你好stackoverflowers!
由于标题表示我想制作热图,但颜色缩放应该跨越每行和彼此的个体。
以下示例将指出我想要的内容:
library(tidyverse)
library(data.table)
data_heat <- expand.grid(y = letters[seq( from = 1, to = 6 )],x = LETTERS[ seq( from = 1, to = 10 )]) %>% as.data.table()
data_heat %>% setkey(y)
data_heat[, fill_value := seq(from = 1,to = nrow(data_heat))]
data_heat%>% ggplot(aes(x = x, y = y)) +
geom_tile(aes(fill = fill_value), colour = "black") + scale_fill_gradient(low = "green",
high = "red") +
theme(axis.text.x = element_text(angle = 30, hjust = 1)) + geom_text(aes(label = fill_value))
这将产生:
虽然我想要的是图表的右侧是红色的,因为每行有最大的值。
答案 0 :(得分:5)
解决方案:
使用每个组scale()
)的函数data_heat$y
缩放值。
代码:
library(ggplot2)
library(data.table)
data_heat[, fillScaled := scale(fill_value), y]
ggplot(data_heat, aes(x, y)) +
geom_tile(aes(fill = fillScaled), colour = "black") +
scale_fill_gradient(low = "green", high = "red") +
geom_text(aes(label = fill_value)) +
theme(axis.text.x = element_text(angle = 30, hjust = 1))
结果:
数据(data_heat
):
structure(list(y = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L), .Label = c("a", "b", "c", "d", "e", "f"), class = "factor"),
x = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 1L, 2L, 3L, 4L,
5L, 6L, 7L, 8L, 9L, 10L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L,
9L, 10L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 1L, 2L,
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L), .Label = c("A", "B", "C",
"D", "E", "F", "G", "H", "I", "J"), class = "factor"), fill_value = 1:60), .Names = c("y",
"x", "fill_value"), out.attrs = structure(list(dim = structure(c(6L,
10L), .Names = c("y", "x")), dimnames = structure(list(y = c("y=a",
"y=b", "y=c", "y=d", "y=e", "y=f"), x = c("x=A", "x=B", "x=C",
"x=D", "x=E", "x=F", "x=G", "x=H", "x=I", "x=J")), .Names = c("y",
"x"))), .Names = c("dim", "dimnames")), class = c("data.table",
"data.frame"), row.names = c(NA, -60L))
答案 1 :(得分:1)
更基本的数据处理方法:
library(dplyr)
data_heat_summary <- data_heat %>%
group_by(y) %>%
summarize(mx = max(fill_value), mn = min(fill_value))
data_heat %>%
inner_join(data_heat_summary) %>%
mutate(p = (fill_value - mn ) / (mx - mn)) %>%
ggplot(aes(x = x, y = y)) +
geom_tile(aes(fill = p), colour = "black") +
scale_fill_gradient(low = "green", high = "red") +
theme(axis.text.x = element_text(angle = 30, hjust = 1)) + geom_text(aes(label = fill_value))