Line Types in R: The Ultimate Guide for R Base Plot and GGPLOT - Datanovia (2024)

• Key R functions
• Show the different line types in R
• Change R base plot line types
• Change ggplot line types
• Conclusion

Key R functions

• plot(x, y, type = "b", lty = 1, lwd = 1, col = "blue") and lines(x, y, lty = 2, lwd = 1): Base R plot functions to create line plots.
• geom_line(aes(x, y), data = NULL, linetype = "dashed", color = "black", size = 1): ggplot2 function to create line plots.
• scale_linetype_manual(), scale_color_manual() and scale_size_manual(): ggplot2 functions to set manually lines type, color and size.

Show the different line types in R

The list of line types available in R, includes:

0. “blank”, 1. “solid”, 2. “dashed”, 3. “dotted”, 4. “dotdash”, 5. “longdash” and 6. “twodash”.

Note that, to specify line types, you can use either full names or numbers : 0, 1, 2, 3, 4, 5, 6. 0 is for “blank”, 1 is for “solid”, 2 is for “dashed”, and so on

The graph below illustrates the list of line types available in R:

library(ggpubr)show_line_types()

In the next sections, we’ll illustrate line type modification using the example of line plots created with the geom_line(). However, note that, the option linetype can be also applied on other ggplot functions, such as: geom_smooth, geom_density, geom_sgment, geom_hline, geom_vline, geom_abline, geom_smooth and more.

Change R base plot line types

Simple format of R lines functions:

• plot(x, y, type = "l", lty = 1). Create the main R base plot frame.
• lines(x, y, type = "l", lty = 1). Add lines onto the plot.

Key options:

• x, y: variables to be used for the x and y axes, respectively.
• type: display the data as line and/or point. Lowed values: l (display line only), p (show point only) and b (show both).
• pch and cex: set points shape and size, respectively.
• lty, lwd: set line types and thickness.
• col: change the color of point and line.
• xlab and ylab: for x and y axis labels, respectively.

Create a plot with multiple lines and set the legend lty. We start by plotting a first single line with a solid line type (lty = 1). Next, we add a second line with a dashed line style (lty = 2). Finally, we add a legend on the plot using the R base function legend(), which take the same col and lty arguments as the lines function. The option cex is used to set the legend text size.

# 1. Create some variablesx <- 1:10y1 <- x*xy2 <- 2*y1# 2. Plot a first lineplot(x, y1, type = "b", frame = FALSE, pch = 19, col = "red", xlab = "x", ylab = "y", lty = 1, lwd = 1)# 3. Add a second linelines(x, y2, pch = 18, col = "blue", type = "b", lty = 2, lwd = 1)# 4. Add a legend to the plot and set legend ltylegend("topleft", legend = c("Line 1", "Line 2"), col = c("red", "blue"), lty = 1:2, cex = 0.8)

Change ggplot line types

Data set: ToothGrowth

ToothGrowth$dose <- as.factor(ToothGrowth$dose)head(ToothGrowth, 3)

## len supp dose## 1 4.2 VC 0.5## 2 11.5 VC 0.5## 3 7.3 VC 0.5

1. Basic line plot showing the mean value of tooth length (len) by the dose of vitamin C (dose):

• Compute the mean of tooth length grouped by dose:

library(dplyr)df <- ToothGrowth %>% group_by(dose) %>% summarise(len.mean = mean(len))df

## # A tibble: 3 x 2## dose len.mean## <fct> <dbl>## 1 0.5 10.6## 2 1 19.7## 3 2 26.1

• Create a single line plot. Change the linetype option to “dashed”.

library(ggplot2)ggplot(data = df, aes(x = dose, y = len.mean, group = 1)) + geom_line(linetype = "dashed")+ geom_point()

2. Create a line plot for multiple groups. Change line types by groups.

• Data:

# Compute the mean of `len` grouped by dose and supplibrary(dplyr)df2 <- ToothGrowth %>% group_by(dose, supp) %>% summarise(len.mean = mean(len))df2

## # A tibble: 6 x 3## # Groups: dose [?]## dose supp len.mean## <fct> <fct> <dbl>## 1 0.5 OJ 13.2 ## 2 0.5 VC 7.98## 3 1 OJ 22.7 ## 4 1 VC 16.8 ## 5 2 OJ 26.1 ## 6 2 VC 26.1

• Line plot:

# Change line types by groupsggplot(df2, aes(x = dose, y = len.mean, group = supp)) + geom_line(aes(linetype = supp))+ geom_point()+ theme(legend.position = "top")# Change line types + colors by groups ggplot(df2, aes(x = dose, y = len.mean, group = supp)) + geom_line(aes(linetype = supp, color = supp))+ geom_point(aes(color = supp))+ theme(legend.position = "top")

3. Change the appearance of line types manually:

• scale_linetype_manual(): change line types
• scale_color_manual(): change line colors
• scale_size_manual(): change the size of lines

To be able to apply these functions, you should create a geom_line, which line types, color and size should be controlled by groups.

# Change manually line type and color manuallyggplot(df2, aes(x = dose, y = len.mean, group = supp)) + geom_line(aes(linetype = supp, color = supp))+ geom_point(aes(color = supp))+ scale_linetype_manual(values=c("solid", "dashed"))+ scale_color_manual(values=c("#00AFBB","#FC4E07"))

Conclusion

• Use lty and lwd options, for changing lines type and thickness in R base graphics:

x <- 1:10; y1 <- x*x; y2 <- 2*y1# Draw two linesplot(x, y1, type = "b", pch = 19, col = "red", lty = 1, lwd = 1)lines(x, y2, pch = 18, col = "blue", type = "b", lty = 2, lwd = 1)# Add legendlegend("topleft", legend = c("Line 1", "Line 2"), col = c("red", "blue"), lty = 1:2)

• Use linetype and size arguments in ggplot2 :

# Create some datax <- 1:10; y1 <- x*x; y2 <- 2*y1df <- data.frame( x = c(x, x), y = c(y1, y2), grp = as.factor(rep(c("A", "B"), each = 10)) )# Plotlibrary(ggplot2)ggplot(data = df, aes(x, y, group = grp)) + geom_line(aes(linetype = grp))+ geom_point()

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