Transformations

• Several scale transformation functions that work on the x- or y-axis.
• All of these transformations do not affect the data, they just modify the axes.

• Every continuous scale takes a transform argument allowing for using transformations:

• You can construct your own transform by using scales::new_transform

• The following table lists some of the more common variants:

Name	Transformer	Function $f(x)$	Inverse $f^{-1}(x)$
"asn"	scales::transform_asn	$\tanh^{-1}(x)$	$\tanh(y)$
"exp"	scales::transform_exp ()	$e ^ x$	$\log(y)$
"identity"	scales::transform_identity()	$x$	$y$
"log"	scales::transform_log()	$\log(x)$	$e ^ y$
"log10"	scales::transform_log10()	$\log_{10}(x)$	$10 ^ y$
"log2"	scales::transform_log2()	$\log_2(x)$	$2 ^ y$
"logit"	scales::transform_logit()	$\log(\frac{x}{1 - x})$	$\frac{1}{1 + e(y)}$
"probit"	scales::transform_probit()	$\Phi(x)$	$\Phi^{-1}(y)$
"reciprocal"	scales::transform_reciprocal()	$x^{-1}$	$y^{-1}$
"reverse"	scales::transform_reverse()	$-x$	$-y$
"sqrt"	scales::scale_x_sqrt()	$x^{1/2}$	$y ^ 2$

• Let’s see an example:

• Remember you can transform the data manually first and opt not to do the transformation on the axes.
• The appearance of the geom will be the same, but the tick labels will be different.
  • If you transform the data, the axes will be labelled in the transformed space.
  • If you use a transformed scale, the axes will be labelled in the original data space.
• Regardless of which method you use, the transformation occurs before any statistical summaries. To transform after statistical computation use coord_trans().