由于重新排序，缩放 x 轴不起作用？

使用 scale_x_discrete() 可以指定要在 x 轴上放置的标签，例如

library(tidyversE)

rank <- tribble(~"species",~"ab",~"rank","PEGR2",462.10,792,"COUM",269.70,1126,"KRGR",207.04,1314,"KRER",177.11,1439,"PEBR",176.00,1446,"CAMI12",140.71,1623)

ggplot(rank,aes(x = reorder(rank,-ab),y = ab)) +
  geom_bar(stat = "identity") +
  labs(x = "Abundance Rank",y = "Abundance") +
  theme_bw() +
  theme(panel.grid.minor = elemenT_Blank(),panel.grid.major = elemenT_Blank(),panel.border = elemenT_Blank(),axis.line.x = elemenT_Blank(),axis.line.y = elemenT_Blank(),axis.text.x = element_text(angle = 90)) +
  scale_x_discrete(breaks = c(792,1623),labels = c(792,1623))

问题出在 scale_x_conTinuous 上，reorder 的输出是 factor。下面详细解释

library(dplyr,warn.conflicts = falSE)  
library(ggplot2)

# to understand we need to know what reorder does
# As you can see from the output below,it output a factor with Levels
with(rank,reorder(rank,-ab))
#> [1] 792  1126 1314 1439 1446 1623
#> attr(,"scores")
#>     792    1126    1314    1439    1446    1623 
#> -462.10 -269.70 -207.04 -177.11 -176.00 -140.71 
#> Levels: 792 1126 1314 1439 1446 1623

# And as it is a factor it will be treat as discrete value
# Therefore ggplot will display all value in the axis and
# your scale_x_conTinuous will causing error as it apply conTinuous to 
# discrete value
ggplot(rank,y = ab))+
  geom_bar(stat = "identity")+
  scale_x_conTinuous(breaks=seq(792,8538,10))+
  labs(x = "Abundance Rank",y = "Abundance") +
  theme_bw()+
  theme(panel.grid.minor = elemenT_Blank(),axis.text.x = element_text(angle = 90))
#> Error: Discrete value supplied to conTinuous scale

请注意，当您按 ab 重新排序时，数据可能不会像以前那样按连续顺序排列，因此如果人们误认为 x 轴是连续的，而实际上不是，则该图会令人困惑。

您可能需要重新考虑您想在这里实现什么，您想通过图表讲述什么故事。

# Another way to visualize the order is using fill to visualized the rank
graph_data <- rank %>%
  # create a rank variable with negative ab value result
  # in biggest value rank 1st
  mutate(rank_ab = rank(-ab))
graph_data
#>   species     ab rank rank_ab
#> 1   PEGR2 462.10  792       1
#> 2    COUM 269.70 1126       2
#> 3    KRGR 207.04 1314       3
#> 4    KRER 177.11 1439       4
#> 5    PEBR 176.00 1446       5
#> 6  CAMI12 140.71 1623       6

ggplot(graph_data,aes(x = rank,y = ab))+
  # Then here graph data with fill geom_bar
  geom_bar(stat = "identity",mapping = aes(fill = rank_ab)) +
  scale_x_conTinuous(breaks=seq(792,100))+
  labs(x = "Abundance Rank",axis.text.x = element_text(angle = 90))

^{由 reprex package (v2.0.0) 于 2021 年 4 月 28 日创建}