Question

Suppose I have the following data frames:

df1 = data.frame(c11 = c(1:5), c12 = c(1:5))
df2 = data.frame(c21 = c(1:5), c22 = (c(1:5))^0.5)
df3 = data.frame(c31 = c(1:5), c32 = (c(1:5))^2)

I want to plot these as lines in the same plot/panel. I can do this by

p <- ggplot() + geom_line(data=df1, aes(x=c11, y = c12)) + 
     geom_line(data=df2, aes(x=c21,y=c22)) + 
     geom_line(data=df3, aes(x=c31, c32))

All these will be black. If I want them in a different color, I can specify the color explicitly as an argument to geom_line(). My question is can I specify a list of a few colors, say 5 colors, such as, red, blue, green, orange, gray, and use that list so that I do not have to explicitly specify the colors as an argument to geom_line() in case of each line. If the plot p contains 2 geom_line() statements then it will color them red and blue respectively. If it contains 3 geom_line statements, it will color them red, blue and green. Finally, how can I specify the legend for these plots. Even if I can give the colors as a vector at the end of p that would be great. Please let me know if the question is not clear.

Thanks.

Answer 1

ggplot2 works best if you work with a melted data.frame that contains a different column to specify the different aesthetics. Melting is easier with common column names, so I’d start there. Here are the steps I’d take:

• rename the columns
• melt the data which adds a new variables that we’ll map to the colour aesthetic
• define your colour vector
• Specify the appropriate scale with scale_colour_manual

‘

names(df1) <- c("x", "y")
names(df2) <- c("x", "y")
names(df3) <- c("x", "y")

newData <- melt(list(df1 = df1, df2 = df2, df3 = df3), id.vars = "x")

#Specify your colour vector
cols <- c("red", "blue", "green", "orange", "gray")

#Plot data and specify the manual scale
ggplot(newData, aes(x, value, colour = L1)) + 
  geom_line() +
  scale_colour_manual(values = cols)

Edited for clarity

The structure of newData:

'data.frame':   15 obs. of  4 variables:
 $ x       : int  1 2 3 4 5 1 2 3 4 5 ...
 $ variable: Factor w/ 1 level "y": 1 1 1 1 1 1 1 1 1 1 ...
 $ value   : num  1 2 3 4 5 ...
 $ L1      : chr  "df1" "df1" "df1" "df1" ...

And the plot itself: