Sample dataset:
library(ggplot2)
df = read.table(text =
\"id year value1 value2 value3
1 2000 1 2000
JLLagrange was on to the right idea. Use melt
from reshape2
to convert your data to long form before plotting.
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))
)
In light of your comment, your data should be in a different form. Essentially, you are considering value2
and value3
to be the same as year
, but with additional levels for value1
. Reconstruct your data like this:
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)
Then you can draw a plot with this:
(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")
)
)
(I've added a bit of jitter to the points so you can see where they overlap. You could also set an alpha
value in geom_point
.)