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R:如何在单个绘图中绘制两列比较直方图?_R_Ggplot2_Plot_Charts_Plotly - Fatal编程技术网

R:如何在单个绘图中绘制两列比较直方图?

R:如何在单个绘图中绘制两列比较直方图?,r,ggplot2,plot,charts,plotly,R,Ggplot2,Plot,Charts,Plotly,R:如何在单个绘图中绘制两列比较直方图 due_vs_prom <- factor( c(unique(inv$Due_Bin)),levels = c("early","<=5","<=30","<=10","<=50",">50")) due_counts <- inv %>% group_by(Due_Bin) %>% summarize(count = n()) prom_counts <- inv %>% group_b

R:如何在单个绘图中绘制两列比较直方图

due_vs_prom <- factor( c(unique(inv$Due_Bin)),levels = c("early","<=5","<=30","<=10","<=50",">50"))
due_counts <- inv %>% group_by(Due_Bin) %>% summarize(count = n())
prom_counts <- inv %>% group_by(Prom_Bin) %>% summarize(count = n())

due_vs_prom <- data.frame(due_vs_prom , due_counts , prom_counts )

plot_due_vs_prom <- plot_ly(due_vs_prom, y = ~due_counts , x = ~ (prom_counts), type = 'bar', name = 'Due_Bin') %>%
  add_trace(x = ~due_counts, name = 'Late Bin') %>%
  layout(xaxis = list(title = 'Count'), barmode = 'group')

due\u vs\u prom%summary(count=n())
prom\U计数%group\U by(prom\U Bin)%>%SUMMARY(计数=n())
到期日与可编程只读存储器%
布局(xaxis=list(title='Count'),barmode='group')
数据集,如:

Promise_Bin             Due_Bin

early                   early             
early                   >50
early                   >50
>50                     >50
>50                     >50
<=50                    <=50
early                   early
early                   early
<=5                     <50
<=5                     <=5
<=30                    <=30
early                   early
<=30                    >50
<=30                    <=30                    
<=10                    <=10

Promise\u Bin到期
早早
早期>50
早期>50
>50                     >50
>50                     >50

您可以将数据帧重塑为更长的格式(此处使用
tidyr
软件包中的
pivot\u longer
),按“Bin”和不同的“categories”分组,对每个数据帧进行计数,最后使用
geom\u col
绘制数据帧:

库(dplyr)
图书馆(tidyr)
图书馆(GG2)
df%>%pivot\u更长(everythings(),names\u to=“var”,values\u to=“val”)%>%
分组依据(var,val)%>%count()%>%
ggplot(aes(x=val,y=n,fill=var))+
几何坐标(位置=位置减淡()

它回答了你的问题吗


可再现数据

结构(列表(Promise_Bin=c(“早”、“早”、“早”、“早”和“>50”),

“>50”,“请编辑您的问题以解释当前代码有什么问题,它生成了什么?也可以执行
count(var,val)%%>%
而不是
group\u by(var,val)%%>%count()%%>%
是的,您说得对;)。我不知道如何使用
count
。谢谢;).现在,我发现先通过
分组,然后再通过
计数更加明确,但我想这只是我的用途。