r - 如何计算列中每个类别的份额？

Question

df = data.frame(week = as.factor(rep(c(1, 2), times = 5)),
                name = as.factor(rep(LETTERS[1:5], times = 2)),
                count = rpois(n = 10, lambda = 20))

    > df
     week   name count
1       1      A    16
2       2      B    14
3       1      C    23
4       2      D    15
5       1      E    12
6       2      A    15
7       1      B    23
8       2      C    22
9       1      D    22
10      2      E    26

我想计算每个名字每周的计数份额。
起初我打算使用以下方法:

transform(df, week1_share = ifelse(week == "1", round((df$count / sum(df$count)  * 100),2), NA))
transform(df, week2_share = ifelse(week == "2", round((df$count / sum(df$count)  * 100),2), NA))

但是然后让每一列合并，最终把它作为条形图上的标签，似乎效率太低了。必须有某种类型的快速解决方案，我还不知道。

基本上我想做的是如下但添加可能已按上述计算出的份额％以匹配每个框。

ggplot(df, aes(reorder(week, -count),count, color = "white", group = name, fill = name))+
        geom_bar(position = "stack", stat = "identity") +
        scale_y_continuous(labels=comma)+
        ggthemes::scale_color_tableau()

我不知道为什么重新排序功能经常在我身上失败。如果您有在 desc 中排序的任何提示，请分享。

Answer 1

您提供的数据已被用于:

# Loading the required data
df = data.frame(week = as.factor(rep(c(1, 2), times = 5)),
                name = as.factor(rep(LETTERS[1:5], times = 2)),
                count = rpois(n = 10, lambda = 20))

使用 plyr包装函数、百分比和标记的相对位置已经计算。

#Loading the required packages    
library(plyr)
library(ggplot2)

# Calculating the percentages
df = ddply(df, .(week), transform, percent = round(count/sum(count) * 100))

# Calculating the position for plotting
df = ddply(df, .(week), transform, pos = cumsum(percent) - (0.5 * percent))

使用上面计算的信息，绘图已经完成。

# Basic graph
p10 <- ggplot() + geom_bar(aes(y = percent, x = week, fill = name), 
                       data = df, stat="identity")

# Adding data labels
p10 <- p10 + geom_text(data=df, aes(x = week, y = pos, 
                                label = paste0(percent,"%")), size=4)
p10

这是您一直在寻找的吗？