**R – scottishsnow**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

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I often find myself coming back to this answer I gave on Stack Overflow in 2014. It shows how to colour a plot based on an independent continuous variable using the base graphics package. In the answer I gave it’s about colouring boxplots, but it equally applies to adding colour to a scatter plot. I’ve decided to elaborate here, as much for my personal use as anyone else’s!

You’ll note that I set *pal* twice, the first time is if you want to define the colours yourself and the second for use with the RColorBrewer package. If you’ve not come across it before it’s an excellent resource for choosing plot colours, here’s a map implementation: http://colorbrewer2.org, and you can view the colours here.

# Make some dummy data df = data.frame(Year=1980:2010, Flow=rnorm(31, mean=150, sd=4), Temp=rnorm(31, mean=0, sd=2)) # Optionally set colours using RColorBrewer library(RColorBrewer) cols = brewer.pal(4, "Blues") # Define colour pallete pal = colorRampPalette(c("blue", "red")) # Use the following line with RColorBrewer pal = colorRampPalette(cols) # Rank variable for colour assignment df$order = findInterval(df$Temp, sort(df$Temp)) # Make plot plot(Flow ~ Year, df, pch=19, col=pal(nrow(df))[df$order]) # Add a simple legend legend("topright", col=pal(2), pch=19, legend=c(round(range(df$Temp), 1)))

Here are the resulting plots:

Of course, you could also accomplish this using the ggplot2 package.

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**R – scottishsnow**.

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