R:具有n个组的条形图，可堆叠2个值 [英] R: barplot with n groups which stacks 2 values

问题描述

我需要生成一个包含以下内容的 barplot :

我有一个包含以下内容的csv文件:类别原因时间值

• 类别有7个可能的名称(c1 ... c7)
• 原因有8个可能的名称(n1 ... n8)
• 时间有2个可能的名称(T1，T2)
• 值是时间值

示例数据集:

 类别原因时间值C1 R1 T1 1C2 R1 T2 2C1 R2 T1 3C2 R2 T2 4C1 R3 T1 8C2 R3 T2 0 

我想要实现的目标:条形图由3组组成(每个REASON一组)，其中每组由2条堆叠的条形图(即每个CATEGORY的条形图)组成，每个条形图在其顶部都表示T1和T2.

我想我需要类似于

感谢您的帮助.

解决方案

我将向您介绍R中的 ggplot 包，它可能为您提供更好的可视化问题的方法.即使不能解决您当前的问题， ggplot 也是在R中启动可视化效果的最简单方法.

首先输入代码:

库将加载 ggplot 和 scales 包

 库(ggplot2)图书馆(秤) 

生成您的虚拟数据集

  df = expand.grid(factor(c("C1"，"C2"，"C3"，"C4"，"C5"，"C6"，"C6"，"C8"))，因子(c("R1"，"R2"，"R3"，"R4"，"R5"，"R6"，"R7"))，因子(c("T1"，"T2"))) 

在x轴上以 Category ，在y轴上为 Value ，以 Time 作为堆积条的图，需要 geom_bar().代替对条形图本身进行分组， ggplot 可以使用 facets ，这样可以产生更清晰的结果. scale_y_continuous()将您的y轴转换为百分比.

  ggplot(数据= df，aes(x =原因，y =值，填充=时间))+geom_bar(stat ='identity')+facet_wrap(〜类别)+scale_y_continuous(labels = percent)+主题(panel.background = element_rect(fill ="white")) 

I need to generate a barplot which consists of the following:

I have a csv file with columns: Category Reason Time Value

• Category has 7 possible names (c1 ... c7)
• Reason has 8 possible names (n1 ... n8)
• Time has 2 possible names (T1, T2)
• Value is the time value

Example dataset:

Category    Reason  Time    Value
C1  R1  T1  1
C2  R1  T2  2
C1  R2  T1  3
C2  R2  T2  4
C1  R3  T1  8
C2  R3  T2  0

What i want to achieve: A bar plot which consists of 3 groups (i.e. one group per REASON), where each group consists of 2 stacked bars (i.e. a bar for each CATEGORY), where each bar depicts T1 and T2 on top of it.

I guess i need something similar as R: bar plot with two groups, of which one is stacked, but unfortunately i'm very new to R.

Similar to this picture, which has in terms of my example:

• 5 categories
• 3 reasons
• 4 times values
• % as a time value

Any help is appreciated.

解决方案

I am going to introduce you to the ggplot package in R which may give you a better way of visualizing your problem. Even if it does not solve your current problem, ggplot would be the easiest for starting your visualizations in R.

First the code:

library will load ggplot and scales package

library(ggplot2)
library(scales)

Generating your dummy data set

df = expand.grid(factor(c("C1","C2","C3","C4","C5","C6","C6","C8")),
                 factor(c("R1","R2","R3","R4","R5","R6","R7")),
                 factor(c("T1","T2")))

Plot with Category on x-axis, Value on y-axis, Time as the stacked bar which needs geom_bar(). Instead of grouping on the bar chart itself, ggplot can use facets, which produces cleaner results. scale_y_continuous() converts your y-axis to percent.

ggplot(data = df, aes(x=Reason, y=Value, fill = Time)) + 
  geom_bar(stat='identity') + 
  facet_wrap(~Category) +
  scale_y_continuous(labels = percent) +
  theme(panel.background = element_rect(fill = "white"))

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