【发布时间】:2020-05-05 19:44:12
【问题描述】:
我正在尝试创建一个堆叠条形图,它在 y 轴上显示平均丰度,在 x 轴上显示主要营养组,每个条形图将由特定营养组填充(主要营养组被细分进一步)
我创建了一个数据示例,您应该可以直接将其放入 R:
Example<-structure(list(Species = c("Fish1", "Fish2", "Fish3", "Fish4",
"Fish5", "Fish6", "Fish7", "Fish1", "Fish2", "Fish3", "Fish4",
"Fish5", "Fish6", "Fish7", "Fish1", "Fish2", "Fish3", "Fish4",
"Fish5", "Fish6", "Fish7"), Trophic = c("Herbivore", "Omnivore",
"Herbivore", "Predator", "Predator", "Omnivore", "Omnivore",
"Herbivore", "Omnivore", "Herbivore", "Predator", "Predator",
"Omnivore", "Omnivore", "Herbivore", "Omnivore", "Herbivore",
"Predator", "Predator", "Omnivore", "Omnivore"), Trophic_Specific = c("Grazer",
"Generalist_Omnivore", "Browser", "Micro-invertebrate_Predator",
"Micro-invertebrate_Predator", "Generalist_Omnivore", "Benthic_Omnivore",
"Grazer", "Generalist_Omnivore", "Browser", "Micro-invertebrate_Predator",
"Micro-invertebrate_Predator", "Generalist_Omnivore", "Benthic_Omnivore",
"Grazer", "Generalist_Omnivore", "Browser", "Micro-invertebrate_Predator",
"Micro-invertebrate_Predator", "Generalist_Omnivore", "Benthic_Omnivore"
), Transect = c(1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 3,
3, 3, 3, 3, 3, 3), Count = c(1, 2, 34, 0, 4, 2, 1, 0, 2, 25,
1, 4, 2, 1, 1, 4, 50, 3, 6, 7, 3)), class = c("spec_tbl_df",
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -21L), spec = structure(list(
cols = list(Species = structure(list(), class = c("collector_character",
"collector")), Trophic = structure(list(), class = c("collector_character",
"collector")), Trophic_Specific = structure(list(), class = c("collector_character",
"collector")), Transect = structure(list(), class = c("collector_double",
"collector")), Count = structure(list(), class = c("collector_double",
"collector"))), default = structure(list(), class = c("collector_guess",
"collector")), skip = 1), class = "col_spec"))
如果我在 Excel 中手动计算出平均丰度(即 3 个样带中每个物种/营养组的平均数量),我知道如何使用 ggplots 在条形图中绘制它(但我不知道如何得到我的误差线)。
我如何在 R 中总结这些原始数据,以便我可以使用横断面 1-3 作为我的重复来获得每个特定营养组的平均丰度,然后我可以将其绘制在如上所述的条形图中?
【问题讨论】:
标签: r ggplot2 bar-chart mean data-manipulation