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Changing the line color in ggplot2 plots is a simple task. You just need to use the scale_color_manual() function and pass it a vector of colors. This function allows you to specify the line color for each group in a plot. You can also use the scale_color_brewer() function to choose from a variety of color palettes and have ggplot2 automatically assign a color to each group in your plot. Additionally, you can bind the color to a variable in your data set so that the color changes dynamically with the data.
You can use the following basic syntax to specify line colors in ggplot2:
ggplot(df, aes(x=x, y=y, group=group_var, color=group_var)) +
geom_line() +
scale_color_manual(values=c('color1', 'color2', 'color3'))
The following example shows how to use this syntax in practice.
Example: Change Line Colors in ggplot2
Suppose we have the following data frame in R:
#create data frame df <- data.frame(store=c('A', 'A', 'A', 'B', 'B', 'B', 'C', 'C', 'C'), week=c(1, 2, 3, 1, 2, 3, 1, 2, 3), sales=c(9, 12, 15, 7, 9, 14, 10, 16, 19)) #view data frame df store week sales 1 A 1 9 2 A 2 12 3 A 3 15 4 B 1 7 5 B 2 9 6 B 3 14 7 C 1 10 8 C 2 16 9 C 3 19
Now suppose we create the following line plot in ggplot2 to visualize the total sales by week and by store:
library(ggplot2) #create line plot ggplot(df, aes(x=week, y=sales, group=store, color=store)) + geom_line(size=2)
By default, ggplot2 uses a with red, green, and blue for the lines.
However, you can use the scale_color_manual() function to specify your own colors for the lines:
library(ggplot2) #create line plot ggplot(df, aes(x=week, y=sales, group=store, color=store)) + geom_line(size=2) + scale_color_manual(values=c('orange', 'pink', 'red'))
The colors are now orange, pink, and red.
Note that you can also use hex color codes to specify the colors:
library(ggplot2) #create line plot ggplot(df, aes(x=week, y=sales, group=store, color=store)) + geom_line(size=2) + scale_color_manual(values=c('#063970', '#A69943', '#7843a6'))
The following tutorials explain how to perform other common tasks in ggplot2: