要实现每个分组使用不同的颜色渐变，我们可以借助ggnewscale包来突破ggplot默认只能有一组填充映射的限制。下面是修改后的完整代码，以及关键步骤的解释：

完整代码 #

## dummy data -----------------------------------------------------------------------------
data <- data.frame(
 group = sample(c("Direct Patient Care", "Indirect Patient Care", "Education", "Rounds", "Handoff", "Misce"), 30, replace = T),
 pct = rnorm(30, mean = 50, sd = 8)
)
## generate group id
data <- data %>% group_by(group) %>% mutate(id = row_number())
data$grpid <- with(data, ifelse(group == "Direct Patient Care", 1, ifelse(group == "Indirect Patient Care", 2, ifelse(group == "Education", 3, ifelse(group == "Rounds", 4, ifelse(group == "Handoff", 5,6 ))))))

## draw graph ------------------------------------------------------------------------------
library(ggplot2)
library(dplyr)
library(ggnewscale) # 先安装：install.packages("ggnewscale")

p <- ggplot() +
  # Direct Patient Care：橙色渐变
  geom_tile(data = filter(data, group == "Direct Patient Care"), 
            aes(x = id, y = group, fill = pct)) +
  scale_fill_gradient2(low = "white", mid = "orange", high = "darkorange", 
                       limits = c(0, 80), name = "Direct Care\nTime, %") +
  new_scale_fill() + # 重置填充比例尺，用于下一个分组
  
  # Indirect Patient Care：紫色渐变
  geom_tile(data = filter(data, group == "Indirect Patient Care"), 
            aes(x = id, y = group, fill = pct)) +
  scale_fill_gradient2(low = "white", mid = "plum", high = "purple", 
                       limits = c(0, 80), name = "Indirect Care\nTime, %") +
  new_scale_fill() +
  
  # Education：黄色渐变
  geom_tile(data = filter(data, group == "Education"), 
            aes(x = id, y = group, fill = pct)) +
  scale_fill_gradient2(low = "white", mid = "gold", high = "goldenrod", 
                       limits = c(0, 80), name = "Education\nTime, %") +
  new_scale_fill() +
  
  # Rounds：红色渐变（你的需求）
  geom_tile(data = filter(data, group == "Rounds"), 
            aes(x = id, y = group, fill = pct)) +
  scale_fill_gradient2(low = "white", mid = "pink", high = "red", 
                       limits = c(0, 80), name = "Rounds\nTime, %") +
  new_scale_fill() +
  
  # Handoff：绿色渐变（你的需求）
  geom_tile(data = filter(data, group == "Handoff"), 
            aes(x = id, y = group, fill = pct)) +
  scale_fill_gradient2(low = "white", mid = "lightgreen", high = "darkgreen", 
                       limits = c(0, 80), name = "Handoff\nTime, %") +
  new_scale_fill() +
  
  # Misce：蓝色渐变（你的需求）
  geom_tile(data = filter(data, group == "Misce"), 
            aes(x = id, y = group, fill = pct)) +
  scale_fill_gradient2(low = "white", mid = "lightblue", high = "darkblue", 
                       limits = c(0, 80), name = "Misce\nTime, %") +
  
  # 保留你原来的主题设置
  theme(panel.background = element_rect(fill = "white", colour = "grey50"), 
        aspect.ratio = 0.4) +
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +
  scale_x_continuous(name = " ", breaks = seq(1, 8, by = 1)) +
  scale_y_discrete(name = " ") +
  theme(axis.text.x = element_text(angle = 0, hjust = 1, vjust = 1), 
        plot.title = element_text(hjust = 0.5)) +
  ggtitle("Heatmap of time spent doing activities across 194 shifts")

print(p)

关键细节说明 #

• ggnewscale核心作用：每次调用new_scale_fill()，ggplot会重置填充映射规则，让后续的geom_tile()可以使用完全独立的颜色渐变，不会和之前的分组冲突。
• 按分组筛选数据：用filter(data, group == "XXX")精准定位每个分组的数据集，确保每个geom_tile()只绘制对应分组的热图块。
• 统一数值标尺：所有渐变都设置了相同的limits = c(0, 80)，这样不同分组的颜色深浅能对应相同的百分比数值，保证可视化的准确性和可比性。
• 渐变自定义：你可以根据需求调整scale_fill_gradient2的low（浅色调）、mid（中间色调）、high（深色调）参数；如果不需要中间色，改用scale_fill_gradient（仅需设置low和high）即可。

内容的提问来源于stack exchange，提问作者mandy