如何将连续日期转换为离散日期？

Question

我有一组数据，其中包含两个不同年份的值，但在绘制它时我无法将其设置为两个离散的类别，而不是连续的日期范围。

如果我尝试 scale_x_discrete，年份标签将完全消失。

library(ggplot2)
ggplot(df2018, aes(x = Year, y= Weight, fill = Year)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  facet_wrap(~ Species, scale = "free_x") +
  scale_x_discrete("Year", labels = c("2018", "2019"))

如何转换年份列以便 ggplot 将其读取为两个不同的类别（即 2018 年和 2019 年）？

数据：

structure(list(Species = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 
2L, 3L, 1L, 4L, 5L, 6L), .Label = c("Coralline", "Pocockiella", 
"Gigartina", "Ulva", "Colpomenia", "Sargassum"), class = "factor"), 
    Year = c(2018, 2018, 2018, 2018, 2018, 2018, 2019, 2019, 
    2019, 2019, 2019, 2019), Weight = c(0.83879, 1.61504, 2.32838, 
    6.25983, 8.77286, 115.48649, 0.046695, 0.1373982, 0.392931, 
    0.508436, 0.521956, 90.098115), Percent = c(0.614156130776106, 
    1.18252091399354, 1.70482343825805, 4.58340344080901, 6.42342630865946, 
    84.5583946581545, 0.0508869004261174, 0.149732702047923, 
    0.428205175529173, 0.554079282686656, 0.568812999225068, 
    98.186396971536)), row.names = c(NA, -12L), class = c("tbl_df", 
"tbl", "data.frame"))

Answer 1

将 year 更改为 factor class :

library(dplyr)
library(ggplot2)

df %>%
  mutate(Year = factor(Year)) %>%
  ggplot() + aes(x = Year, y= Weight, fill = Year) +
  geom_bar(stat = "identity") +
  coord_flip() +
  facet_wrap(~ Species, scale = "free_x")

Answer 2

我们可以单独使用ggplot来做到这一点

library(ggplot2)
ggplot(df2018, aes(x = Year, y= Weight, fill = as.factor(Year))) +
    geom_bar(stat = "identity") +
   coord_flip() +
   facet_wrap(~ Species, scale = "free_x") +
   scale_x_discrete("Year", labels = c("2018", "2019")) + 
   scale_fill_discrete(name = 'Year')

-输出

如何将连续日期转换为离散日期？

How to convert continuous date into discete category?

r

data-visualization

bar-chart

ggplot2

geom-bar