R ggplot2中geom_point气泡上色及viridis离散配色设置方法

前置准备 #

如果未安装viridis配色包，先运行以下命令安装：

install.packages("viridis")

完整可运行代码 #

# 加载所需包
library(ggplot2)
library(reshape2)
library(viridis)

# 示例数据构造，如果你是从本地读取dat.csv，直接替换这段为你的读文件代码即可
dat <- structure(list(station = c(980009L, 980042L, 980145L, 980338L, 
980351L, 980365L, 980563L), JAN = c(0.04, 0.04, 0.04, 0.04, 0.04, 
0.05, 0), FEB = c(0.05, 0.04, 0.99, 0.99, 0.99, 0.04, 0.99), 
 MAR = c(0.04, 0.99, 0.99, 0.99, 0.99, 0.99, 0), APR = c(0.05, 
 0.04, 0.99, 0.99, 0.99, 0.99, 0), MAY = c(0.06, 0.05, 0.95, 
 0.05, 0.96, 0.94, 0.98), JUN = c(0.05, 0.07, 0.04, 0.04, 
 0.05, 0.04, 0.99), JUL = c(0.05, 0.04, 0, 0.93, 0.92, 0.97, 
 0), AUG = c(0.04, 0.06, 0.98, 0.98, 0.99, 0.99, 0), SEP = c(0.04, 
 0.04, 0.98, 0.04, 0.04, 0.04, 0), OCT = c(0.04, 0.07, 0.99, 
 0.05, 0.04, 0.99, 0), NOV = c(0.04, 0.07, 0.99, 0.05, 0.06, 
 0.05, 0), DEC = c(0.04, 0.99, 0.05, 0.04, 0.04, 0.05, 0)), class = "data.frame", 
 row.names = c(NA,-7L))

# 数据长宽转换
pcm <- melt(dat, id = c("station"))
pcm$station <- factor(pcm$station, levels = unique(pcm$station))
# 百分比计算+切为10个离散分组，对应10种viridis配色
pcm$value_percent <- pcm$value * 100
pcm$value_group <- cut(pcm$value_percent, breaks = seq(0, 100, by = 10), include.lowest = TRUE)

# 绘图
p <- ggplot(pcm, aes(x = variable, y = station)) +
  geom_point(aes(fill = value_group, size = value_percent), alpha = 0.5, shape = 21) +
  coord_fixed(ratio = 1) +
  labs(x = "month", y = "station", size = "Percentage") +
  scale_size_continuous(limits = c(0, 100), breaks = seq(0, 100, by = 10)) +
  scale_x_discrete(expand = c(0.1, 0)) +
  # 调用离散viridis配色，调整option参数可切换同系列不同配色风格
  scale_fill_viridis_d(option = "D", drop = FALSE) +
  # 隐藏填充色对应的图例，保留大小图例
  guides(fill = "none")

# 导出图片
png("Bubble_plot.png", width = 800, height = 600)
print(p)
dev.off()

调整说明 #

• 针对问题a：你原本使用的shape=21本身就支持填充色展示，只需新增guides(fill = "none")语句即可直接隐藏填充色对应的图例，不会影响大小图例的正常显示。
• 针对问题b：先通过cut()函数把0-100的连续百分比值切为10个等距离散分组，再调用scale_fill_viridis_d()即可匹配10种离散的viridis配色。

内容的提问来源于stack exchange，提问作者Lyndz