Go to TogaWare.com Home Page. Data Science Desktop Survival Guide
by Graham Williams
Duck Duck Go


Bar Chart Colour No Legend



ds %>%
  ggplot(aes(wind_dir_3pm, fill=wind_dir_3pm)) +
  geom_bar() +
  scale_y_continuous(labels=comma) +
  labs(x=vnames["wind_dir_3pm"], y="Count") +

Colour can add interest to a plot, though (unlike this example) it is usually good to use the colour to communicate further information about the data. Nonetheless, it adds to the attractiveness of the visualisation.

A spread of colour is added through the aesthetic fill=wind_dir_3pm. This will fill the bars with colour controlled by the different values of the variable wind_dir_3pm. As this is also the variable being plotted on the x-axis a different colour is chosen for each bar from a good default set of colours.

We add a ggplot2::theme() element here to remove the legend that would be displayed by default, by indicating that the legend.position="none". An alternative to turn the legend off is to provide show.legend=FALSE to the layer (i.e., ggplot2::geom_bar()). This then allows layer specific control of the legends.

Support further development by purchasing the PDF version of the book.
Other online resources include the GNU/Linux Desktop Survival Guide.
Books available on Amazon include Data Mining with Rattle and Essentials of Data Science.
Popular open source software includes rattle and wajig.
Hosted by Togaware, a pioneer of free and open source software since 1984.
Copyright © 2000-2020 Togaware Pty Ltd. . Creative Commons ShareAlike V4.