第四列是数字,用来填充颜色和控制位置 接下来是ggplot2作图代码 install.packages('aplot')library(ggplot2)library(aplot)df<-read.csv('rscu.txt',header=F,stringsAsFactors=F)p1<-ggplot(df,aes(fill=as.character(V4),x=V2,y=V3))+geom_bar(position="stack",stat="identity")+theme_bw()+scale_y...
第四列是数字,用来填充颜色和控制位置 接下来是ggplot2作图代码 install.packages('aplot') library(ggplot2) library(aplot) df<-read.csv('rscu.txt',header=F,stringsAsFactors = F) p1<-ggplot(df,aes(fill=as.character(V4),x=V2,y=V3))+ geom_bar(position = "stack",stat="identity")+ theme_...
第四列是数字,用来填充颜色和控制位置 接下来是ggplot2作图代码 install.packages('aplot') library(ggplot2) library(aplot) df<-read.csv('rscu.txt',header=F,stringsAsFactors = F) p1<-ggplot(df,aes(fill=as.character(V4),x=V2,y=V3))+ geom_bar(position = "stack",stat="identity")+ theme_...
I have got a question about creating a stacked barplot in R with ggplot2. What I want to create is a stacked bar plot in which every bar is placed "on top" of the other. x = c(100,200,400,600,800,1000,1250,1500) y1 = c(1,2,3,4,5,6,7,8) y2 = c(8,7,6,5,4,3...
Here's the basic plot (in this example, all 6 bars have the same color ramp): library(ggplot2)ggplot(data=dat,aes(x=reorder(Group.2,-xMax),y=x))+geom_bar(aes(fill=reorder(Group.1,-x)),position='stack',colour="black",size=.3)+coord_flip()+theme_bw()+stat...
接下来是ggplot2作图代码 代码语言:javascript 复制 install.packages('aplot') library(ggplot2) library(aplot) df<-read.csv('rscu.txt',header=F,stringsAsFactors = F) p1<-ggplot(df,aes(fill=as.character(V4),x=V2,y=V3))+ geom_bar(position = "stack",stat="identity")+ theme_bw()+scale...
r stacked ggplot2 stacked-chart dplyr Die*_*oya 2018 10-05 1推荐指数 1解决办法 503查看次数 如何在熊猫中添加堆叠条形图孵化?(...或者如何在 Pandas plot 与 matplotlib 中获取 BarContainer 与 AxisSubplot?) 我有一个代码示例,使用matplotlib.pyplot.plot()它可以工作,我想复制它以在堆积条形图上制作...
21-distribution-plot-using-ggplot2_files 210-custom-barplot-layout_files 211-basic-grouped-or-stacked-barplot_files 215-interactive-heatmap-with-plotly_files 215-the-heatmap-function_files 218-basic-barplots-with-ggplot2_files 22-order-boxplot-labels-by-names_files 220-basic-ggplot...
Bland-Altman/Tukey Mean-Difference Plots using ggplot2 A very useful data visualisation tool in science, particularly in medical and sports settings, is the Bland-Altman/Tukey Mean-Difference plot. When comparing two sets of measurements for the same variable made by different instruments, it is ...
(dpi = 300) # Plot p <- ggplot(data = df, aes(x = AntBev, y = Jahr, fill = reorder(Bildungsstand, -rang))) + geom_bar(stat = "identity", width = 0.6) + geom_errorbar(aes(y = Jahr, xmin = AntCumUn, xmax = AntCumOb), width = 0.1, linewidth = 0.25, color = get_...