示例数据集:
library(ggplot2)
df = read.table(text =
"id year value1 value2 value3
1 2000 1 2000 2001
1 2001 2 NA NA
1 2002 2 2000 NA
1 2003 2 NA 2003
2 2000 1 2001 2003
2 2002 2 NA 2000
2 2003 3 2002 NA
3 2002 2 2001 NA
", sep = "", header = TRUE)
df$value1 <- as.factor(df$value1)
我知道如何使用三个级别更改因子变量的颜色:
p <- ggplot(df, aes(y=id))
p <- p + scale_colour_manual(name="", values =c("yellow", "orange", "red"))
p <- p + geom_point(aes(x=year, color=value1), size=4)
p
我还可以更改两个数字变量的颜色:
p <- ggplot(df, aes(y=id))
p <- p + scale_colour_manual(name="", values =c("value3"="grey", "value2"="black"))
p <- p + geom_point(aes(x=value3, colour ='value3'), size=3)
p <- p + geom_point(aes(x=value2, colour ='value2'), size=5)
p
但我不知道如何在同一个图表中更改两者的颜色? 它是否也适用于scale_color_manual?
p <- last_plot() + geom_point(aes(x=year, color=value1))
p
答案 0 :(得分:23)
这是你在找什么?
ggplot(df, aes(y=id)) +
geom_point(aes(x=year, color=value1), size=4) +
geom_point(aes(x=value3, colour ='value3'), size=3) +
geom_point(aes(x=value2, colour ='value2'), size=5) +
scale_colour_manual(name="",
values = c("1"="yellow", "2"="orange", "3"="red",
"value3"="grey", "value2"="black"))
基本上,只需将所有可能的颜色标签放在一个列表中即可。
答案 1 :(得分:2)
JLLagrange提出了正确的想法。在绘图之前,使用melt
中的reshape2
将数据转换为长格式。
df_long <- melt(df,id.vars = c("id", "year"), measure.vars=c("value2", "value3"))
(p <- ggplot(df_long, aes(y = id)) +
scale_colour_manual(name = "", values = c(value3 = "grey", value2 = "black")) +
scale_size_manual(name = "", values = c(value3 = 3, value2 = 5)) +
geom_point(aes(x = value, colour = variable, size = variable))
)
根据您的评论,您的数据应采用不同的形式。从本质上讲,您认为value2
和value3
与year
相同,但value1
的附加级别。像这样重建您的数据:
df1 <- df[, c("id", "year", "value1")]
df2 <- data.frame(
id = df$id,
year = df$value2,
value1 = "4"
)
df3 <- data.frame(
id = df$id,
year = df$value3,
value1 = "5"
)
df_all <- rbind(df1, df2, df3)
df_all$value1 <- factor(df_all$value1)
然后你可以用这个画出一个情节:
(p <- ggplot(df_all, aes(id, year, colour = value1)) +
geom_point(
size = 3,
position = position_jitter(height = 0, width = 0.05)
) +
scale_colour_manual(
values = c("1" = "yellow", "2" = "orange", "3" = "red", "4" = "grey", "5" = "black")
)
)
(我在点上添加了一些抖动,因此您可以看到它们重叠的位置。您还可以在alpha
中设置geom_point
值。)