schloerke
commented
8 years ago To remove the warning, please upgrade your code from...
library(ggplot2)
library(GGally)
# using iris, as I do not have the 'ar' dataset
ggpairs(
iris[,1:4],
upper = list(params = c(size = 10)),
lower = list(continuous = 'smooth')
)
#Error in display_param_error() :
# 'params' is a deprecated argument. Please 'wrap' the function to supply arguments. help("wrap", package = "GGally")to...
ggpairs(
iris[,1:4],
upper = list(continuous = wrap(ggally_cor, size = 10)),
lower = list(continuous = 'smooth')
)
To move the axes into the diagonal, use the axisLabels parameter...
ggpairs(
iris[,1:4],
upper = list(continuous = wrap(ggally_cor, size = 10)),
lower = list(continuous = 'smooth'),
axisLabels = "internal"
)
Next, we make a custom correlation ggplot2 plot that uses data, mapping, and ... as parameters...
my_custom_cor <- function(data, mapping, color = I("grey50"), sizeRange = c(1, 5), ...) {
# get the x and y data to use the other code
x <- eval(mapping$x, data)
y <- eval(mapping$y, data)
ct <- cor.test(x,y)
sig <- symnum(
ct$p.value, corr = FALSE, na = FALSE,
cutpoints = c(0, 0.001, 0.01, 0.05, 0.1, 1),
symbols = c("***", "**", "*", ".", " ")
)
r <- unname(ct$estimate)
rt <- format(r, digits=2)[1]
# since we can't print it to get the strsize, just use the max size range
cex <- max(sizeRange)
# helper function to calculate a useable size
percent_of_range <- function(percent, range) {
percent * diff(range) + min(range, na.rm = TRUE)
}
# plot the cor value
ggally_text(
label = as.character(rt),
mapping = aes(),
xP = 0.5, yP = 0.5,
size = I(percent_of_range(cex * abs(r), sizeRange)),
color = color,
...
) +
# add the sig stars
geom_text(
aes_string(
x = 0.8,
y = 0.8
),
label = sig,
size = I(cex),
color = color,
...
) +
# remove all the background stuff and wrap it with a dashed line
theme_classic() +
theme(
panel.background = element_rect(
color = color,
linetype = "longdash"
),
axis.line = element_blank(),
axis.ticks = element_blank(),
axis.text.y = element_blank(),
axis.text.x = element_blank()
)
}
my_custom_cor(iris, aes(Sepal.Length, Sepal.Width))
Next, we make a custom 'smooth' ggplot2 plot that uses data, mapping, and ... as parameters...
my_custom_smooth <- function(data, mapping, ...) {
ggplot(data = data, mapping = mapping) +
geom_point(color = I("blue")) +
geom_smooth(method = "lm", color = I("black"), ...)
}
my_custom_smooth(iris, aes(Sepal.Length, Sepal.Width))
Custom final example
ggpairs(
iris[,1:4],
upper = list(continuous = my_custom_cor),
lower = list(continuous = my_custom_smooth),
axisLabels = "internal"
)
# slightly smaller labels
ggpairs(
iris[,1:4],
upper = list(continuous = wrap(my_custom_cor, sizeRange = c(1,3))),
lower = list(continuous = my_custom_smooth),
axisLabels = "internal"
)
Hope this helps!
Feel free to adjust the code to your needs. Now that custom plots may be inserted, you have full control over what goes in the plot space.
- Barret
yzh402
akhst7
ScottStetkiewicz
Palette RdYlGn looks pretty good, as we associate red and greed with positive and negative naturally.
Question received....
1) Sometimes, the R shows:
Why?
2) I used the following codes to create a correlation matrix for figure 1.
And I used the following ggpairs codes to create figure 2.
As you can see the font size varies with the size of the correlation coefficient in the 1st figure. I would like to produce something similar with ggpairs. I would also like to remove 'Corr:' and add an indicator of significance behind the coefficient (just like the 3rd figure below).
Would you please give me some suggestions or codes if possible?