes all the categories defined in bar graphs with respective class. This plot is called stacked graph....
首先,我们需要了解ggplot2是一个基于R语言的绘图库,它可以帮助我们轻松地创建高质量的图形。geom_bar是ggplot2中的一个几何对象,用于创建条形图。 在ggplot2中,我们可以使用geom_bar来创建一个条形图,并使用scale_x_continuous和scale_y_continuous函数来限制图形的轴范围。
R Graphics Cookbook 第3章 – Bar Graphs 3.1 基本条形图 library(ggplot2) library(gcookbook) pg_mean #这是用到的数据 group weight 1 ctrl 5.032 2 trt1 4.661 3 trt2 5.526 ggplot(pg_mean, aes(x=group, y=weight)) + geom_bar(stat="identity") x轴是连续变量还是因子,画出的图有所不同,...
在ggplot2中,geom_bar函数用于创建柱状图。当我们使用geom_bar函数时,可以通过重新排序分解后的计数数据来改变柱状图的顺序。 重新排序分解后的计数数据可以通过对数据框进行排序来实现...
ggplot(diamonds, aes(x=price)) + geom_bar(stat="bin") 这时最好用geom_histogram(): ggplot(diamonds, aes(x=price)) + geom_histogram() 3.4. Using Colors in a Bar Graph 把计步数据用指定的颜色填充。这里只有11个月,所以造了11种颜色。
color = dose,ymin = len,ymax = len+sd),width = 0.2)多重分组的Error bar f <-ggplot(df3, aes(x = dose,y = len))# 柱状图+Errorbarf +geom_errorbar(aes(color = supp,ymin = len-sd,ymax = len+sd),position = "dodge")+ geom_bar(aes(fill = supp),stat = "identity",...
1. 对数值进行排序 require(plyr)# Sort by dose and suppdf_sorted <- arrange(df2, dose, supp)head(df_sorted)2. 分别计算Y轴数值的和 df_cumsum <- ddply(df_sorted, "dose", transform, label_ypos=cumsum(len))head(df_cumsum)3. 画图 ggplot(data=df_cumsum, aes(x = dose, y = len...