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The ggcharts
package currently offers two functions with a highlight
parameter: bar_chart()
and lollipop_chart()
. The usage is the same for both functions.
library(ggcharts)
library(dplyr)
data("biomedicalrevenue")
revenue2018 <- biomedicalrevenue %>%
filter(year == 2018)
In its most simple form the highlight
feature can be used to highlight a single bar or lollipop.
bar_chart(
revenue2018,
company,
revenue,
top_n = 10,
highlight = "Roche"
)
The color for the highlighted and non-highlighted values are automatically determined from the currently active ggcharts
theme, i.e. ggcharts_get_theme()
. Thus, changing the theme will change these colors.
ggcharts_set_theme("theme_ng")
bar_chart(
revenue2018,
company,
revenue,
top_n = 10,
highlight = "Roche"
)
To set the highlight and non-highlight colors manually you will need to pass a highlight_spec()
to the highlight
argument.
ggcharts_set_theme("theme_ggcharts")
spec <- highlight_spec(
what = "Roche",
highlight_color = "black",
other_color = "lightgray"
)
bar_chart(
revenue2018,
company,
revenue,
top_n = 10,
highlight = spec
)
To highlight more than one value pass a vector to highlight
.
bar_chart(
revenue2018,
company,
revenue,
top_n = 10,
highlight = c("Roche", "Novartis")
)
To highlight multiple values in different colors you will need to use a highlight_spec()
again.
spec <- highlight_spec(
what = c("Roche", "Novartis"),
highlight_color = c("steelblue", "darkorange")
)
lollipop_chart(
revenue2018,
company,
revenue,
top_n = 10,
highlight = spec
)
The highlight feature is particularly useful when used in conjunction with the facet
feature.
biomedicalrevenue %>%
filter(year %in% c(2012, 2014, 2016, 2018)) %>%
bar_chart(
company,
revenue,
facet = year,
top_n = 12,
highlight = "Bayer"
)
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.