如何根据其平均值 convert/transform 列并将其反映在 R 中的图表上？

Question

我有以下数据框和基于它的堆积面积图

df <- data.frame (Year  = c("2010", "2010",  "2010", "2010", "2011","2011","2011","2011","2012","2012","2012","2012","2013","2013","2013","2013"),
                  Sales = c(100000000,200000000,50000000,500000000,400000000,200000000,400000000,145000000,100000000,456000000,345000000,321000000,100000000,200000000,250000000,400000000),
                 Category = c("A", "B",  "C", "D","A", "B",  "C", "D","A", "B",  "C", "D","A", "B",  "C", "D"))

df$Year <- as.integer(df$Year)

df %>% 
  ggplot(aes(x = Year, y = Sales, fill = Category)) +
  geom_area() + scale_x_continuous(breaks=2010:2013)

现在我想以某种方式编写以下代码：

如果 mean(df$Sales) > 1 000 000 那么 df$Sales/1 000 000
如果 mean(df$Sales) > 1 000 & <1 000 000 那么 df$Sales/1 000
否则什么也不做

在我想在 ggplot y 轴上反映之后：

如果满足第一个条件，则将 y 轴标记为“万亿销售额”
如果满足第二个条件，则将 y 轴标记为“十亿销售额”，否则
将 y 轴标记为“百万销售额”

Answer 1

这个 if/else 语句不能解决问题吗？

library(tidyverse)


y_label = "Sales in Million"
if(mean(df$Sales)>1000000){
  df$Sales2 = df$Sales/1000000
  y_label = "Sales in Billion"
} else if(mean(df$Sales)>1000){
  df$Sales2 = df$Sales/1000
  y_label = "Sales in Trillion"
}

df %>% 
  ggplot(aes(x = Year, y = Sales2, fill = Category)) +
  geom_area() + scale_x_continuous(breaks=2010:2013) + 
  ylab(y_label)

^{由 reprex package (v2.0.1)}

于 2022-04-30 创建

PS ：+1 用于使用示例数据集格式化问题

如何根据其平均值 convert/transform 列并将其反映在 R 中的图表上？

How to convert/transform column based on its mean value and reflect that on chart too in R?

loops

if-statement

r

ggplot2

dplyr