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_continuous(expand=c(0,0), limits = c(0,...
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_continuous(expand=c(0...
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_continuous(expand=c(0,0),limits=c...
counts = [5,3,4,2,4,6] p = figure(x_range=fruits, plot_height=250, title="Fruit Counts", toolbar_location=None, tools="") p.vbar(x=fruits, top=counts, width=0.9) p.xgrid.grid_line_color =Nonep.y_range.start =0show(p) 效果图见上述参考 增加一个 y 数据源,做堆叠效果 这样...
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_continuous(expand=c(0,0), limits = c(0,...
1.Make a bar plot. //生成一个条形图 2.The bars are positioned at x with the given alignment. Their dimensions are given by height and width. The vertical baseline is bottom (default 0). //x定义bar放置的位置,如labels; (x,height是必须参数) ...
# 4. Create a stacked bar plot, add "mean_se" error barsp <- ggbarplot( df, x ="dose", y ="len", add ="mean_se", color ="supp", palette ="jco")# 5. Add p-values to the bar plot using ggpubr verbsp + stat_pvalue_manual( res.stats, x ="dose", y.position = c(...
我先假设你用的是python(虽然我感觉像是matlab)import matplotlib.pyplot as plt plt.plot(x,y,'ro',label="point")plt.legend()plt.show()这里legend可以显示图示 如果是matlab 你直接标legend=xxxx就行了 可以查一下用法
Plot bar chart:By usingbar()method we can bar chart. Set bottom:Set bottom of the next bar equalls to the values of the pervious bars. Generate a Plot:Use theshow()method to visulaize the plot on the user’s windows. ReadHow to install matplotlib python ...
bar(r, orangeBars, bottom=greenBars, color='#f9bc86', edgecolor='white', width=barWidth) # Create blue Bars plt.bar(r, blueBars, bottom=[i+j for i,j in zip(greenBars, orangeBars)], color='#a3acff', edgecolor='white', width=barWidth) # Custom x axis plt.xticks(r, names) ...