geom_cor
will add the correlatin, method and p-value to the plot
automatically guessing the position if nothing else specidfied.
family font, size and colour can be used to change the format.
geom_cor(mapping = NULL, data = NULL, method = "spearman",
inherit.aes = TRUE, ...)
Arguments
mapping |
Set of aesthetic mappings created by aes() or
aes_() . If specified and inherit.aes = TRUE (the
default), it is combined with the default mapping at the top level of the
plot. You must supply mapping if there is no plot mapping. |
data |
The data to be displayed in this layer. There are three
options:
If NULL , the default, the data is inherited from the plot
data as specified in the call to ggplot() .
A data.frame , or other object, will override the plot
data. All objects will be fortified to produce a data frame. See
fortify() for which variables will be created.
A function will be called with a single argument,
the plot data. The return value must be a data.frame. , and
will be used as the layer data. |
method |
Method to calculate the correlation. Values are
passed to cor.test() . (Spearman, Pearson, Kendall). |
inherit.aes |
If FALSE , overrides the default aesthetics,
rather than combining with them. This is most useful for helper functions
that define both data and aesthetics and shouldn't inherit behaviour from
the default plot specification, e.g. borders() . |
... |
other arguments passed on to layer() . These are
often aesthetics, used to set an aesthetic to a fixed value, like
color = "red" or size = 3 . They may also be parameters
to the paired geom/stat. |
Details
It was integrated after reading this tutorial to extend
ggplot2 layers
See also
ggplot2::layer()
Examples