grattan_axes | R Documentation |
Ensure your y- and x-axis are Grattan style guide-consistent and doesn't hang off the edge of the chart.
grattan_y_continuous(expand_bottom = 0, expand_top = 0.015, ...) scale_y_continuous_grattan(expand_bottom = 0, expand_top = 0.015, ...) grattan_x_continuous(expand_left = 0, expand_right = 0.015, ...) scale_x_continuous_grattan(expand_left = 0, expand_right = 0.015, ...)
expand_bottom |
default is 0. This will ensure that your x-axis is at the bottom value of your plotted data. Increase to add some buffer between the lowest point in your data and the x-axis. Note that the value is interpreted as a fraction of the total plotting space - a value of 1 will add white space equal to the whole area of your data. |
expand_top |
default is 0.015. This will ensure that a small amount of white space is added to the top of your chart. Increase to add more white space. |
... |
arguments passed to scale_y_continuous or scale_x_continuous |
expand_left |
default is 0. This will ensure your y-axis is at the lowest value of your plotted value. |
expand_right |
default is 0.015. This will ensure that a small amount of white space is added to the right of your chart. |
# Here's a basic chart in the Grattan style: library(ggplot2) p <- ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point() + theme_grattan() p # In the example above, the top label on the y-axis is hanging off the top. # To fix: p <- ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point() + grattan_y_continuous() + theme_grattan() p # Now the top of the chart looks fine, but the bottom has two points # (at the lower right) that are partially obscured. # We could fix this by doing: p <- ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point() + grattan_y_continuous(expand_bottom = 0.015) + theme_grattan() p # Alternatively, set the limits of the chart (in this example we'll set # the lower limit to 0, but you could use some other value # like 10 in this case).Note that by setting the second value of limits # to NA, we're telling ggplot2 to calculate theupper limit as usual based # on the data. All the usual arguments of `scale_y_continuous()` # (limits, breaks, labels, etc.) can be used. p <- ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point() + grattan_y_continuous(limits = c(0, NA)) + theme_grattan() p
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