28 Working with symbols and glyphs
marker.symbol values, and all the acceptable values can be accessed through plotly.js’
vals <- schema(F)$traces$scatter$attributes$marker$symbol$values vals <- grep("-", vals, value = T) plot_ly() %>% add_markers( x = rep(1:12, each = 11, length.out = length(vals)), y = rep(1:11, times = 12, length.out = length(vals)), text = vals, hoverinfo = "text", marker = list( symbol = vals, size = 30, line = list( color = "black", width = 2 ) ) )
In addition to these marker symbols, you can also use
add_text() to encode data with on-graph text. Moreover, the
add_text() function (i.e. a scatter trace with
mode="markers") enjoys a lot of the same properties as
add_markers() (i.e. a scatter trace with
mode="text"). As Figure 28.2 shows, similar to how we can supply typographical glyphs and/or unicode in a custom tooltip, you can supply a character vector of similar content to
add_text() (i.e. a scatter trace with
mode='text') which renders on-graph text. Furthermore, when using
text to render on-graph text, one can leverage the
hovertext attribute to display some different text on hover.
Having the ability to encode data with unicode means that we have a virtually endless number of ways to encode data in symbols/glyphs. Just for fun, Figure 28.3 demonstrates how you could plot all the activity emojis using the emo package and display the name of the emoji on hover (Wickham, François, and D’Agostino McGowan 2018).
Wickham, Hadley, Romain François, and Lucy D’Agostino McGowan. 2018. Emo: Easily Insert ’Emoji’. https://github.com/hadley/emo.