How to vary LINE color with a variable in R graph (ggplot or similar)

Question

I am trying to vary the color of the LINE in an R graph (within the same series of data). For example if you had points showing temperature for weeks of the year, and they're connected with geom_line() or equivalent, how would I show say the line being deeper red for higher temperature weeks and gradually changing to say yellow in colder weeks? (if BOTH points and line could vary across the same palette/gradient based on the same variable - say temperature, that would be ideal).

bp.df <- NULL
bp.weeks <- 26
bp.days <- 7 * bp.weeks
bp.df$day <- 1:bp.days
bp.df$week <- ceiling(bp.df$day / 7)
bp.mean.normal <- 100
bp.sd.normal <- 20

bp.df <- as.data.frame(bp.df)

bp.df$normal <- rnorm(nrow(bp.df),bp.mean.normal, bp.sd.normal)
bp.df$day <- as.numeric(bp.df$day)

# make sure ggplot2 is installed and loaded

g <- ggplot(bp.df, aes(x = day, y = normal, color = normal)) + 
    geom_point() + 
    geom_line(col = bp.df$normal)
g

Why do the line colors not match the levels of the "normal" variable? I understand that, since they connect two dots, the lines must "decide" which one's value to use, but this output seems to make the colors completely random.

If varying across a gradient won't work, how would I make the line be red for the first 50 days, green for the next 50, etc?

Answer 1

Try this:

g <- ggplot(bp.df, aes(x=day, y = normal, color = normal)) + geom_point() +
geom_line(aes(color=normal))

g

It seems the col argument is different than the color in the aes argument.