Вы можете использовать Tidyverse для сбора данных и затем классифицировать их по группам:
library(tidyverse)
dat <- structure(list(A = c(0.9523, 0.06944,
0.53061, 0.11111, 0.03125, 0.64794,
0.10763, 0.02782, 0.0374149659863946, 0.8439),
B = c(0, 0.2378, 0.0068, 0.8328, 0.7292, 0.7539, 0.7439, 0.0742, 0.5272, 0.6822),
C = c(0.0273, 0.0901, 0.7778, 0.9462, 0.5327, 0.2744, 0.5327, 0.4262, 0.6821, 0.03125),
D = c(0.0297, 0, 0, 0.03462, 0.0272, 0.0325, 0.6282, 0.6282, 0.6329, 0.8925),
E = c(0.0325, 0.0829, 0.6328, 0.5237, 0.5722, 0.7283, 0.6382, 0.5637, 0.5632, 0.0532)),
row.names = c(NA, -10L), class = c("tbl", "data.frame"))
dat_clean <- dat %>%
gather(key = "col", value = "value") %>%
mutate(group = case_when(
col %in% c("A","B") ~ "group1",
col %in% c("C", "D", "E") ~ "group2"
))
ggplot(dat_clean, aes(x = col, y = value, fill = group)) +
geom_bar(stat = 'identity') +
theme(legend.position = 'None')
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Создано в 2019-04-30 с помощью представьте пакет (v0.2.1)