Dataset

The dataset has three columns:

Date: This column contains dates starting from January 1, 2020, and continuing for 100 days.
Value: This column holds numbers. These numbers are created by adding random amounts to each other in a cumulative way. It’s like keeping a running total of random values.
Type: This column categorizes each row with one of three labels: a, b, or c.

# dataset with 3 lines named "a", "b" and "c"
set.seed(1)
period = 100
df = data.frame(Date = seq(as.Date("2020-01-01"),
                           by = "day",
                           length.out = period), 
                Value = c(cumsum(rnorm(period)),
                          cumsum(rnorm(period)),
                          cumsum(rnorm(period))),
                Type = c(rep("a", period),
                         rep("b", period),
                         rep("c", period)))

Package

For this post, we need the ggplot2 and gghighlight packages.

# Install the packages if not already done
# install.packages("ggplot2")
# install.packages("gghighlight")

# Load the package
library(ggplot2)
library(gghighlight)

Default line chart in ggplot2

Here’s what the default line chart output looks like with ggplot2:

Highlight specific lines

With the gghighlight() function and some criterion, we can indicate which line will be displayed.

In this case, it’s all lines where the maximum Value is greater than 10.

ggplot(df) +
  geom_line(aes(Date, Value, colour = Type)) +
  gghighlight(max(Value) > 10)

Properties of faded out lines

The gghighlight() function has an argument named unhighlighted_params that allows us to define what are the properties to use for the lines that does not meet our criterion.

In this case, we reduce the line width, change the color to blue and lower the opacity (alpha). We also change the line to dashed.

ggplot(df) +
  geom_line(aes(Date, Value, colour = Type), linewidth=1) +
  gghighlight(max(Value) > 10,
              unhighlighted_params = list(linewidth = 0.3,
                                          colour = alpha("blue", 0.7),
                                          linetype = "dashed"))

A more complex example

The gghighlight package is also very useful when combined with other packages such as hrbrthemes and patchwork.

In this example we use the power of gghighlight with the simplicity of patchwork for stacking graphs and hrbrthemes' beautiful themes.

library(hrbrthemes)
library(patchwork)

plot1 = ggplot(df) +
  geom_line(aes(Date, Value, colour = Type), linewidth=0.4, color='#4393C3') +
  gghighlight(max(Value) > 10,
              unhighlighted_params = list(linewidth = 0.3,
                                          colour = alpha("darkred", 0.7),
                                          linetype = "dotted"),
              use_direct_label = FALSE) +
  theme_bw() + xlab("") + ylab("")

plot2 = ggplot(df) +
  geom_line(aes(Date, Value, colour = Type), linewidth=0.4, color='#4393C3') +
  gghighlight(min(Value) < -10,
              unhighlighted_params = list(linewidth = 0.3,
                                          colour = alpha("darkred", 0.7),
                                          linetype = "dotted"),
              use_direct_label = FALSE) +
  theme_bw() 

plot1 / plot2 + plot_annotation(title = 'This chart is built with gghighlight')

Conclusion

In this post, we look at how to use the gghighlight package to highlight specific elements of a multi-part line chart. To find out more about how to customize a line chart, see the dedicated section.

Highlight specific elements in a line chart